SRIJA CHAKRABORTY

SRIJA CHAKRABORTY

  • NASA Postdoctoral Program Fellow
  • NASA/GSFC
  • Employer: UNIVERSITIES SPACE RESEARCH ASSN
  • Research Interests

    Applied Machine Learning, Statistical Signal Processing, Nighttime Remote Sensing, Multitemporal Analysis

    https://srijachakraborty.com

    Current Projects

    Nighttime Remote Sensing

    Tracking Earth system variabilities at night using machine learning

    • anomaly detection from nighttime VIIRS observations and post anomaly monitoring
    • detecting features of interest from nighttime observations
    • towards a machine learning based catalog of nighttime observations

    Land Surface Reflectance and Land Cover Time-Series Analysis

    • Adaptive time-series monitoring and for sequential change detection from multispectral MODIS time-series.
    • Time-varying frequency modeling for change rate monitoring
    • Unsupervised class separability of land surface change events (natural hazards such as wildfires, floods, droughts and coastal land gain)

    Context Based Novelty Detection from Planetary Orbiter Images

    Detecting geological features of interest from THEMIS images and ranking observations using a context-based score of novelty.


    Positions/Employment

    2/2020 - 1/2022

    NASA Postdoctoral Fellowship

    GSFC/ USRA, Greenbelt

    Nighttime Remote Sensing and Machine Learning

    • Unsupervised anomaly detection
    • Multispectral models of nighttime features of interest
    • Multitemporal analysis of nighttime lights
    8/2014 - 12/2019

    Graduate Research Assistant

    Arizona State University, Tempe
    • Multitemporal analysis of MODIS Land Surface Reflectance Time-Series
    • Unsupervised land cover change detection
    • Time-frequency analysis of vegetation time-series
    • Multispectral analysis of land surface reflectance change
    • Novelty Detection in THEMIS images
    5/2018 - 7/2018

    Intern

    Jet Propulsion Laboratory, Pasadena

    Spectral anomaly detection for Europa Clipper onboard Science

    6/2017 - 8/2017

    Intern

    Los Alamos National Laboratory, Los Alamos

    Unsupervised seismic anomaly detection

    Teaching Experience

    Graduate Teaching Assistant, Computer Science, Arizona State University, January 2015 - May 2019

    Education

    PhD, Computer Engineering, Arizona State University, December 2019

    Professional Societies

    IEEE Geoscience and Remote Sensing Society, 2017 - Present
    American Geophysical Union, 2017 - Present

    Professional Service

    Executive Secretary and Panelist - NASA ROSES, 2020, 2021.

    Reviewer - NASA EpSCOR, 2020, 2021.

    Reviewer - NeurIPS Workshop on AI for Earth, 2020.

    Reviewer - Challenges in Deploying and Monitoring Machine Learning Systems, ICML-2020.

    Volunteer - NASA SMD AI/ML Landscape Study, 2020 - Present

    Volunteer - Machine Learning for Science and Engineering, Earth and Environmental Sciences Track, 2020

    Volunteer - IEEE GRSS IADF - Technical Co-Lead: Benchmarking Working Group, 2021 - Present

    Publications

    Refereed

    Hills, D., J. Damerow, B. Ahmmed, et al. N. Catolico, S. Chakraborty, T. Y. Chen, 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, and T. Yao. 2022. "Earth and Space Science Informatics Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science." Earth and Space Science, [10.1029/2021EA002108]

    Talks, Presentations and Posters

    Invited

    Adaptive Representations of Multispectral Satellite Images for Change and Novelty Detection

    10 / 7 / 2019

    Carnegie Institute for Science

    Tracking Dynamic Changes in Land Surface Using Statistical Processing and Bayesian Modeling of Satellite Time- Series Data

    10 / 2 / 2019

    Department of Earth and Environment, Boston University

    Other

    Multispectral Analysis of Land Surface Reflectance Time-Series for Clustering Change Events

    2 / 10 / 2021

    NASA Second AI and Data Science Workshop

    Feature Extraction from Visible Infrared Imaging Radiometer Suite (VIIRS) Observations for Monitoring the Earth at Night

    12 / 4 / 2020

    International Virtual School on Application of Machine Learning and IoT in Remote Sensing, Chapnet- 2020, IEEE Geoscience and Remote Sensing Society, Kolkata Chapter

    Latent Space Representations of VIIRS Multispectral Observations for Monitoring the Earth at Night

    11 / 12 / 2020

    GSFC Early Career Scientist Forum.


    Analysis of Multispectral Land Surface Reflectance Time-Series for Detecting and Classifying Land Cover Change

    11 / 12 / 2020

    2nd NOAA Workshop on Leveraging AI in Environmental Sciences

    Extracting Features from VIIRS Observations for Monitoring the Earth at Night

    11 / 5 / 2020

    NASA SED Director’s Seminar (Earth Science Division).

    Towards Data-Informed Climate Sciences - Leveraging Machine Learning Inferences of Satellite Observations

    8 / 20 / 2020

    Workshop in Data Science in Climate and Climate Impact Research, Weather and Climate Risks Group, ETH Zurich

    Time-Varying Semantic Representations of Planetary Observations for Discovering Novelties

    4 / 26 / 2020

    AI for Earth Workshop, ICLR


    Class Separability of Land Cover Change Events from Multispectral Satellite Image Time-Series


    12 / 12 / 2019

    AGU Fall Meeting.

    Expert Guided Rule Based Prioritization of Scientifically Relevant Images for Downlinking over Limited Bandwidth from Planetary Orbiters

    1 / 2019

    IAAI/AAAI

    Spectral Anomaly Detection for Europa Clipper

    7 / 2018

    Machine Learning and Instrument Autonomy Group, Jet Propulsion Laboratory,

    Region of Interest Aware Compressive Sensing of THEMIS Images and Its Reconstruction Quality

    3 / 2018

    IEEE Aerospace Conference

    Unsupervised Seismic Anomaly Detection

    8 / 2017

    Los Alamos National Laboratory

    Estimation of Dynamic Parameters of MODIS NDVI Time Series Nonlinear Model Using Particle Filtering

    7 / 2017

    IEEE IGARSS

    Publications

    Refereed

    Hills, D., J. Damerow, B. Ahmmed, et al. N. Catolico, S. Chakraborty, T. Y. Chen, 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, and T. Yao. 2022. "Earth and Space Science Informatics Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science." Earth and Space Science [10.1029/2021EA002108]

                                                                                                                                                                                            
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