About me
I am an Assistant Professor in the Department of Computer Science and Engineering at University of Minnesota, Twin Cities.
My general research interests are in the areas of artificial intelligence (AI) and machine learning (ML) where I focus on advancing foundations of AI/ML to solve challenging real-world problems. The overarching theme of my research program is AI to Accelerate Scientific Discovery and Engineering Design. Specific topics include:
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Sequential decision-making under uncertainty in a data-efficient manner (Bayesian optimization and reinforcement learning).
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Probabilistic modeling over combinatorial structured data in small supervised data settings.
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Applications: accelerate the discovery of nanoporous materials for sustainability applications (e.g., carbon capture and storage/separation of gases); accelerate the design of effective, safe, and low-cost drugs/vaccines; and design of high-performance and low-power hardware.
I did my PhD in Computer Science at Washington State University where I was very fortunate to be advised by Dr. Jana Doppa. I also spent three wonderful summers as a research intern at Meta and Google.
- May 2026 - Honored to receive NSF CAREER Award to support our group's research on Adaptive Experimental Design to Accelerate Scientific Discovery and Engineering Design. Grateful to my students and collaborators!
- May 2026 - Undergraduate mentee Bellamy John won the Runner-up Best Poster award for his undergraduate research at 2026 MSI Research Computing Exhibition. Congratulations to Bellamy!
- April 2026 - Paper on Adaptive Experimental Design to Efficiently Determine the Critical Micelle Concentration of a Surfactant accepted at Langmuir Journal. Code
- March 2026 - Excited to co-organize Decision-Making from Offline Datasets to Online Adaptation: Black-Box Optimization to Reinforcement Learning at ICML 2026.
- February 2026 - Tutorial talk on Generative AI for Science and Engineering including our work on Adaptive Experimental Design at GenAI for Science & Engineering Workshop. Recording available here at University of Minnesota's CSE DSI Youtube Channel.
- January 2026 - Received the Innovative Deployed Application Award from IAAI conference 2026 for our Paper on Discovery of Feasible 3D Printing Configurations for Metal Alloys via AI-Driven Adaptive Experimental Design. Grateful to collaborators and the organizers!
- January 2026 - Slides and Website for tutorial on Black-box Optimization from Offline Datasets presented at AAAI 2026.
- November 2025 - Paper on AI driven adaptive experimental design for discovering 3D printing configurations accepted to IAAI/AAAI 2026.
- November 2025 - Paper on offline safe reinforcement learning accepted to NeurIPS 2025. Code
- November 2025 - Paper on real-world benchmark for high dimensional Bayesian optimization derived from urban mobility accepted to NeurIPS 2025. Code
- September 2025 - Paper on sample-efficient exploration of accuracy-calibration pareto frontier in language models accepted to EMNLP 2025. Code
- September 2025 - Tutorial on Black-box Optimization from Offline Datasets accepted at AAAI 2026.
- September 2025 - Excited to organize the fifth iteration of our Annual AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE) at AAAI 2026.
- August 2025 - Co-organized the GenAI4Science Workshop: Integrating Scientific Knowledge into Generative AI at the University of Minnesota.
- August 2025 - New perspective article on AI enabled scientific revolution capturing the consensus discussed at the second NSF workshop on AI-enabled scientific revolution.