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2025 Investiture Information

Human-Centered 

 

Research Quick Takes

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Jun 05, 2025

Improving Healthcare Access

Professor Vikrant Vaze is a co-author of "A novel outreach approach for identification of familial hypercholesterolemia: Interview-based formative evaluation to improve healthcare access and quality" published in PEC Innovation. "This was a collaborative effort with folks from DH and Geisel, as well as Family Heart Foundation. The study is aimed at designing and evaluating direct outreach and referral to specialty care for patients with an elevated risk of FH identified through a machine learning model and expert review of the electronic record in a rural US health system. It's an excellent human-centered design thinking exercise and it yielded a great deal of success," said Vaze.

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May 22, 2025

Cyber Defense x2

Professor Peter Chin's Learning, Intelligence + Singal Processing (LISP) lab had two papers accepted at the Reinforcement Learning Conference (RLC): "Hierarchical Multi-agent Reinforcement Learning for Cyber Network Defense" and "Quantitative Resilience Modeling for Autonomous Cyber Defense." Said Chin, "Both papers are part of the outcome of the four-year DARPA research project called CASTLE: Cyber Agents for Security Testing and Learning Environments that LISP lab has been working on to develop game-theoretic reinforcement learning agents that can outsmart potential cyber adversaries in an enterprise-level network."

Vikrant Vaze

May 22, 2025

Most Read of All Time

Professor Vikrant Vaze is a co-author of “Operational Research: methods and applications” which recently became the most read article of all time in the Journal of the Operational Research Society—the oldest journal in the field of operations research. "This is arguably the first prominent article to provide a comprehensive overview of the state-of-the-art in operations research [OR], from both a methodological and from an applications standpoint. It is meant to serve as the first point of reference for OR academics, researchers, students and practitioners alike," said Vaze.

Clement Nyanhongo

May 01, 2025

Understanding AI Behavior

PhD students Clement Nyanhongo '17 Th'18 and Bruno Miranda Henrique, and Professor Gene Santos co-authored "Reward Distance Comparisons Under Transition Sparsity" published in Transactions on Machine Learning Research. "Traditional reward comparison methods rely on behavioral simulations, which can be costly and pose safety risks. Our method is specifically designed to operate in more realistic and practical settings, recognizing real-world constraints, and outperforms existing approaches across a range of domains," says Santos.

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