Google Research (arshikal at google dot com)
arshika77 at gmail dot com
f20170620g at alumni dot bits hyphen pilani dot ac dot in
Developing Multi-Agent systems for bringing Social Impact at Scale
Bio
I am a Pre-Doctoral Researcher at Google Research India, working in the MASSI lab mentored by Prof. Milind Tambe. My work focuses on developing robust bandit algorithms for efficiently delivering health awareness information in underserved communities in India. My CV is available here.
Previously, I was a Research Assistant at the Kreiman Lab at Harvard University where I worked on adopting continual learning algorithms for continuous domain adaptations.
I’m interested in Continual Learning and Multi-agent Systems with applications in developing large-scale, robust and adaptable AI/ML systems, specifically in public health and social impact domains. I want to develop agents that can provide adaptive, efficient and personalized solutions in a fast-changing world.
2017 - 2022
2021
2021-2022
2022 - present
I graduated from Birla Institute of Technology and Science (BITS), Pilani in 2022. At BITS, I was mentored by Prof. Snehanshu Saha and Dr. Basabdatta Sen Bhattacharya. I also have a deep appreciation for teaching , and I have experience as a Teaching Assistant (TA) in three courses: Object-Oriented Programming, Database Systems, and Econometric Methods. In my free time, I served as a volunteer instructor in Mathematics and English for women and children hailing from the underprivileged families that contributed to the campus’s operations. I enjoy writing as a medium of creative expression and you can find some of my works here, here and here.
Updates
- [Oct 23] Our work on Improving Health Information Access in the World’s Largest Maternal Mobile Health Program via Bandit Algorithms was accepted at the Innovative Applications of Artificial Intelligence 2024 as an Oral Presentation
- [May 23] Our preliminary work on Analyzing and Predicting Low-Listenership Trends in a Large-Scale Mobile Health Program was accepted at the Data Science for Social Good Workshop, KDD 2023 as an Oral Presentation
- [Dec 22] Our work on Adherence Bandits, a specialized RMAB subclass designed to address the complexities of adherence within the domain of public health got accepted at the Artificial Intelligence for Social Good Workshop, AAAI 2023
- [Aug 22] Joined Google AI India as Pre-Doctoral Reseacher! Working with Milind Tambe within MASSI.
- [Aug 21] Joined the Kreiman Lab at Harvard University!
- [Oct 21] Our work on ** a biologically inspired an SNN-based SDM utilizing N-of-M encoding** was aceepted at the Bernstein Conference 2021.
- [Aug 20] Accepted to CBMM’s Brain, Minds and Machines Summer School!
Publications
Improving Health Information Access in the World’s Largest Maternal Mobile Health Program via Bandit Algorithms
Oral Presentation @ Innovative Applications of Artificial Intelligence (IAAI 2024)
Analyzing and Predicting Low-Listenership Trends in a Large-Scale Mobile Health Program: A Preliminary Investigation
Oral Presentation @ Data Science for Social Good Workshop, KDD 2023
Paper
Adherence Bandits
Artificial Intelligence for Social Good Workshop, AAAI 2023
Paper
Continual Learning and Out of Domain Generalization in Continuous Domain Adaptation
Undergraduate Thesis 2022
Paper
Sparse Distributed Memory Using Spiking Neural Networks on Nengo
Bernstein Conference 2021
Paper
Epigraphiology: A Hybrid Approach for Measuring and Analyzing Influence Diffusion in Article Networks
Under Review @ Journal of Scientometric Research
Stock Price and Job Growth: A Causal Influence Study
Preprint 2021
Paper