Akanksha Atrey

Biography

Akanksha Atrey is a Research Scientist in the Software and Data Systems Research Lab where she works on AI/ML systems, Web3 infrastructure, and edge computing. Akanksha's research interests span over multiple topics in these areas including privacy, trustworthiness, resource-efficient ML, and blockchain technologies. Her prior work has focused on building systems for machine learning that enable explainability and generalizability, building trustworthy and privacy-preserving ML systems for resource-constrained edge environments, and designing machine learning solutions for ubiquitous computing. Prior to joining graduate school, she was a software engineer at IBM where she worked on the z/OS Mainframe. Among her achievements, she has been named a ML and Systems Rising Star 2023, awarded as a CRA-W Research Scholar, and received the NSF Graduate Research Fellowship Program Honorable Mention.

Education

Ph.D. in Computer Science, University of Massachusetts Amherst
M.S. in Computer Science, University of Massachusetts Amherst
B.S. in Computer Science and Mathematics, State University of New York at Albany

Selected Articles and Publications

W4-Groups: Modeling the Who, What, When and Where of Group Behavior Via Mobility Sensing

Akanksha Atrey, Camellia Zakaria, Rajesh Balan, Prashant Shenoy
ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) 2024.
SODA: Protecting Proprietary Information in On-Device Machine Learning Models

Akanksha Atrey, Ritwik Sinha, Saayan Mitra, Prashant Shenoy
ACM/IEEE Symposium of Edge Computing (SEC) 2023.
Measuring and Characterizing Generalization in Deep Reinforcement Learning

Sam Witty, Jun K. Lee, Emma Tosch, Akanksha Atrey, Kaleigh Clary, Michael L. Littman, David Jensen
Applied AI Letters 2021.
Preserving Privacy in Personalized Models for Distributed Mobile Services

Akanksha Atrey, Prashant Shenoy, David Jensen
IEEE International Conference on Distributed Computing Systems (ICDCS) 2021.
New Frontiers in IoT: Networking, Systems, Reliability, and Security Challenges

Saurabh Bagchi, Tarek F. Abdelzaher, Ramesh Govindan, Prashant Shenoy, Akanksha Atrey, Pradipta Ghosh, Ran Xu
IEEE Internet of Things Journal 2020.
Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning

Akanksha Atrey, Kaleigh Clary, David Jensen
International Conference on Learning Representations (ICLR) 2020.
Identifying When Effect Restoration Will Improve Estimates of Causal Effect

Hüseyin Oktay, Akanksha Atrey, David Jensen
SIAM International Conference on Data Mining (SDM) 2019.
Generalization in Deep Reinforcement Learning

Sam Witty, Jun Ki Lee, Emma Tosch, Akanksha Atrey, Michael Littman, David Jensen
Critiquing and Correcting Trends in Machine Learning Workshop at NeurIPS 2018.

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