Scholar
Aditya Mate
Google Scholar ID: 2yHJIP0AAAAJ
Microsoft New England
Machine Learning
Sequential Decision Making
Reinforcement Learning
Bandits
Probabilistic
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Homepage
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Google Scholar
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Citations & Impact
All-time
Citations
661
H-index
13
i10-index
16
Publications
20
Co-authors
10
list available
Contact
Email
adityamate@microsoft.com
CV
Open ↗
Twitter
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GitHub
Open ↗
LinkedIn
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Publications
2 items
Preventing Catastrophic Forgetting: Behavior-Aware Sampling for Safer Language Model Fine-Tuning
2025
Cited
0
One Head, Many Models: Cross-Attention Routing for Cost-Aware LLM Selection
2025
Cited
0
Resume (English only)
Academic Achievements
Recipient of the IAAI 2023 Innovative Application Award
Second prize at INFORMS 2022 'Doing Good with Good OR' competition
Best paper awards at NeurIPS 2021 and NeurIPS 2020 workshops on Machine Learning for Public Health
Paper accepted at AAAI 2022: 'Field Study Deploying Restless Bandits in Assisting Non-profits Improve Maternal Health'
Paper accepted at AAMAS 2022: 'Efficient Algorithms for Streaming Bandits'
Research featured in Harvard newsletter, Google AI blog, and Nature newsletter
Selected by India’s Department of Science & Technology to represent India at the International Science School, University of Sydney (2013)
Research Experience
Applied Scientist-2 at Microsoft New England, Cambridge MA, July 2023–present, Manager: Dr. Chester Curme
Research Intern at Google Research, India, June 2022–Sept 2022, Manager: Dr. Aparna Taneja
Student Researcher at Google Research, USA, Nov 2021–April 2022, Managers: Philip Nelson, Dr. Aparna Taneja; awarded a spot bonus for impact
Research Intern at IBM Research, Thomas J. Watson Research Center, USA, June 2021–Sept 2021, Manager: Dr. Kush Varshney
Research Intern at Google Research, USA, April 2021–June 2021, Manager: Philip Nelson; awarded a peer bonus
R&D Intern at Sony Corporation, Tokyo, Japan, May 2016–July 2016, Manager: Yohei Kawamoto
Background
Passionate about using AI to solve impactful real-world problems
Research interests include Machine Learning, Sequential Decision Making, and Causal Inference
Ph.D. research focuses on applying restless multi-armed bandits, learning, and causal inference to public health challenges
Developed novel algorithms for tuberculosis prevention and improving maternal & child health
Committed to real-world deployment; as of early 2023, his system has assisted over 100,000 enrolled mothers in partnership with an NGO
Co-authors
10 total
Milind Tambe
Professor & Director CRCS Center @Harvard; Director "AI for Social Good" @Google Research
Andrew Perrault
Assistant Professor, Dept. of Computer Science and Engineering
Co-author 3
Bryan Wilder
Assistant Professor of Machine Learning, Carnegie Mellon University
Marie-Laure Charpignon
Postdoctoral fellow in implementation science and clinical informatics
Shahin Jabbari
Drexel University
Co-author 7
Co-author 8
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