Kelsey Doerksen

Kelsey Doerksen

Postdoctoral Researcher

Curriculum Vitae

🎓 Education

  • DPhil Computer Science (2021 - 2025), University of Oxford, United Kingdom
    Advised by Professor Yarin Gal. Member of OATML and Autonomous Intelligent Machines and Systems CDT
  • MESc Electrical & Computer Engineering (2019 - 2020), University of Western Ontario, Canada
    Member of the Planetary Science and Exploration Collaborative Program (CPSX)
  • BEng Aerospace Engineering: Space Systems Design (2013 - 2017), Carleton University, Canada

đŸ–„ïž Highlighted Technical Skills

  • 5+ years of experience leading Machine Learning projects from multi-modal dataset generation, feature engineering, model building and performance analysis using PyTorch and Tensorflow.
  • Skilled in developing automation and data analysis tools in Python, with industry applications in EO satellite constellation operations, in addition to large-scale geospatial data analysis in R and JavaScript.
  • Applied experience deploying Machine Learning models in an operational context, with work being actively used by the Nepal government to forecast landslide likelihood as of May 2024.

🔬 Research Experience

  • Research Lead, Agricultural Impact Risk (Oct 2025 – Present), African Climate and Development Initiative, Climate Risk Lab, University of Cape Town
    â–ș Leading the agricultural impacts pillar of the Climate Risk Lab, developing models to predict impacts on food systems from climate change globally and with a focus on Africa.
  • Postdoctoral Researcher (Oct 2025 – Present), Arizona State University, School of Computer and Augmented Intelligence
    â–ș Research focuses on fundamental and applied Machine Learning utilizing Earth Observation and Remote Sensing data products. Work concentrated on geofoundational modelling and biodiversity mapping under the supervision of Dr. Hannah Kerner.
  • Visiting Researcher (Feb – Mar 2025), African Climate and Development Initiative – University of Cape Town
    â–ș Supported the development of the R-based data processing pipeline for large-climate datasets with the application of generating decadal-scale biodiversity exposure analysis.
  • Visiting Researcher (Feb – May 2024), European Space Agency Phi-Lab
    â–ș Developed a data-driven ML pipeline for automatic school mapping and internet connectivity prediction using Earth Observation data sources to support UNICEF’s Giga Initiative.
  • Data Science PhD Fellow (Oct 2023 – June 2024), UNICEF
    â–ș PhD Data Science intern for the Giga initiative. Work accepted at ICLR 2024 MLRS Workshop.
  • Research Affiliate (Sept 2022 – 2025), NASA Jet Propulsion Laboratory, Machine Learning and Instrument Autonomy Group
    â–ș Developed airPy; open-sourced by NASA. airPy is used by the Science Understanding from Data Science group to integrate high-resolution satellite imagery into Machine Learning frameworks for air quality studies.
  • Visiting Researcher (Oct – Dec 2019), NASA Jet Propulsion Laboratory
    â–ș Focused on feature engineering, robotic assembly, data collection, and machine learning for planetary rover applications for future rover missions.
  • Visiting Researcher (May 2018 – Sept 2021), l’Observatoire de Paris
    â–ș Investigated the response of Earth’s atmosphere to solar flares, published in Space Weather Journal.

🍎 Teaching Experience

  • Workshop Lead, AI for Science (Sept 2024 – May 2025), University of Oxford
    â–ș Designed, curated, and taught the curriculum of the Oxford Autonomous Intelligent Machines and Systems Doctoral training workshop, “AI for Science” for doctoral students across STEM departments.
  • Tutorial Lead, Data Visualization (Jan – May 2023), University of Oxford
    â–ș Responsible for teaching the techniques and algorithms for creating effective visualizations based on principles from graphic design, visual art, perceptual psychology, and cognitive science using JavaScript.
  • Teacher and Organizer (Jan – Aug 2019), Natural Space Risks Summer School, l’Observatoire de Paris, France
    â–ș Responsible for developing and teaching curriculum on attitude dynamics and orbital mechanics, hosting students from across the globe.
  • Certificate in University Teaching and Learning (2018 – 2019), University of Western Ontario
    â–ș Completed a graduate-level teaching certification program to prepare for future faculty roles.
  • Graduate Teaching Assistant (Sept 2018 – May 2019), University of Western Ontario
    â–ș Introductory Design & Innovation Studio (1st year) and Electrical & Computer Engineering CAPSTONE project (4th year).
  • Graduate Teaching Assistant (Sept – Dec 2017), Carleton University
    â–ș Circuits & Signals: 2nd year Electrical Engineering course.

đŸ›°ïž Industry Experience

  • Data Scientist, Climate and Environment Unit (Sept 2024 – May 2025), UNICEF
    â–ș Supporting the development of the data architecture pipeline of UNICEF's Children’s Climate Risk Index, building infrastructure for processing various climate and environmental datasets.
  • Space Systems Engineer, Satellite Operations (Jan 2020 – Apr 2022), Planet
    â–ș Developed Python tools for autonomous satellite operations, led the successful autonomous commissioning of 48 satellites in 30 days — a company record.

đŸ§Ș STEM Outreach and Project Management Experience

  • Newfoundland & Labrador Outreach Coordinator (May – Aug 2017), ACTUA / SuperNOVA at Dalhousie University
    â–ș Delivered STEM education programs to remote Innu and Inuit communities.
  • Program Coordinator (Sept 2015 – 2016), Virtual Ventures, Carleton University
    â–ș Oversaw administration, logistics, budget, registration, and curriculum delivery for summer camps and workshops serving 1200+ youth.

📘 Publications

  • S. Hickman, M. Kelp, P. Griffiths, K. Doerksen, et al. “Applications of Machine Learning and Artificial Intelligence in Tropospheric Ozone Research”. TOAR-II Community Special Issue. 2025. Highlight paper.
  • Pre-print: K. Doerksen, C. Fibaek, R. Schneider, D. Kim, I. Tingzon. “Predicting Internet Connectivity in Schools”.
  • K. Doerksen, S. Li. “AI-Driven Sub-seasonal Landslide Forecasting in Nepal for Disaster Preparedness”. ICLR CCAI Workshop 2025.
  • K. Doerksen et al. “Uncertainty Quantification for Surface Ozone Emulators using Deep Learning”. NeurIPS ML and the Physical Sciences Workshop 2024.
  • K. Doerksen*, I. Tingzon*, D. Kim. “AI-powered school mapping and connectivity status prediction using Earth Observation.” ICLR 2024 ML for Remote Sensing Workshop.
  • K. Doerksen et al. “Leveraging Deep Learning for Physical Model Bias of Global Air Quality Estimates”. NeurIPS ML and Physical Sciences Workshop 2023.
  • K. Doerksen et al. “Precipitation-Triggered Landslide Prediction in Nepal using Machine Learning and Deep Learning”. IEEE IGARSS 2023.
  • C. Briand, K. Doerksen, F. Deleflie. “Solar EUV-Enhancement and Thermospheric Disturbances”. Space Weather Journal, Vol. 9, Issue 12.
  • P. Bernal, K. Doerksen, C. Yap. “Machine Learning for Early Satellite Anomaly Detection”. SmallSat 2021.
  • J. Ahumada, K. Doerksen, S. Zeller. “Automated fleet commissioning workflows at Planet”. SmallSat 2021. (Shared first authorship)
  • K. Doerksen*, K. Fischer*. “Autonomous Systems Validation (SysVal) environment for advancing Mission Operations”. SmallSat 2021.

💗 Volunteering

  • Ethics Reviewer, NeurIPS (2025)
  • Workshop Reviewer, ICML TerraBytes Earth Observation Workshop (2025)
  • Subject Matter Expert, AI Risk, British Red Cross (2025)
  • President, Oxford Womxn in CS (2023–2024)
  • Equity, Diversity & Inclusion Fellow, University of Oxford MPLS Division (2023–2024)
  • Mentor, Zenith Canada Pathways Foundation (2020–Present) — zenithpathways.ca
  • Science & Technology Committee, American Meteorological Society (2019–2021)
  • Congress Manager, Space Generation Congress, SGAC (2019–2021) — spacegeneration.org/sgc2021

đŸ—Łïž Invited Talks

  • Upcoming: Panelist, Climate Change AI, NeurIPS (Dec 2025)
  • ITU AI for Good Webinar: "AI for humanity: Using earth observation for solving global challenges" (Nov 2025)
  • University of Oxford Keble College Alumni Event: “Using Space to Help Life on Earth” (Oct 2025)
  • Satellite Application Catapult: “Applied Machine Learning: Geospatial AI for Earth’s Systems Science” (Oct 2025)
  • Session Chair, Adaptation Futures, Adaptation for Children’s Education, Physical Activity, Health and Well-being (Oct 2025)
  • Space and Satellites Professional International Podcast Guest, Movers in Our Orbit, ""Doing Impactful Work for Earth from Space" (Oct 2025)
  • "Using Space to Help Life on Earth: Geospatial AI for Humanity" University of Oxford Autonomous Intelligent Machines and Systems Meeting, (Sept 2025)
  • Keynote: "AI for Humanity: From Outer Space to at home on Earth" University of Oxford EnSpire. (Aug 2025)
  • "Creating your dream job - Using Space to help life on Earth with Artificial Intelligence" University of Oxford Autonomous Intelligent Machines and System High School Outreach day (May 2025)
  • TEDx Queen’s U: “AI won’t save us, but it can help us” Largest TEDx event in Canada. (Jan 2025)
  • Keynote: “Ethically Engaging with AI”, Swedish University of Agricultural Sciences Educational Conference (Aug 2024)
  • Vice Chancellor’s International Women’s Day Panelist, “Can AI be a Force for Inclusion?” (Mar 2024)
  • “AI for Scientific Understanding”. Invited Oral talk for Caltech’s Yuk Lunch Seminar. Caltech, (Aug 2023)
  • “AI in Space: Challenges and Opportunities”. Invited Panelist. Canadian Aeronautics and Space Institute Conference (Nov 2022)
  • Keynote Panelist: “AI4Space: Perspectives from the Next Generation” International Astronautical Congress, (Sept 2022)
  • Panelist, Women in Machine Learning, ICML (Jul 2022)
  • SOAR Student Leadership Conference, Carleton (Jan 2022)
  • Class of 2021 Mechanical and Aerospace Engineering Convocation Speaker, Carleton University, (June 2021)
  • American Meteorological Society Clear Skys Podcast Guest (June 2021)
  • Canadian Aeronautics and Space Institute (CASI) Invited Talk, “A Journey to a Career in Space” (June 2021)
  • Girl Geek webinar series: "Inbox Full: Handling Big Data in Space" (Sept 2020)

🏆 Selected Awards

  • Museum of Science – Science Communication Fellowship (2025)
    â–ș $20,000 fellowship awarded to support national science communication strategy.
  • Portraits of Keble III, University of Oxford (2025)
    â–ș Featured for outstanding research & leadership — View Portrait
  • Grace Hopper Scholarship Winner (2023)
    â–ș Full scholarship to attend Grace Hopper Conference for EDI contributions.
  • SSPI 20 under 35 Promise Award (2021)
    â–ș Top 3 under-35 professionals in space industry.
  • Global Grants Award, Space Generation Advisory Council (2020)
    â–ș SGAC’s most competitive scholarship.
  • Winner, Caltech Space Challenge (2019)
    â–ș Top 1 of 32 selected from 600+ applicants worldwide. Best proposal winner.
  • Outstanding Presentation, Western ECE Symposium (2019)
  • 3MT Finalist, University of Western Ontario (2019)

Last updated: November 2025