Publications

List of peer-reviewed publications, pre-prints, open-access ML-generated datasets, technical presentations, conference abstracts and posters.

Peer Reviewed Publications

  1. S. Chakraborty, O. Alexander, N. Kittner, Z. Wang, A Global Stocktake on Electricity Access and Gaps from NASA Black Marble Nighttime Lights, 2025, AGU Earth’s Future, 13, e2024EF005916. https://doi.org/10.1029/2024EF005916
  2. S. Chakraborty, “Data-Centric Safety and Ethical Measures for Data and AI Governance”, AAAI Workshop on Datasets and Evaluators of AI Safety, 2025, https://openreview.net/forum?id=iCcbtNIFuj
  3. S. Chakraborty, E.C. Stokes, O. Alexander, “Global urban activity changes from COVID-19 physical distancing restrictions”, Scientific Data, 12 (1), 98, 2025, https://www.nature.com/articles/s41597-025-04398-x
  4. S. Chakraborty, E.C. Stokes, “Adaptive modeling of satellite-derived nighttime lights time-series for tracking urban change processes using machine learning”, Remote Sensing of Environment, 298: 113818, 2023, https://doi.org/10.1016/j.rse.2023.113818
  5. S. Chakraborty, T. Oda, V.L. Kalb, Z. Wang, M.O. Rom ́an, “Potentially Underestimated Gas Flaring Activities – A New Approach to Detect Combustion Using Machine Learning and NASA’s Black Marble Product Suite”,
    Environmental Research Letters, 2023, https://doi.org/10.1088/1748-9326/acb6a7
  6. D. Hills, J. Damerow, B. Ahmmed, N. Catolico, S. Chakraborty, C. Coward, R. Crystal-Ornelas, W. Duncan, L. Goparaju, C. Lin, Z. Liu, M. Mudunuru, Y. Rao, R. Rovetto, Z. Sun, B. Whitehead, L. Wyborn, T. Yao, “Earth and Space Science Informatics Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science”, Earth and Space Science, 2022, https://doi.org/10.1029/2021EA002108.
  7. T. Oda, M.O. Román, Z. Wang, E.C. Stokes, Q. Sun, R.M. Shrestha, S. Feng, T. Lauvaux, R. Bun, S. Maksyutov and S. Chakraborty, 2021. US Cities in the Dark: Mapping Man‐Made Carbon Dioxide Emissions Over the Contiguous US Using NASA’s Black Marble Nighttime Lights Product. Urban Remote Sensing: Monitoring, Synthesis, and Modeling in the Urban Environment, pp.337-367.
  8. K. Wagstaff, G. Doran, A. Davies, S. Anwar, S. Chakraborty, M. Cameron, I. Daubar, C. Phillips, “Enabling Onboard Detection of Events of Scientific Interest for the Europa Clipper Spacecraft”, Proceedings of the Twenty- Fifth ACM SIGKDD Conference On Knowledge Discovery And Data Mining, 2019.
  9. S. Chakraborty, S. Das, A. Banerjee, S.K.S. Gupta, P. R. Christensen, “Expert Guided Rule Based Prioritization of Scientifically Relevant Images for Downlinking over Limited Bandwidth from Planetary Orbiters”, Proceedings of the Thirty-First Annual Conference on Innovative Applications of Artificial Intelligence, 2019.
  10. S. Chakraborty, A. Banerjee, S. Gupta, P. R. Christensen, A. Papandreou-Suppappola, “Time-Varying Modeling of Land Cover Change Dynamics Due to Forest Fires”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 6, pp. 1769–1776, 2018.
  11. S. Chakraborty, A. Banerjee, S. Gupta, P. Christensen, “Region of Interest Aware Compressive Sensing of THEMIS Images and Its Reconstruction Quality”, IEEE Aerospace Conference, 2018.
  12. S. Chakraborty, A. Banerjee, S. Gupta, A. Papandreou-Suppappola, P. Christensen, “Estimation of Dynamic Parameters of MODIS NDVI Time Series Nonlinear Model Using Particle Filtering”, IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 1091–1094, 2017.
  13. S. Chakraborty, S. Das, P. Chatterjee, Prediction of domain boundaries in protein sequences using predicted secondary structure and physicochemical properties of amino acids, IEEE International Conference on Circuit, Power and Computing Technologies, March 2014

Papers in Review (Preprints):

1. A A Asanjan, …., S. Chakraborty, …, D. Bell, GAIA: A Foundation Model for Operational Atmospheric Dynamics, 2025, https://arxiv.org/abs/2505.18179

2. D. Szwarcman, S. Roy, P. Fraccaro,…, S. Chakraborty,…, J. B. Moreno, Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications, 2024, https://arxiv.org/abs/2412.02732

3. S. Chakraborty, Towards A Comprehensive Assessment of AI’s Environmental Impact, 2024, In Review, preprint: https://arxiv.org/pdf/2405.14004

Datasets Published:

  1. S. Chakraborty, O. Alexander, & Z. Wang (2024). Global Electricity Access Dataset from NASA Black Marble Nighttime Lights [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14582206
  2. S. Chakraborty, E.C. Stokes, O.A. Alexander, “Global Urban Activity Changes from COVID-19 Physical Distancing Restrictions Dataset: TRacking Anomalous COVID-19 induced changEs in NightTime Lights (TRACE-NTL)“, 2024, https://zenodo.org/records/11206064
  3. S.Chakraborty, NASA AWS Open Data on Nighttime fires and gas flaring from VIIRS using iterative machine learning labeling and detection, 2023:  https://registry.opendata.aws/black_marble_combustion
Selected Presentations

1.Towards Monitoring the Environmental Degradation Index of AI, Rethinking the Inevitability of AI Conference, Dec 2024.

2. Invited: Facilitating the Discoverability and Analysis of Rare Class Signals in Earth and Space Sciences Using Unsupervised Learning, Exoplanets in Our Backyard Workshop, Nov 2024.

3.Invited: Satellite-Derived Insights on Global Electricity Infrastructure with NASA Black Marble Nighttime Lights for Disaster Response and Assessing Energy Access Gaps, EIS Council/ Imperial College, Sep, 2024.

4. Invited: Nightlights-Based Assessment of Global Electricity Infrastructure and its Impact on Future Emissions to Meet the Growing Demand, MIT Center for Global Change Science, Joint Program on the Science and Policy of Global Change, Dec 2023.

5. Invited: Monitoring the Earth at Night with a Machine Learning Lens, NASA IMPACT/University of Alabama, Huntsville, Mar 2023 Seminar.

6. Invited: Monitoring the Earth at Night with a Machine Learning Lens, NASA Goddard Scientific Colloquium, February, 2023.

7. Benchmarking NASA’s Black Marble Product Suite for Near-Real Time Monitoring of Nighttime Combustion, AGU Fall Meeting, 2022.

8. Adaptive Modeling of Satellite-Derived Nighttime Lights for Monitoring Urban Change Processes Using Time-Series Forecasting, AGU Fall Meeting, 2022.

9. Invited: Feature Extraction from Visible Infrared Imaging Radiometer Suite (VIIRS) Observations for Monitoring the Earth at Night, International Virtual School on Application of Machine Learning and IoT in Remote Sensing, Chapnet- 2020, IEEE Geoscience and Remote Sensing Society, Kolkata Chapter, December 2020.

10. Latent Space Representations of VIIRS Multispectral Observations for Monitoring the Earth at Night, NASA GSFC Early Career Scientist Forum, November 2020.

11. Analysis of Multispectral Land Surface Reflectance Time-Series for Detecting and Classifying Land Cover Change, 2nd NOAA Workshop on Leveraging AI in Environmental Sciences, November 2020.

12. Extracting Features from VIIRS Observations for Monitoring the Earth at Night, NASA SED Director’s Seminar (Earth Science Division), November 2020.

13. Towards Data-Informed Climate Sciences – Leveraging Machine Learning Inferences of Satellite Observations, Workshop in Data Science in Climate and Climate Impact Research, Weather and Climate Risks Group, ETH Zurich, August 2020.

14. Time-Varying Semantic Representations of Planetary Observations for Discovering Novelties, AI for Earth Workshop, ICLR, April 2020.

15. Invited: Adaptive Representations of Multispectral Satellite Images for Change and Novelty Detection, Carnegie Institute for Science, October 2019.

16. Invited: Tracking Dynamic Changes in Land Surface Using Statistical Processing and Bayesian Modeling of Satellite Time- Series Data, Department of Earth and Environment, Boston University, October 2019.

17. Expert Guided Rule Based Prioritization of Scientifically Relevant Images for Downlinking over Limited Bandwidth from Planetary Orbiters, IAAI/AAAI, January 2019.

18. Spectral Anomaly Detection for Europa Clipper, Machine Learning and Instrument Autonomy Group, Jet Propulsion Laboratory, July 2018.

19. Region of Interest Aware Compressive Sensing of THEMIS Images and Its Reconstruction Quality, IEEE Aerospace Conference, March 2018.

20. Unsupervised Seismic Anomaly Detection, Los Alamos National Laboratory, August 2017.

21. Estimation of Dynamic Parameters of MODIS NDVI Time Series Nonlinear Model Using Particle Filtering, IEEE IGARSS, July 2017.

22. Multitemporal Analysis of Satellite Image Time-Series for Land Cover Change Detection, NASA JPL Climate Sciences Summer School, August 2016.

Conference Abstracts and Posters

1. S. Chakraborty, O. Alexander, B. Mujeci, N. Kittner, Z. Wang, V. Kalb, R. Shrestha, Continuous Planetary-Scale Urban Infrastructure Monitoring from NASA Black Marble Nighttime Lights, American Geophysical Union Fall Meeting, Dec 2024.

2. S. Chakraborty, Towards Discoverability and Cataloging of Rare Class Signals from Large Earth and Space Science Datasets Using Machine Learning, NASA SMD Software Workshop, May 2024.

3. S. Chakraborty, O. Alexander, Z. Wang, V. Kalb, R. Shrestha, Assessing Electricity Availability from Machine Learning Insights of NASA’s Black Marble Nighttime Lights, American Geophysical Union Fall Meeting, Dec 2023.

4. S. Chakraborty, R. Attie, T. Oda, Z. Wang, V. Kalb, R. Shrestha, Domain Adaptive Anomaly Detectors for Extracting and Identifying Rare Class Signals: A Case Study with NASA’s Black Marble Nighttime Lights and the Atmospheric Imaging Assembly Assembly Onboard the Solar Dynamics Observatory, American Geophysical Union Fall Meeting, Dec 2023.

5. S. Chakraborty, Machine Learning Insights on Electricity Access from Satellite-derived Nightlights, Energy Data Analytics Symposium: Accelerating Sustainability in the AI Era, Energy Data Analytics Symposium, Oct 2023.

6. S. Chakraborty, O. Alexander, Z. Wang, V. Kalb, R. Shrestha, Nightlight-Based Assessment of Electricity Infrastructure and Its Impact on Emissions in an Urbanizing Planet, MultiSector Dynamics Workshop, DOE Earth and Environmental System Modeling Program, Oct 2023.

7. S. Chakraborty, T. Oda, V.L. Kalb, Z. Wang, E.C. Stokes, R.M. Shrestha, Benchmarking NASA’s Black Marble Product Suite for Near-Real Time Monitoring of Nighttime Combustion, AGU Fall Meeting, 2022.

8. S. Chakraborty, E.C. Stokes, Adaptive Modeling of Satellite-Derived Nighttime Lights for Monitoring Urban Change Processes Using Time-Series Forecasting, AGU Fall Meeting, 2022.

9. R.M. Shrestha, E.C. Stokes, Z. Wang, V.L. Kalb, S. Chakraborty, A. Molthan, J.R. Bell, L.A. Schultz, Disaster Monitoring through NASA’s Black Marble Nighttime Lights Product Suite, AGU Fall Meeting, 2022.

10. S. Chakraborty, T. Oda, V.L. Kalb, Z. Wang, M.O. Román, Satellite-Derived Combustion Activity Estimation Using Machine Learning and NASA’s Black Marble Product Suite for Evaluation of Greenhouse Gas Emission Inventories, Metrology for Climate Action, 2022.

11. S. Chakraborty, Explaining Unsupervised Detections of Natural Hazards from Multispectral Satellite Image Time-Series, AI for Earth and Space Science, ICLR, 2022.

12. S. Chakraborty, T. Oda, V.L. Kalb, M.O. Román, Z. Wang, Towards Improved Monitoring of Combustion Emissions: An Enhanced Combustion Detection Approach Using Machine Learning and NASA’s Black Marble Nighttime Lights Product Suite, AGU Fall Meeting, 2021.

13. M. Ansdell, S. Chakraborty, M. Guhathakurta, M.M. Little, Growing Opportunities for Multiparty Collaborations in Artificial Intelligence and Machine Learning for Science Research, AGU Fall Meeting, 2021.

14. S. Chakraborty, Multispectral Analysis of Land Surface Reflectance Time-Series for Clustering Change Events, NASA Second AI and Data Science Workshop, February 2021.

15. S. Chakraborty, V.L. Kalb, M.O. Roman, Z. Wang, E.C. Stokes, R.M. Shrestha, I.L. Paynter, T. Oda, Modeling VIIRS Brightness Temperature for Improving Nighttime Cloud Detection, AGU Fall Meeting Abstract, December 2020.

16. E. C. Stokes, M. O. Roman, R.M. Shrestha, Z. Wang, V. L. Kalb, I. L. Paynter, S. Chakraborty, T. Oda, Battling COVID-19 from Space: Cross-Scale Changes in Urban Activity Captured by NASA’s Black Marble Product Suite, AGU Fall Meeting Abstract, December 2020.

17. M. O. Roman, E.C. Stokes, R.M. Shrestha, Z. Wang, V.L. Kalb, I.L. Paynter, S. Chakraborty, T. Oda Tracking Responses to the COVID-19 Pandemic using NASA’s Black Marble Product Suite, AGU Fall Meeting Abstract, December 2020.

18. S. Chakraborty, Analysis of Multispectral Land Surface Reflectance Time-Series for Detecting and Classifying Land Cover Change, 2nd NOAA Workshop on Leveraging AI in Environmental Sciences, November 2020.

19. S. Chakraborty, Towards Data-Informed Climate Sciences – Leveraging Machine Learning Inferences of Satellite Observations, Workshop in Data Science in Climate and Climate Impact Research, August 2020.

20. S. Chakraborty, Unsupervised Land Cover Change Detection and Interpretation from Multispectral Satellite Image Time-Series, Women In Machine Learning Workshop, ICML, 2020.

21. S. Chakraborty, Time-Varying Semantic Representations of Planetary Observations for Discovering Novelties, AI for Earth Workshop, ICLR, 2020.

22. S. Chakraborty, A. Papandreou-Suppappola, P.R. Christensen, Class Separability of Land Cover Change Events from Multispectral Satellite Image Time-Series, AGU Fall Meeting Abstract, December 2019.

23. K. L. Wagstaff, G. Doran, A. Davies, S. Anwar, S. Chakraborty, M. Cameron, J. Bapst, S. Chien, C. Cochrane, I. Daubar, S. Diniega, C. Phillips, S. Piqueux, Responsive Onboard Science for the Europa Clipper Mission, JPL Data Science Showcase, April 2019.

24. K. L. Wagstaff, D. L. Blaney, S. Chakraborty, S. A. Chien, A. G. Davies, S. Diniega, and G. Doran, Spectral Anomaly Detection for the Mapping Imaging Spectrometer for Europa (MISE), 50th Lunar and Planetary Science Conference, Abstract #1604, March 2019.

25. S. Chakraborty, A. Banerjee, S. K. S Gupta, P. R. Christensen, A. Papandreou-Suppappola, Multitemporal Analysis of Image Time-Series for Land Cover Change Detection and Unsupervised Classification of Change Event Using Spectral Analysis, AGU Fall Meeting Abstract, 2018.

26. K. L. Wagstaff, A. Davies, G. Doran, S. Chakraborty, S. Anwar, D. L. Blaney, S. Chien, P. R. Christensen, and S. Diniega, Responsive Onboard Science for Europa Clipper, Outer Planets Assessment Group Meeting, Sept 2018.

27. S. Chakraborty, A. Banerjee, S. Gupta, P. Christensen, A. Papandreou-Suppappola, Automated Land Cover Change Detection and Mapping from Hidden Parameter Estimates of Normalized Difference Vegetation Index (NDVI) Time-Series, AGU Fall Meeting Abstract, 2017.