I develop machine learning models for satellite data to solve problems related to sustainability, climate change and social good. Currently, I am a Machine Learning Scientist (Postdoctoral Fellow) at CIRA CSU and NSF AI2ES starting January'22 hosted by Dr. Imme Ebert-Uphoff and Kyle Hilburn. Specifically, I am interested in exploring the use of self-supervised learning and attention based neural networks to extract the spatio-temporal features from the time-series satellite imagery.

In October'21, I earned my Ph.D. in Computer Engineering from the University of Massachusetts, Amherst, where I was advised by Prof. David Irwin. My doctoral work focuses on using ML and satellite imagery for control, modeling and, forecasting solar power.

Work Experience:

Machine Learning Scientist (Post-Doc) - CIRA CSU and NSF AI2ES, January 2022 - Present

Research Intern - GeoAI group @Oak Ridge National Labs, Tennessee, June-August 2021

Research Assistant (Pre-Doc) - School of Computer Science & Engineering - NTU, Singapore, 2014-2015


Ph.D. in Computer Engineering, University of Massachusetts Amherst, Sep. 2015 - Oct. 2021

M.S. by Research in Information Technology, IIIT- Bangalore (India), 2011-2014

B.Tech in Computer Science, MDU Rohtak (India), 2007-2011




Join us at the Trustworthy Artificial Intelligence for Environmental Science (TAI4ES) Summer School organized by NSF AI2ES & NCAR from 27-30 June'22 . Registration is mandatory and free for students!

Our paper "A Moment in the Sun: Solar Nowcasting from Multispectral Satellite Data using Self-Supervised Learning" got accepted in ACM e-Energy'22 conference. Catch the virtual talk on 29th June'22 at e-Energy'22

Very excited to share that I have joined CIRA Colorado and NSF AI2ES institute as Machine Learning Scientist (Postdoc).

Just released the final chapter of my Ph.D. thesis in our new paper

I successfully passed my Ph.D. thesis defense on 18th October'21 !! Yayyyyyy

Our paper "Self-Supervised Learning on Multispectral Satellite Data for Near-Term Solar Forecasting" got accepted in ICML Workshop on Tackling Climate Change with Machine Learning'21.

Super excited to be spending the Summer'21 researching at the GeoAI group, Oak Ridge National Labs!

I won third prize in the ECE 3-Minute Thesis (3MT)'21 Competition at UMass Amherst.

Serving as TPC member for FATEsys'21.

I passed my Ph.D. Dissertation Proposal titled, "Data-Driven Control, Modeling, and Forecasting for Residential Solar Power", at UMass Amherst.

I won second prize in the Lightning Talks Competition during the 2020 Energy Data Analytics Symposium! Check the talk here, and the media coverage on Twitter, LinkedIn, Facebook.

Check out the media coverage by UMass and UMass IPO on the Duke Data Analytics talk.

Our Paper "See the Light: Modeling Solar Performance using Multispectral Satellite Data", received honorable mention under best presentation award in ACM Buildsys'20

Our Paper "See the Light: Modeling Solar Performance using Multispectral Satellite Data", Akansha Singh Bansal and David Irwin got accepted in ACM Buildsys'20.

Our Paper "Exploiting Satellite Data for Solar Performance Modeling", Akansha Singh Bansal and David Irwin got accepted in IEEE Smartgridcomm'20.

I am teaching an undergraduate first-year seminar course at UMass Amherst this Fall'2020 titled - "Staring at the Sun: An Introduction to Solar Energy".

I am attending Grace Hopper Celebration (GHC'19) at Orlando, Florida - (October 1 - October 4' 2019).

I will be presenting our paper (On the Feasibility, Cost, and Carbon Emissions of Grid Defection) at IEEE Smartgridcomm'19 in Beijing, China - (October 20 - October 24' 2019).


I was born and grew up in India. I am married to Trapit Bansal

I am presently located in San Francisco, California. Apart from research, I enjoy cooking, doodling, playing board games and video games.