Climate Change AI Directory

Welcome to the (beta version of the) CCAI directory, a searchable list of people with experience and/or interest in doing impactful work at the intersection of climate change and machine learning.

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Our goal for this tool is to help users build connections, collaborations, and careers. If you have feedback or suggestions for improvements, please contact us at info@climatechange.ai!

Joined 🤖 Name Affiliation Location Short Bio Links Interests/Experience Seeking/Offering
2021-09-23

Galen Vincent
Carnegie Mellon University
Pittsburgh, PA
I'm a PhD student in the Statistics and Data Science department at Carnegie Mellon University. My research is focused on developing statistically rigorous and scientifically interpretable methods for analyzing environmental data.
Areas of Interest:
Climate and Earth science Disaster prediction, management, and relief Hybrid physical models
Areas of Experience:
Classification, regression, and supervised learning Interpretable ML Uncertainty quantification and robustness
Seeking:
Employment opportunities Internships Mentorship Networking
Offering:
Networking Research collaborations
2021-09-22
Andrea
Stevens Institute of Technology
Mexico City
Areas of Interest:
Disaster prediction, management, and relief
Areas of Experience:
Disaster prediction, management, and relief Policy
Seeking:
Research collaborations
Offering:
Mentorship
2021-09-22

Quentin Paletta
University of Cambridge
Cambridge, UK
Areas of Interest:
Computer vision and remote sensing Power and energy
Areas of Experience:
Computer vision and remote sensing Power and energy
2021-09-21

Sebastian Romero
Tracks GmbH
Berlin
Technical product manager, tree-hugger, data scientist, in love with mama earth
Areas of Interest:
Climate justice Computer vision and remote sensing Interpretable ML
2021-09-21
Ish Girwan
UK
Areas of Interest:
Behavioral and social science Computer vision and remote sensing Disaster prediction, management, and relief Natural language processing Policy
Areas of Experience:
Computer vision and remote sensing Natural language processing
Seeking:
Employment opportunities Internships Networking
Offering:
Mentorship Networking Startup co-founder
2021-09-20

Dickson Lukose
Monash University
Melbourne
I have over 25 years of experience in Applied AI working with technologies like Machine Learning, Deep Learning, Semantic Web, Knowledge Graphs, Social Network Analytics, and Natural Language Processing.
Areas of Interest:
Active learning Classification, regression, and supervised learning Data mining Natural language processing Time-series analysis Unsupervised and semi-supervised learning
Areas of Experience:
Agriculture Behavioral and social science

I also have extensive experience in Semantic Web, Knowledge Graphs and Ontology Modelling and Engineering.

Seeking:
Research collaborations
Offering:
Academic positions
2021-09-20

Zikri Bayraktar
Schlumberger
Cambridge, MA
I am a senior AI research scientist, currently focusing on carbon capture tech.
Areas of Interest:
Carbon capture and sequestration
Areas of Experience:
Natural language processing

I have over a decade long R&D experience post PhD in computational fields spanning from computational EM to semiconductors and from ML to carbon capture.

Seeking:
Mentorship Networking
Offering:
Mentorship Networking Startup co-founder
2021-09-20

Yamine Bouzembrak
WFSR
NL
AI in food safety
Areas of Interest:
Agriculture Causal and Bayesian methods Classification, regression, and supervised learning Climate and Earth science Computer vision and remote sensing
Areas of Experience:
Agriculture Causal and Bayesian methods Classification, regression, and supervised learning Computer vision and remote sensing Reinforcement learning and control Time-series analysis
Seeking:
Funding Research collaborations
Offering:
Research collaborations
2021-09-20

Sophie Purdom
Climate Tech VC
NY
I’m a sustainable business practitioner; first from the perspective of state & global policy, then at a major endowment, followed by a few years decking at Bain & Co., published a book along the way, and founded an agtech venture (raised +$15m). I now write a climate tech newsletter (15,000+ readers) and invest in early stage companies.
Areas of Interest:
Agriculture Carbon capture and sequestration Climate finance Disaster prediction, management, and relief Industry
Areas of Experience:
Climate finance
Offering:
Funding
2021-09-20

Hillary Scannell
Columbia University
New York, NY
Postdoctoral Research Scientist in the Climate Data Science Lab at the Lamont-Doherty Earth Observatory
Areas of Interest:
Climate and Earth science Computer vision and remote sensing Disaster prediction, management, and relief Interpretable ML
Seeking:
Mentorship Networking Research collaborations
Offering:
Mentorship Networking Research collaborations
2021-09-20
Paul Christopher Ulrich
Consultant
New Haven, CT
I have worked on issues related to climate change in Asia Pacific for NGOs and the GSMA, the trade organization representing global mobile operators. I have also done policy work on AI for the GSMA. I am an economist by training with degrees from Stanford and Harvard.
Areas of Interest:
Behavioral and social science Carbon capture and sequestration Climate finance Climate justice Disaster prediction, management, and relief Ecosystems and natural resources Policy Societal adaptation
Areas of Experience:
Behavioral and social science Classification, regression, and supervised learning Climate finance Disaster prediction, management, and relief Ecosystems and natural resources Forestry and other land use Industry Policy Time-series analysis
Offering:
Mentorship Networking Pro-bono consulting Research collaborations Startup co-founder
2021-09-20

Garrett Kinman
McGill University
Montreal, QC, Canada
I am an MSc Electrical Engineering student at McGill University in Montreal, focusing on embedded ML. I'm particularly interested in what embedded ML and intelligent control can do to help with precision and sustainable agriculture and forestry.
Areas of Interest:
Agriculture Computer vision and remote sensing Ecosystems and natural resources Forestry and other land use Reinforcement learning and control
Areas of Experience:
Classification, regression, and supervised learning Computer vision and remote sensing Reinforcement learning and control
Seeking:
Employment opportunities Mentorship Networking
Offering:
Networking
2021-09-20

Martin Röck
KU Leuven
Cologne, Germany
I'm a built environment researcher focused on environmental modelling of buildings and building stocks using life cycle-based assessment methods. I have been working on a joint effort to compile data on life cycle emissions of buildings and would be glad to find partners in this community for exploring it further!
Areas of Interest:
Classification, regression, and supervised learning Climate and Earth science Uncertainty quantification and robustness
Areas of Experience:
Buildings and cities Industry Policy

Much of my research focuses on the assessment of 'embodied impacts' of buildings, i.e. environmental impacts (GHG emissions, etc) related to construction material processing (production, transport, end-of-life treatment). Embodied GHG emission are a hidden challenge for effective climate change mitigation in buildings and cities, as we could show in earlier research.

Seeking:
Funding Research collaborations
Offering:
Data Research collaborations
2021-09-20

Zachary Labe
Colorado State University
Fort Collins, CO
I am a postdoc in the Department of Atmospheric Science at Colorado State University. Broadly, I am interested in a signal-to-noise problem. The signal is climate change. The noise is weather. My research intends to disentangle the two components within large ensembles of climate models.
Areas of Interest:
Classification, regression, and supervised learning Climate and Earth science Interpretable ML Time-series analysis Uncertainty quantification and robustness Unsupervised and semi-supervised learning
Areas of Experience:
Climate and Earth science Interpretable ML

Interested in using novel data science methods to extract climate change signals in large ensemble simulations

Seeking:
Academic positions Employment opportunities Networking Research collaborations
Offering:
Data Mentorship Networking Research collaborations
2021-09-14
Ashwin Shirsat
North Carolina State University
NC
Areas of Interest:
Active learning Classification, regression, and supervised learning Data mining Interpretable ML Power and energy Reinforcement learning and control Time-series analysis Uncertainty quantification and robustness
Areas of Experience:
Active learning Power and energy Uncertainty quantification and robustness
Seeking:
Employment opportunities Networking Research collaborations Startup co-founder
Offering:
Mentorship Networking Pro-bono consulting
2021-09-13
Abhishek Bhan
Apple, Columbia University
San Fransisco Bay Area
I am currently working as a SWE at Apple, having just finished grad school at Columbia University. In my free time, I like to read, climb and play basketball and badminton. I have been trying to be environmentally conscious for a number of years now and have taken small steps to change my lifestyle over the years to make it more carbon neutral. There's lots more to do though and I believe the intersecion of AI and climate change is a domain that has a lot of (untapped) potential! I look forward to getting to know all of you and hopefully collaborating in the future to help realize that potential. Cheers!
Areas of Interest:
Behavioral and social science Climate and Earth science Climate finance Transportation
Areas of Experience:
Causal and Bayesian methods Meta- and transfer learning Reinforcement learning and control
Seeking:
Mentorship Networking
Offering:
Research collaborations
2021-09-10
Pierre McWhannel
SFU
Vancouver, BC, Canada
PhD student in Sustainable Energy Engineering, exploring the intersection of AI and energy systems modelling in an effort against climate change.
Areas of Interest:
Classification, regression, and supervised learning Data mining Meta- and transfer learning Policy Power and energy Reinforcement learning and control Time-series analysis Uncertainty quantification and robustness
Areas of Experience:
Classification, regression, and supervised learning Data mining Meta- and transfer learning Natural language processing Time-series analysis Unsupervised and semi-supervised learning
Seeking:
Mentorship Research collaborations
Offering:
Networking Research collaborations
2021-09-10

Sara El Mekkaoui
Ecole Mohammadia d'Ingénieurs, Mohammed V University in Rabat
Rabat, Morocco
PhD student in Machine Learning for Maritime Logistics, interested in Blue Shipping.
Areas of Interest:
Classification, regression, and supervised learning Interpretable ML
Areas of Experience:
Industry Transportation
Seeking:
Networking Research collaborations
Offering:
Networking
2021-09-09

Zane Selvans
Catalyst Cooperative
Guanajuato, Mexico
I wrangle US open energy system data for researchers, activists, policymakers, and journalists working on climate & energy policy.
Areas of Interest:
Climate finance Policy Power and energy
Areas of Experience:
Climate and Earth science Climate finance Policy Power and energy Transportation

I am primarily interested in using ML/AI to do record linkage, entity resolution, outlier detection, missing value imputation, and automated data labeling. We have a lot of messy data to wrangle and rule-based data data cleaning is too tedious and fragile.

Seeking:
Data Mentorship Paid consulting Pro-bono consulting Research collaborations
Offering:
Data Employment opportunities Internships Networking Paid consulting Research collaborations
2021-09-08

Shanti
UMich
MI
Interested in creating solutions for Energy Poverty and efficiency using AI. At present working in Data Science internships with NOAA (weather prediction using ML) and an AI startup. Pursued Masters in Geospatial Data science at UMich. In the past, worked in India in sectors of Renewable Energy (with SELCO Foundation) , Education ( with Teach For India and SINE, IIT Bombay) .
Areas of Interest:
Climate and Earth science Climate justice Disaster prediction, management, and relief Power and energy Reinforcement learning and control
Areas of Experience:
Active learning Classification, regression, and supervised learning Climate justice Data mining Ecosystems and natural resources Time-series analysis
Seeking:
Data Employment opportunities Internships Mentorship Networking Research collaborations
2021-09-06
Javed Ali
University of Central Florida
I am a Water Resources Engineer and Multi-hazards Researcher. I’m pursuing a Ph.D. in Civil Engineering (Major: Water Resources Engineering) at the University of Central Florida (UCF). My work involves multi-hazards risk analysis and studying hydrometeorological extreme events and their interrelationships using machine learning and statistical methods.
Areas of Interest:
Classification, regression, and supervised learning Climate and Earth science Data mining Disaster prediction, management, and relief Ecosystems and natural resources Time-series analysis
Areas of Experience:
Classification, regression, and supervised learning Climate and Earth science Data mining Disaster prediction, management, and relief Ecosystems and natural resources Time-series analysis Unsupervised and semi-supervised learning
Seeking:
Funding Internships Mentorship Networking Research collaborations
Offering:
Mentorship Networking
2021-09-03

Olga Mierzwa-Sulima
Data Scientist and Data4Good Lead at Appsilon. Supporting organizations and researchers tackling climate change by offering our service (data science, dashboards, and ML Vision) pro-bono.
Areas of Interest:
Agriculture Carbon capture and sequestration Climate and Earth science Power and energy
Areas of Experience:
Computer vision and remote sensing
Seeking:
Mentorship Networking Research collaborations
Offering:
Paid consulting Pro-bono consulting
2021-09-02
Neha Puri
Faculty AI
London, UK
Green finance specialist, with over a decade of experience in low-carbon infrastructure / technologies in Europe, South Asia and Americas. Currently Commercial Principal at Faculty AI.
Areas of Interest:
Buildings and cities Causal and Bayesian methods Climate finance Computer vision and remote sensing Interpretable ML Time-series analysis Transportation
Areas of Experience:
Buildings and cities Causal and Bayesian methods Climate finance Computer vision and remote sensing Interpretable ML Policy Power and energy Time-series analysis Transportation Uncertainty quantification and robustness

Experience of leading infra projects focussing on asset inspection (Computer Vision), anomaly detection (Unsupervised Time Series Analysis), and operational forecasting (Bayesian Hierarchical Modelling).

Seeking:
Networking Paid consulting Pro-bono consulting Research collaborations
Offering:
Networking Research collaborations
2021-09-02
Michael Orimogunje
University of Huddersfield
United Kingdom
Areas of Interest:
Agriculture Buildings and cities Ecosystems and natural resources Human-computer Interaction Unsupervised and semi-supervised learning
Areas of Experience:
Agriculture Classification, regression, and supervised learning Computer vision and remote sensing Data mining Ecosystems and natural resources Natural language processing Unsupervised and semi-supervised learning

Researcher at the University of Huddersfield on intelligent system with self-rectifying capability for autonomous farming powered by solar energy.

Seeking:
Networking Research collaborations
2021-09-01

Alan Cordova
Fluence Energy
San Francisco, CA
Areas of Interest:
Power and energy
Areas of Experience:
Power and energy
Offering:
Employment opportunities
2021-08-31

Brian Kent
The Crosstab Kite
Data scientist and ML engineer, currently focused on translating digital experimentation lessons to real-world applications in climate R&D. Please reach out and say hi!
Areas of Experience:
Causal and Bayesian methods Classification, regression, and supervised learning Reinforcement learning and control
Seeking:
Employment opportunities Funding Networking Paid consulting Startup co-founder
2021-08-30

Andy Chen
Afresh Technologies, Stanford Food Design
ML Engineering at Afresh Technologies (reducing fresh food waste at the grocery level!) ||| Stanford Math + Computer Science ||| Stanford Food Recovery
Areas of Interest:
Agriculture Behavioral and social science Classification, regression, and supervised learning Generative modeling Reinforcement learning and control Uncertainty quantification and robustness
Areas of Experience:
Classification, regression, and supervised learning Industry Time-series analysis

My experience and interests are primarily in food systems, especially in food waste reduction. I'm currently doing ML engineering at Afresh Technologies!

Seeking:
Mentorship Networking Research collaborations
Offering:
Networking Research collaborations
2021-08-27
Olivier Asselin
Ouranos, Montreal (CA)
I studied the fluid dynamics of the atmosphere and oceans in academia for about 10 years. Last year, I left academia to join Ouranos, a Montreal-based NGO advising the Quebec government and other actors on climate adaptation. My current work focuses on the climate effects of forests.
Areas of Interest:
Agriculture Climate and Earth science Forestry and other land use Power and energy Societal adaptation
Areas of Experience:
Climate and Earth science Forestry and other land use
Seeking:
Mentorship Networking
2021-08-24

Csaba Bán
Bosch, ADAS Software Engineer
I'm a graduate physicsist who works in the automotive industry as a software engineer for advanced driver assictance systems. One of my hobbies is deep learning.
Areas of Interest:
Behavioral and social science Buildings and cities Classification, regression, and supervised learning Climate and Earth science Climate finance Computer vision and remote sensing Data mining Disaster prediction, management, and relief Ecosystems and natural resources Forestry and other land use Industry Natural language processing Power and energy Recommender systems Reinforcement learning and control Time-series analysis Transportation Unsupervised and semi-supervised learning
Areas of Experience:
Causal and Bayesian methods Classification, regression, and supervised learning Data mining Time-series analysis Transportation

I'm a graduate physicsist who works in the automotive industry as a software engineer for advanced driver assictance systems. One of my hobbies is deep learning. I have experience with deep learning for image classification, time series datas, Bayesien classification methods, web-scraping and willing to learn mor about other deepl learning areas with a special interest in reinforcement learning.

Seeking:
Data Employment opportunities Mentorship Networking
2021-08-23
Tushar Gupta
I help Financial Institutions and Corporates manage their climate risk and align it with their decarbonisation strategy
2021-08-21

Alireza Shams
Process Data Scientist at Svante Inc.
Ph.D. in Chemical Engineering with over 15 years of experience as a process specialist, consultant, and researcher in energy, acid gas removal & CO2 capture, materials, liquid-crystal polymers, petrochemical, biotechnology, and environmental projects.
Areas of Interest:
Data mining Generative modeling Meta- and transfer learning Unsupervised and semi-supervised learning
Areas of Experience:
Carbon capture and sequestration Classification, regression, and supervised learning Generative modeling Industry Time-series analysis

R&D Scientist & Process Specialist, Experienced in Industrial Design & Scale-up, Modelling & Simulation, TEA, Data Analysis, Machine Learning, and AI.

Seeking:
Networking Research collaborations
Offering:
Pro-bono consulting
2021-08-20

Kalyan Nadimpalli
International Institute of Information Technology, Bangalore
I'm an Integrated Masters student in CS, particularly interested in AI and am passionate about helping in the struggle towards stopping climate change.
Areas of Interest:
Classification, regression, and supervised learning Climate and Earth science Computer vision and remote sensing Forestry and other land use Reinforcement learning and control
Areas of Experience:
Causal and Bayesian methods Classification, regression, and supervised learning Computer vision and remote sensing Natural language processing Reinforcement learning and control
Seeking:
Mentorship Networking Research collaborations
Offering:
Networking Research collaborations
2021-08-19

Diego Kiedanski
Tryolabs
Areas of Interest:
Agriculture Buildings and cities Climate finance Power and energy Reinforcement learning and control Time-series analysis
Areas of Experience:
Power and energy Reinforcement learning and control Time-series analysis
Seeking:
Mentorship Networking Research collaborations
Offering:
Mentorship Research collaborations
2021-08-17

Jakob Heller
deeeper.technology GmbH
Machine Learning professional with a strong interest in remote sensing. Executive to a company that tracks land cover change with remote sensing down to submeter resolution.
Areas of Interest:
Ecosystems and natural resources Forestry and other land use
Areas of Experience:
Classification, regression, and supervised learning Computer vision and remote sensing Unsupervised and semi-supervised learning

deeeper.technology gathers large datasets for land cover and its change down to submeter resolution.

Seeking:
Networking Research collaborations
Offering:
Networking Paid consulting
2021-08-16
Asmaa
Vodafone
AI Solution Architect
Areas of Interest:
Agriculture Climate and Earth science Policy
Areas of Experience:
Classification, regression, and supervised learning Disaster prediction, management, and relief Recommender systems
Seeking:
Networking Research collaborations
Offering:
Paid consulting Research collaborations
2021-08-14

Peter Dolan
Waymo
I'm a research engineer with broad interests, formerly at DeepMind working on climate change projects including wind power and energy efficiency.
Areas of Interest:
Agriculture Carbon capture and sequestration Climate and Earth science Climate justice Disaster prediction, management, and relief
Areas of Experience:
Buildings and cities Climate and Earth science
Seeking:
Employment opportunities Networking Paid consulting Pro-bono consulting Research collaborations Startup co-founder
Offering:
Employment opportunities Mentorship Networking Research collaborations
2021-08-13
Rama Ramakrishnan
MIT
2021-08-12

Kiana Alikhademi
PhD student at the University of Florida
Areas of Interest:
Causal and Bayesian methods Classification, regression, and supervised learning Climate justice Computer vision and remote sensing Generative modeling Interpretable ML Policy Transportation
Areas of Experience:
Causal and Bayesian methods Classification, regression, and supervised learning Data mining Interpretable ML Societal adaptation Transportation
Seeking:
Employment opportunities Funding Mentorship Research collaborations
Offering:
Networking Research collaborations
2021-08-10

Carl Boettiger
UC Berkeley
Assistant professor in Environmental Science, Policy, and Management at UC Berkeley. Interested in ecological systems, natural resource management, and possible applications of Deep Reinforcement Learning to conservation and management. Also interested in issues of ethics and power arising from algorithmic approaches to conservation.
Areas of Interest:
Ecosystems and natural resources Forestry and other land use Reinforcement learning and control Uncertainty quantification and robustness
Areas of Experience:
Ecosystems and natural resources Reinforcement learning and control Time-series analysis
Seeking:
Research collaborations
Offering:
Data Employment opportunities Research collaborations
2021-08-10
Nandakumar Krishnaswamy
Areas of Interest:
Agriculture Behavioral and social science Buildings and cities Carbon capture and sequestration Climate and Earth science Climate finance Disaster prediction, management, and relief Ecosystems and natural resources Forestry and other land use Industry Societal adaptation Transportation
2021-08-09

Anson Ho
University of St Andrews
I'm a recent physics graduate at the University of St Andrews, interested in the relationship between AI, scientific research and effective altruism. This means trying to use AI to further scientific understanding (e.g. through interpretable ML) and technologies, while also keeping the ethical and safety issues of AI a priority. Within climate change, I'm interested in improving long-term forecasts, especially regarding extreme climate events.
Areas of Interest:
Causal and Bayesian methods Climate and Earth science Interpretable ML Reinforcement learning and control Uncertainty quantification and robustness
Areas of Experience:
Classification, regression, and supervised learning
Seeking:
Mentorship Networking
2021-08-06

Tom Corringham
Scripps Institution of Oceanography, University of California San Diego
Staff Research Economist at Scripps Institution of Oceanography's Department of Climate and Atmospheric Sciences. My research focuses on quantifying the costs of extreme weather events related to climate change to inform interventions that protect vulnerable populations.
Areas of Interest:
Behavioral and social science Classification, regression, and supervised learning Climate and Earth science Climate finance Climate justice Disaster prediction, management, and relief Natural language processing Policy Societal adaptation Unsupervised and semi-supervised learning
Areas of Experience:
Behavioral and social science Climate and Earth science Disaster prediction, management, and relief Natural language processing Policy Societal adaptation
Seeking:
Data Funding Mentorship Networking Research collaborations
Offering:
Data Mentorship Networking Research collaborations
2021-08-05
Allison Campbell
Pacific Northwest National Laboratory
I'm a staff scientist in the Electricity, Infrastructure, and Buildings Division at PNNL. I'm also working towards a PhD in Bayesian estimation of net load at UNC Charlotte.
Areas of Interest:
Causal and Bayesian methods Generative modeling Power and energy Time-series analysis Uncertainty quantification and robustness
Areas of Experience:
Causal and Bayesian methods Industry Power and energy Time-series analysis Uncertainty quantification and robustness
Seeking:
Mentorship Research collaborations
Offering:
Networking Research collaborations
2021-08-05
Pranav Bhosale
BITS Pilani
Starting out as a software developer. Interested in tech for social good.
Areas of Interest:
Climate and Earth science Policy Unsupervised and semi-supervised learning
Seeking:
Mentorship Networking
2021-08-04

Jack Lynch
NC State University / Masterful AI
I'm an undergraduate and machine learning engineer interested in the application of domain adaptation and unsupervised learning to geospatial machine learning.
Areas of Interest:
Carbon capture and sequestration Computer vision and remote sensing Generative modeling Interpretable ML Natural language processing Time-series analysis Unsupervised and semi-supervised learning
Areas of Experience:
Computer vision and remote sensing Unsupervised and semi-supervised learning
Seeking:
Data Mentorship Networking Research collaborations
Offering:
Networking Research collaborations
2021-08-04

Miguel-Ángel Fernández-Torres
Image and Signal Processing (ISP) Group, Image Processing Laboratory (IPL), Universitat de València, Spain
I work at present as a postdoctoral researcher in the ERC USMILE project, taking part in the Image and Signal Processing Group at the Universitat de València, Spain. My current research within the area of Machine Learning for Earth and Climate Sciences involves the design and understanding of explainable deep generative models and machine attention mechanisms to be deployed for anomaly and extreme event detection.
Areas of Interest:
Causal and Bayesian methods Climate and Earth science Computer vision and remote sensing Disaster prediction, management, and relief Generative modeling Interpretable ML Unsupervised and semi-supervised learning
Areas of Experience:
Causal and Bayesian methods Computer vision and remote sensing Generative modeling Interpretable ML Unsupervised and semi-supervised learning
Seeking:
Data Networking Research collaborations
2021-08-03
Thomas Walther
Utrecht University
Assistant Professor of Finance with research on financial econometrics; climate/energy/commodity finance
Areas of Interest:
Active learning Classification, regression, and supervised learning Climate finance Ecosystems and natural resources Industry Interpretable ML Natural language processing Policy Power and energy Reinforcement learning and control Time-series analysis Uncertainty quantification and robustness Unsupervised and semi-supervised learning
Areas of Experience:
Climate finance Time-series analysis
Seeking:
Funding Mentorship Networking Research collaborations
Offering:
Networking
2021-08-03

Geneviève Patterson
Visual Supply Company (VSCO)
I'm the Head of Applied Research @ VSCO and I'm co-developing the CCAI Course for Summer School 2022. Before joining VSCO, I was CTO of the TRASH app. Before that I was a Postdoctoral Researcher at Microsoft Research New England. My work is about creating dialog between AI and people. My interests include video understanding, visual attribute discovery, human-in-the-loop systems, fine-grained object recognition, AI for climate science, and active learning. I received my PhD from Brown University in 2016 under the direction of James Hays.
2021-08-03

Santonu Goswami
Indian Space Research Organization
I am senior scientist with the National Remote Sensing Centre - ISRO and based in Hyderabad, India. My work is in understanding the various ecosystem processes such as coastal ecosystem dynamics, permafrost landscape dynamics using a data-driven approach using traditional remote sensing methods as well as leveraging the power of Artificial Intelligence in finding newer insights. I am open for collaborations and discuss about exciting ideas of mutual interests.
Areas of Interest:
Classification, regression, and supervised learning Climate and Earth science Computer vision and remote sensing Disaster prediction, management, and relief Ecosystems and natural resources Forestry and other land use Generative modeling Natural language processing Reinforcement learning and control Time-series analysis Unsupervised and semi-supervised learning
Areas of Experience:
Agriculture Buildings and cities Classification, regression, and supervised learning Climate and Earth science Computer vision and remote sensing Data mining Disaster prediction, management, and relief Ecosystems and natural resources Forestry and other land use Generative modeling Hybrid physical models Natural language processing Reinforcement learning and control Time-series analysis Unsupervised and semi-supervised learning
Seeking:
Networking Research collaborations Startup co-founder
Offering:
Mentorship Pro-bono consulting Research collaborations
2021-08-03
James Crowley
Experienced CTO/founder in the SaaS fintech world, now working with start-ups and NGOs focused on climate
Areas of Interest:
Carbon capture and sequestration Climate finance Power and energy
Areas of Experience:
Climate finance

Experience includes building platforms streaming high volume IoT data from energy storage devices to data collection for agroforestry. Looking to build my ML expertise - and share my existing SaaS expertise.

Seeking:
Networking Paid consulting
Offering:
Mentorship Pro-bono consulting
2021-08-03

Duncan Watson-Parris
University of Oxford
Areas of Interest:
Causal and Bayesian methods Climate and Earth science Hybrid physical models
Areas of Experience:
Climate and Earth science
Seeking:
Academic positions Research collaborations
Offering:
Research collaborations
2021-07-31
Cengiz Avcı
Istanbul Technical University
BSc Geomatics Engineering student at Istanbul Technical University
Areas of Interest:
Computer vision and remote sensing
Areas of Experience:
Classification, regression, and supervised learning Computer vision and remote sensing
Seeking:
Funding Mentorship Networking Research collaborations
2021-07-30

Avni Kothari
UC San Diego
I'm a masters student at UC San Diego. I just at the beginning on my journey to work in the space of AI and Climate Change. I've formally studied math and economics and worked as a software engineer for 6 year.
Areas of Interest:
Buildings and cities Climate justice Power and energy
Seeking:
Mentorship Networking Research collaborations
2021-07-30

Heather Couture
Pixel Scientia Labs
Fighting cancer & climate change with AI. Distilling the latest research to help R&D teams implement better models and create an impact. CV/ML/DL Consultant
Areas of Interest:
Classification, regression, and supervised learning Computer vision and remote sensing Generative modeling Interpretable ML Meta- and transfer learning Unsupervised and semi-supervised learning
Areas of Experience:
Classification, regression, and supervised learning Computer vision and remote sensing Interpretable ML Meta- and transfer learning Power and energy Unsupervised and semi-supervised learning

Primarily focused on computer vision for remote sensing

Seeking:
Paid consulting
Offering:
Employment opportunities
2021-07-29

Christoph Klemenjak
University of Klagenfurt
Hello, my name is Christoph. I have spent the past four years working as a research and teaching assistant at the University of Klagenfurt. My research has mainly been related to applying Machine Learning approaches to Energy Disaggregation, also known as Non-Intrusive Load Monitoring. During this time, I demonstrated my ability to meet high expectations, maintain strong attention to detail, and deliver results on time. Besides research, I was given the chance to share knowledge with students in the form of mentoring. How would I describe myself? Nothing excites me more than a good book. I believe in life-long learning. I am a team player. I am curious. Coffee. You are most welcome to contact me. I am currently looking for new job opportunities that not only get me excited but also bear the chance to make an impact.
Areas of Interest:
Industry Meta- and transfer learning Societal adaptation Unsupervised and semi-supervised learning
Areas of Experience:
Classification, regression, and supervised learning Power and energy Time-series analysis
Seeking:
Academic positions Employment opportunities
Offering:
Networking Research collaborations
2021-07-29
Pia Faustino
Thinking Machines Data Science
I am the Director for Sustainability at Thinking Machines, where I lead the company's mission to use technology for social and environmental good. We work with government and nonprofit partners to address challenges in public health, humanitarian response, and sustainable development using data science.
Areas of Interest:
Agriculture Carbon capture and sequestration Ecosystems and natural resources Forestry and other land use Power and energy Societal adaptation
Areas of Experience:
Active learning Classification, regression, and supervised learning Computer vision and remote sensing Data mining Interpretable ML Natural language processing Time-series analysis

Thinking Machines specializes in leading-edge data platforms and custom cloud AI solutions to match various business needs and social sector use cases. Our GeoAI solution uses remote sensing techniques, geospatial data, and machine learning to leverage location intelligence for grounded decision-making, while our DocAI solution uses NLP to turn unstructured documents into structured data and rapidly extract valuable insights. Lastly, our Customer Intelligence solution brings together terabytes of siloed data to fast-track customer data insights.

Seeking:
Funding Networking Paid consulting Research collaborations
Offering:
Data Employment opportunities Research collaborations
2021-07-29

Thomas Y. Chen
Academy for Mathematics, Science, and Engineering
Thomas Chen is a student and early-career machine learning researcher from the Academy for Mathematics, Science, and Engineering (NYC metro area). He is primarily interested in applying ML and computer vision to real-world climate adaptation (e.g. deep learning-based computer vision for damage assessment post-natural disaster). He has been an invited speaker at conferences like the IEEE Conference on Technologies for Sustainability, American Geophysical Union Fall Meeting, and the Energy Anthropology Network. Thomas has also spoken at events like NeurIPS and CVPR workshops, Applied Machine Learning Days, the Open Data Science Conference, and Machine Learning Week Europe. He is a leading voice in the area of machine learning-driven earth observation (EO) applications. Thomas is a member of the U.S. Technology Policy Committee (Association for Computing Machinery) and the Research Data Alliance.
Areas of Interest:
Buildings and cities Carbon capture and sequestration Classification, regression, and supervised learning Climate and Earth science Computer vision and remote sensing Data mining Disaster prediction, management, and relief Ecosystems and natural resources Generative modeling Interpretable ML Meta- and transfer learning Natural language processing Policy Societal adaptation Time-series analysis Transportation
Areas of Experience:
Buildings and cities Classification, regression, and supervised learning Computer vision and remote sensing Data mining Disaster prediction, management, and relief Interpretable ML Policy Societal adaptation

Check out my paper on interpretable computer vision for damage assessment and disaster relief using satellite imagery at the NeurIPS 2020 workshop!

Seeking:
Data Employment opportunities Funding Mentorship Networking Research collaborations Startup co-founder
Offering:
Networking Research collaborations Startup co-founder
2021-07-28

Anya Schukin
I’m a Paris-based ML software engineer, originally from San Francisco. Masters in CS / AI from École 42 Paris, with experience in technical product R&D, project management, and in a past life I founded and scaled a digital travel + culture publication. I want to use my skills to affect environmental change at 10x scale. If you have any career opportunities that touch on tech x product x data x environment, shoot me a message!
Areas of Interest:
Carbon capture and sequestration Computer vision and remote sensing Disaster prediction, management, and relief Ecosystems and natural resources Forestry and other land use Meta- and transfer learning Natural language processing
Areas of Experience:
Classification, regression, and supervised learning Computer vision and remote sensing Recommender systems
Seeking:
Employment opportunities Mentorship Networking
2021-07-26

Jose Cordova-Garcia
ESPOL University
I am an Assistant Professor at ESPOL University in Guayaquil, Ecuador. I received my PhD from Stony Brook University where I worked on data-driven monitoring and control of failures in power grids. My research focuses in optimization and machine learning applications in Smart Grids and data networks. At ESPOL I lead a campus-wide initiative towards generating user-centered automated recommendations for energy efficiency.
Areas of Interest:
Buildings and cities Classification, regression, and supervised learning Generative modeling Hybrid physical models Power and energy Reinforcement learning and control Uncertainty quantification and robustness
Areas of Experience:
Classification, regression, and supervised learning Hybrid physical models Power and energy
Seeking:
Data Networking Research collaborations
Offering:
Networking Research collaborations
2021-07-26

Simone Nsutezo Fobi
Columbia University
I am a PhD student, in Mechanical Engineering at Columbia University. My research focuses on Electricity Demand Analytics & Prediction and Energy System Design . Specifically, my work combines large amounts of electricity consumption data (obtained from electric meters) with remote sensed satellite imagery, to infer electricity demand from satellite imagery.
Areas of Interest:
Classification, regression, and supervised learning Computer vision and remote sensing Power and energy Unsupervised and semi-supervised learning
Areas of Experience:
Classification, regression, and supervised learning Computer vision and remote sensing Power and energy Unsupervised and semi-supervised learning
Seeking:
Networking Research collaborations
2021-07-26

Tegan Maharaj
University of Toronto
I'm an Assistant Professor at the University of Toronto, and did my PhD at Mila. Research primarily in deep representation learning & predictive methods in ecological modeling and environmental risk assessment, as well as real-world generalization, learning theory, and practical auditing tools (e.g. unit tests, sandboxes). Co-founder of CCAI, current Peer Review and Publications Lead.
Areas of Interest:
Classification, regression, and supervised learning Climate and Earth science Climate justice Disaster prediction, management, and relief Ecosystems and natural resources Hybrid physical models Meta- and transfer learning Unsupervised and semi-supervised learning
Areas of Experience:
Classification, regression, and supervised learning Computer vision and remote sensing Ecosystems and natural resources Meta- and transfer learning Time-series analysis Unsupervised and semi-supervised learning
Seeking:
Networking Research collaborations
Offering:
Academic positions Mentorship Paid consulting Pro-bono consulting
2021-07-26

Marcus Voss
TU Berlin, Birds on Mars
At the Distributed Artificial Intelligence Laboratory (DAI-Lab), I have coordinated and worked on several research projects investigating how digitization and AI can support the energy transition. Within those projects, I have been modeling, forecasting, and optimizing different demand-side processes such as electric vehicles, smart building- and smart home loads, and renewable generation. I have coordinated the research group Smart Energy Systems, where I was responsible for aligning the DAI research for solutions for the energy system. I have co-supervised several Seminar, Bachelor and Master theses and project-based courses, mostly in applied machine learning for energy data, hoping to inspire more students to work in the field. In my doctoral research at TU Berlin, I work on analyzing low voltage-level smart meter data using non-Euclidean distance measures and neural networks with applications in load forecasting and load profile clustering.
Areas of Interest:
Buildings and cities Generative modeling Power and energy Time-series analysis
Areas of Experience:
Power and energy Time-series analysis
Seeking:
Research collaborations
Offering:
Mentorship Networking Research collaborations
2021-07-26

Jan Drgona
Pacific Northwest National Laboratory
I am a data scientist in the Physics and Computational Sciences Division (PCSD) at Pacific Northwest National Laboratory. My current research interests fall in the intersection of model-based optimal control, constrained optimization, and machine learning facilitated by differentiable programming.
Areas of Interest:
Buildings and cities Hybrid physical models Industry Power and energy Reinforcement learning and control Time-series analysis
Areas of Experience:
Buildings and cities Hybrid physical models Reinforcement learning and control
Seeking:
Networking Research collaborations
Offering:
Employment opportunities Mentorship Research collaborations
2021-07-26

Negin Katal
Max Planck Institute for Biogeochemistry
currently, I'm a Ph.D. student at MPI for Biogeochemistry in Jena. I'm researching applying ML for phenological modeling using citizen science.
Areas of Interest:
Classification, regression, and supervised learning Climate and Earth science Disaster prediction, management, and relief Ecosystems and natural resources Hybrid physical models Interpretable ML Time-series analysis
Areas of Experience:
Classification, regression, and supervised learning Climate and Earth science Disaster prediction, management, and relief Ecosystems and natural resources
Seeking:
Mentorship Networking Research collaborations
2021-07-26

Sebastian Gerard
KTH Stockholm
PhD student working on self-supervised learning for satellite images. Planning to work on wildfire predictions.
Areas of Interest:
Disaster prediction, management, and relief Forestry and other land use
Areas of Experience:
Computer vision and remote sensing Unsupervised and semi-supervised learning
Seeking:
Networking Research collaborations
Offering:
Networking Research collaborations
2021-07-26

Rendani Mbuvha
University of Witwatersrand
I am a lecturer in the School of Statistics and Actuarial Science at the University of the Witwatersrand. I completed a PhD in Artificial Intelligence at the University of Johannesburg focusing on probabilistic Machine Learning, an MSc in Computer Science and Engineering from KTH, Royal Institute of Technology in Sweden and a BSc Honours in Actuarial Science at the University of Cape Town.
Areas of Interest:
Causal and Bayesian methods Climate finance Data mining Disaster prediction, management, and relief
Areas of Experience:
Causal and Bayesian methods Classification, regression, and supervised learning Data mining
Seeking:
Funding Research collaborations
2021-07-25
Nishan Srishankar
I graduated with a Masters degree in Robotics engineering at WPI and have worked on decision-making for adversarial Multi-robot swarm systems (thesis), self-supervised learning of satellite images (NASA-SETI institute), explainable AI using graphs for multi-agent systems (Honda Research Institute), autonomous driving, and action recognition using smartphone sensors in the wild (DARPA).
Areas of Interest:
Classification, regression, and supervised learning Climate and Earth science Computer vision and remote sensing Generative modeling Hybrid physical models Interpretable ML Meta- and transfer learning Policy Reinforcement learning and control Time-series analysis Uncertainty quantification and robustness Unsupervised and semi-supervised learning
Seeking:
Academic positions Employment opportunities Networking Research collaborations
2021-07-24
Vivek Ramavajjala
DeepMind
I'm a Research Engineering Lead at DeepMind, working on applied research projects, and deploying ML in the real world.
Areas of Interest:
Behavioral and social science Climate and Earth science Climate justice Disaster prediction, management, and relief Policy
Areas of Experience:
Classification, regression, and supervised learning Data mining Reinforcement learning and control Time-series analysis
Seeking:
Mentorship Networking Research collaborations
2021-07-24

Thomas Soumarmon
Continental / DEEL.ai
Data Scientist willing to use my skills to tackle climate change. Currently on sabbatical year to find the best way to do it.
Areas of Interest:
Causal and Bayesian methods Climate and Earth science Climate justice Computer vision and remote sensing Disaster prediction, management, and relief Ecosystems and natural resources Forestry and other land use Generative modeling Uncertainty quantification and robustness Unsupervised and semi-supervised learning
Areas of Experience:
Causal and Bayesian methods Classification, regression, and supervised learning Computer vision and remote sensing Generative modeling Transportation Uncertainty quantification and robustness Unsupervised and semi-supervised learning

Industrial experience on deep learning, CV, SSL Research experience on OOD, generative models, bayesian "Kaggle" experience on remote sensing

Seeking:
Academic positions Employment opportunities Funding Mentorship Networking Research collaborations Startup co-founder
Offering:
Mentorship Networking Paid consulting Pro-bono consulting Research collaborations Startup co-founder
2021-07-24

Ramit Debnath
University of Cambridge
Ramit Debnath is a computational social scientist. His research focuses on energy and climate justice in the built environment using tools from data science. He uses machine learning and AI to inform sustainability and policy decisions for climate repair. He is currently a Laudes Foundation Research Associate and a Gates-Cambridge Scholar at the Centre for Natural Material Innovation and Energy Policy Research Group at the University of Cambridge. Ramit is a visiting researcher at the International Energy Agency (IEA)’s Energy Efficiency Division, working on the social dimension of digitalisation. He has a background in electrical engineering and a PhD in Energy Policy from Cambridge.
Areas of Interest:
Behavioral and social science Buildings and cities Classification, regression, and supervised learning Climate justice Natural language processing Policy Power and energy Transportation
Areas of Experience:
Behavioral and social science Buildings and cities Classification, regression, and supervised learning Climate justice Natural language processing Policy Power and energy Societal adaptation
Seeking:
Academic positions Employment opportunities Funding Mentorship Networking Paid consulting Research collaborations Startup co-founder
Offering:
Mentorship Networking Paid consulting Research collaborations
2021-07-24

Eirini Malliaraki
National Endowment for Science, Technology and the Arts (Nesta)
I am a design engineer at the Centre for Collective Intelligence Design at Nesta. Previously, I have led project development on environmental data science and AI for climate action at the Alan Turing Institute, the UK's National Centre for AI and Data Science. I have also worked as a researcher at Imperial College and Microsoft Research. I have a joint MA and MSc in Innovation Design Engineering from Imperial College London and the Royal College of Art.
Areas of Interest:
Active learning Behavioral and social science Buildings and cities Climate and Earth science Ecosystems and natural resources Natural language processing Policy Power and energy Societal adaptation Unsupervised and semi-supervised learning
Areas of Experience:
Climate and Earth science Climate finance Ecosystems and natural resources Policy Power and energy
Seeking:
Mentorship Networking Research collaborations
Offering:
Mentorship Pro-bono consulting Research collaborations
2021-07-24

Gang Huang
Zhejiang Lab
I am a Research Fellow at Zhejiang Lab. I completed the doctoral training at Zhejiang University and Argonne National Laboratory. My research interests lie at the intersection of electrical engineering, operations research, and computer science. A common thread in my research is in designing reliable and computationally efficient algorithms for mission-critical tasks.
Areas of Interest:
Classification, regression, and supervised learning Data mining Disaster prediction, management, and relief Hybrid physical models Policy Power and energy Reinforcement learning and control Transportation
Seeking:
Research collaborations
Offering:
Employment opportunities Research collaborations
2021-07-23

Aditya L. Ramadona
Department of Health Behaviour, Environment, and Social Medicine - Universitas Gadjah Mada
Areas of Interest:
Behavioral and social science Data mining
Areas of Experience:
Behavioral and social science Data mining
Seeking:
Networking Research collaborations
Offering:
Pro-bono consulting
2021-07-23

Levente Klein
IBM Research
I'm a research scientist at IBM Research working at the intersection of big data, geospatial intelligence and machine learning.
Areas of Interest:
Climate and Earth science
Areas of Experience:
Ecosystems and natural resources
Seeking:
Networking
Offering:
Research collaborations
2021-07-23
Jacob Bieker
Open Climate Fix
Machine Learning Researcher focusing on using multi-modal data to predict solar power output. Previously at NASA, Google, and Scale AI doing ML for geospatial, commerical, and self-driving vehicle projects. Masters in Astrophyiscs, previous research on applying ML to large-scale sky surveys, nanosecond astronomical phenomena, and other physics problems.
Areas of Interest:
Active learning Classification, regression, and supervised learning Computer vision and remote sensing Data mining Interpretable ML Time-series analysis Unsupervised and semi-supervised learning
Areas of Experience:
Active learning Classification, regression, and supervised learning Climate and Earth science Computer vision and remote sensing Data mining Time-series analysis

I've worked at NASA on using ML onboard Earth observation satellites, previously at Scale AI doing sensor fusion of lidar+rgb cameras for self-driving vehicle data and assisting human-in-the-loop labelling. Currently using satellite imagery to predict future PV yield.

Seeking:
Networking Pro-bono consulting Research collaborations
Offering:
Networking Research collaborations
2021-07-23

Akansha Singh Bansal
UMass Amherst
I am a soon-to-graduate Ph.D. student at UMass Amherst broadly interested in applying AI, Explainable AI (XAI) methods on satellite data to solve problems related to social good, sustainability, and climate change. My doctoral thesis is on data-driven approaches for control, modeling and, forecasting for solar-powered residences.
Areas of Interest:
Climate and Earth science Hybrid physical models Power and energy Unsupervised and semi-supervised learning
Areas of Experience:
Computer vision and remote sensing Power and energy Unsupervised and semi-supervised learning
Seeking:
Employment opportunities Research collaborations
2021-07-23

Ding Ning
University of Canterbury
I am a PhD student in computational and applied mathematics at the University of Canterbury. I am interested in machine learning for spatiotemporal anomaly forecasting.
Areas of Interest:
Classification, regression, and supervised learning Climate and Earth science Computer vision and remote sensing Meta- and transfer learning Unsupervised and semi-supervised learning
Areas of Experience:
Classification, regression, and supervised learning Computer vision and remote sensing Meta- and transfer learning
Seeking:
Employment opportunities Networking Research collaborations
Offering:
Networking Research collaborations
2021-07-23

Patrick Emami
University of Florida
I'm a PhD candidate at the University of Florida researching multi-object representation learning, reinforcement learning, and energy-efficient traffic intersection control.
Areas of Interest:
Buildings and cities Climate justice Transportation
Areas of Experience:
Generative modeling Reinforcement learning and control
Seeking:
Employment opportunities Research collaborations
Offering:
Networking Research collaborations
2021-07-23

Alex Kell
Imperial College London
Alex is a Research Associate who specialises in long term energy scenarios. Alex has expertise in agent based modelling and machine learning applied to energy markets around the world.
Areas of Interest:
Behavioral and social science Climate finance Policy Power and energy Reinforcement learning and control Time-series analysis Unsupervised and semi-supervised learning
Areas of Experience:
Behavioral and social science Policy Power and energy Reinforcement learning and control Time-series analysis
Seeking:
Networking Paid consulting Research collaborations
Offering:
Networking Research collaborations
2021-07-23

Florin Gogianu
Bitdefender
I am a PhD student at the Technical University of Cluj-Napoca and researcher at Bitdefender working on Deep Reinforcement Learning.
Areas of Interest:
Climate and Earth science Power and energy Reinforcement learning and control Transportation
Areas of Experience:
Active learning Reinforcement learning and control Unsupervised and semi-supervised learning
Seeking:
Research collaborations
Offering:
Research collaborations
2021-07-23

Nathan Lambert
UC Berkeley
Nathan Lambert is a PhD Candidate at the University of California, Berkeley working at the intersection of machine learning and robotics. He is a member of the Department of Electrical Engineering and Computer Sciences, advised by Professor Kristofer Pister in the Berkeley Autonomous Microsystems Lab. Nathan has worked extensively with Roberto Calandra at Facebook AI Research and is joining DeepMind Robotics remotely for the summer of 2021. During his Ph.D., he was awarded the UC Berkeley EECS Demetri Angelakos Memorial Achievement Award for Altruism.
Areas of Interest:
Climate and Earth science Power and energy Reinforcement learning and control
Areas of Experience:
Reinforcement learning and control
Seeking:
Research collaborations
Offering:
Pro-bono consulting
2021-07-23

Santosh Sharma
University of Central Florida
I am a PhD student at UCF. I am interested in applying mathematical optimization (decentralized and distributed algorithms) in multi-energy systems.
Areas of Interest:
Carbon capture and sequestration Disaster prediction, management, and relief Power and energy Transportation
Areas of Experience:
Disaster prediction, management, and relief Power and energy
Seeking:
Employment opportunities Funding Networking Research collaborations
2021-07-23

Sasha Luccioni
Mila + Université de Montréal
I am currently a Postdoctoral Researcher at the Mila Institute supervised by Yoshua Bengio, and a Computational Social Scientist at the UN Global Pulse.
Areas of Interest:
Behavioral and social science Climate finance Interpretable ML Natural language processing Societal adaptation
Areas of Experience:
Behavioral and social science Climate finance Natural language processing

My goal in research is to contribute towards understanding the data and techniques used for developing Machine Learning approaches, as well as to contribute to the growing field of ‘AI for Good’, applying AI to high-impact societal problems like climate change, health, education, and humanitarian response. Most recently, I have been working on analyzing the data used for training large language models, as well as quantifying the carbon footprint of AI algorithms

Seeking:
Employment opportunities
Offering:
Mentorship Paid consulting Research collaborations
2021-07-23

Redouane Lguensat
CEA Saclay / Sorbonne Univ.
Postdoctoral researcher at LSCE-IPSL (CEA Saclay), France. ML for oceanography and climate modeling
Areas of Interest:
Climate and Earth science
Areas of Experience:
Classification, regression, and supervised learning Computer vision and remote sensing Hybrid physical models Interpretable ML Time-series analysis Uncertainty quantification and robustness Unsupervised and semi-supervised learning

I have a background in ML and been working on ML for oceanography since my PhD (2014-2017). Recently I started working on ML for climate modeling, you can learn more by visiting my personal website.

Seeking:
Funding Networking Research collaborations
Offering:
Mentorship Research collaborations
2021-07-23

Merce Casas-Prat
Environment and Climate Change Canada
I am a research scientist studying marine climate extremes, with focus on ocean waves, and their impacts on coastal communities and offshore activities.
Areas of Interest:
Classification, regression, and supervised learning Climate and Earth science Computer vision and remote sensing Data mining Time-series analysis Uncertainty quantification and robustness
Areas of Experience:
Classification, regression, and supervised learning Climate and Earth science Data mining Time-series analysis
Seeking:
Research collaborations
2021-07-23

Julian de Hoog
University of Melbourne
Research scientist with research background in both academia and industry (IBM Research), across electrified transport, solar power forecasting, optimal energy storage operation, and more recently deep learning.
Areas of Interest:
Computer vision and remote sensing Power and energy Time-series analysis
Areas of Experience:
Industry Power and energy Time-series analysis Transportation
Seeking:
Research collaborations
Offering:
Research collaborations
2021-07-22

David Dao
ETH Zurich
I'm a Ph.D. student at ETH Zurich building AI and Data Systems for Sustainable Development. I'm leading the Climate + AI initiative at DS3Lab, mapping the ethical use of AI, and directing the Kara research project with Stanford and UC Berkeley. I'm also the founder of GainForest, a non-profit grantee of Microsoft’s AI for Earth program, which leverages decentralized technology to prevent deforestation. Previously, I was an engineer in Silicon Valley and a research fellow at Berkeley AI Research (BAIR), Stanford University and Broad Institute of MIT and Harvard. I'm a Global Shaper at World Economic Forum, a Core Member of Climate Change AI, a Climate Leader at Climate Reality Project and organized conferences with thousands of attendees in Germany, Silicon Valley, and at Harvard.
Areas of Interest:
Climate finance Climate justice Computer vision and remote sensing Ecosystems and natural resources Forestry and other land use Interpretable ML Policy
Areas of Experience:
Climate finance Computer vision and remote sensing Ecosystems and natural resources Forestry and other land use Interpretable ML
2021-07-09

David Rolnick
McGill University & Mila Quebec AI Institute
I'm an Assistant Professor in Computer Science and Canada CIFAR AI Chair at McGill University and Mila - Quebec AI Institute, a co-founder and Chair of CCAI, and Scientific Co-Director of Sustainability in the Digital Age. My group works on machine learning innovations driven by problems relevant to climate change and biodiversity, as well as mathematical understanding of deep learning algorithms.
Areas of Experience:
Classification, regression, and supervised learning Computer vision and remote sensing Ecosystems and natural resources
Seeking:
Research collaborations
Offering:
Academic positions Research collaborations
2021-07-09
Felipe Oviedo
ML research at MSFT AI for Good
Areas of Interest:
Active learning Classification, regression, and supervised learning Generative modeling Hybrid physical models Recommender systems Unsupervised and semi-supervised learning
Areas of Experience:
Climate and Earth science Forestry and other land use Generative modeling Industry
2021-07-09

Evan David Sherwin
Stanford University, Energy Resources Engineering
Founding member of CCAI, Chair of Programs Committee. Studying decarbonizing hydrocarbons, particularly #methane.
Areas of Interest:
Behavioral and social science Carbon capture and sequestration Classification, regression, and supervised learning Policy Power and energy Time-series analysis Uncertainty quantification and robustness
Areas of Experience:
Behavioral and social science Carbon capture and sequestration Classification, regression, and supervised learning Policy Power and energy Time-series analysis Uncertainty quantification and robustness
2021-07-09

Peetak Mitra
Palo Alto Research Center
Scientist at Palo Alto Research Center working at the intersection of machine learning and computational physics.
Areas of Interest:
Active learning Classification, regression, and supervised learning Climate and Earth science Generative modeling Hybrid physical models Interpretable ML Power and energy Time-series analysis Transportation
Areas of Experience:
Climate and Earth science Hybrid physical models Time-series analysis
2021-07-03

Konstantin Klemmer
University of Warwick, NYU
PhD student in geospatial machine learning, core team member at CCAI
Areas of Interest:
Climate and Earth science Disaster prediction, management, and relief Hybrid physical models Unsupervised and semi-supervised learning
Areas of Experience:
Buildings and cities Classification, regression, and supervised learning Computer vision and remote sensing Generative modeling Transportation

Geospatial machine learning, spatio-temporal machine learning, GeoAI, Urban informatics

Seeking:
Academic positions Employment opportunities
Offering:
Mentorship Networking Research collaborations
2021-06-07

Kasia Tokarska
ETH Zurich (former postdoc)
I am a climate scientist exploring carbon-climate interactions and how they change under anthropogenic influence. I am also interested in providing more robust projections of the Earth's future climate, using climate models and a variety of data analysis tools. I am also very interested in interpretable and physically-informed machine learning applications to climate data analysis, and different ways to quantify the uncertainty.
Areas of Interest:
Hybrid physical models Interpretable ML Uncertainty quantification and robustness
Areas of Experience:
Climate and Earth science
Seeking:
Networking
Offering:
Mentorship Networking Research collaborations
2021-06-05

Priya Donti
Carnegie Mellon University
I'm a Ph.D. student in Computer Science & Public Policy at Carnegie Mellon University, and co-founder and chair of Climate Change AI. My work focuses on machine learning for forecasting, optimization, and control in high-renewables power grids, with a specific focus on incorporating relevant physics and hard constraints into deep learning models.
Areas of Interest:
Buildings and cities Climate justice Computer vision and remote sensing Hybrid physical models Industry Policy Power and energy Reinforcement learning and control Transportation Uncertainty quantification and robustness
Areas of Experience:
Hybrid physical models Policy Power and energy Reinforcement learning and control

I'm also interested in ways to better foster the deployment and scaling of useful climate-relevant work.

Seeking:
Research collaborations
Offering:
Mentorship Networking Research collaborations
2021-05-24

Hari Prasanna Das
UC Berkeley
PhD Candidate at UC Berkeley working on Deep Generative Modeling and its applications in Smart Buildings.
Areas of Interest:
Buildings and cities
Areas of Experience:
Buildings and cities
Seeking:
Research collaborations
Offering:
Research collaborations
2021-05-13

Lynn Kaack
Hertie School
I'm an Assistant Professor at the Hertie School in Berlin, and also one of the three co-founders and chairs of CCAI. I work in the field of public policy, with a focus on climate change mitigation and ML.
Areas of Interest:
Natural language processing
Areas of Experience:
Buildings and cities Classification, regression, and supervised learning Policy Power and energy Transportation
Offering:
Mentorship Research collaborations