Hariri Institute recognizes ECE researchers
by A.J. Kleber
Each year, the Rafik B. Hariri Institute for Computing and Computational Science & Engineering awards funding and institutional support to early career faculty, doctoral students and research teams across disciplines and departments at Boston University. These awards serve the Institute’s mission to foster and accelerate impactful research in computing and AI. ECE researchers were among the recipients in each category of their 2026 cohort.
A computational visionary
Wei-Lun (Harry) Chao, who joined the ECE faculty in January 2026, was selected as one of five new Hariri Junior Faculty Fellows. This three-year appointment carries $10K in research funding and collaborative opportunities, including leading participation in the Institute’s Distinguished Speaker Series. Professor Chao’s research is centered on computer vision and machine learning, with broad applications in autonomous driving, ecological science, healthcare, and beyond. He holds a 2025-2028 Peter J. Levine Career Development Professorship, and was recently promoted to Associate Professor.
Robust and multifaceted
ECE Ph.D. student Ilker Isik’s graduate research is centered around neuro-symbolic AI, a blended approach to artificial intelligence which integrates symbolic computation (logic, formal methodology, automation) with data-driven learning (neural networks, deep learning), combining the strengths of both. Working with advisor Professor Wenchao Li (ECE, SE), he aims to build reliable and interpretable AI systems. As one of five new Hariri Graduate Student Fellows, a three-year appointment, he will benefit both from the opportunity to collaborate with his peers on the Institute-sponsored “Did you know …?” series, and from $5K in research support.
Modeling neural dynamics for reward-based learning
The Hariri Institute’s Focused Research Programs (FRPs) support faculty-led, multidisciplinary research teams to pursue ambitious projects which, as the institute’s director and ECE faculty member Distinguished Professor of Engineering Ioannis Paschalidis (ECE, BME, SE) puts it, “can drive meaningful advances in research and innovation” at the convergence of multiple disciplines.
Professor Venkatesh Saligrama (ECE, SE) and co-PI Professor Mark Howe (Psychology & Brain Sciences) are spearheading one such effort, with $90K in seed funding from a Hariri FRP grant. In Saligrama’s words, they plan to “use AI to uncover how the brain learns–and use brain learning circuits as a testbed for building more interpretable, adaptive AI.”
The project, titled “Multi-Scale Neuro-AI for Striatal Learning: Machine Learning, Voltage Imaging, and Safe Perturbation Design” centers on the effects of interactions between the neurotransmitters dopamine and acetylcholine, often referred to as the “reward system.” Their project blueprint involves computational modeling of these chemical dynamics, analysis of their connections to behavior, and the identification and codification of learning rules. These insights, enabled in part by machine learning, may assist in both the design of safe and effective neuromodulation methods, and that of biologically-informed approaches to AI/ML development.
Several other ECE researchers, including Professor Wei-Lun (Harry) Chao and Research Scientist Aditya Gangrade, are attached to the project, alongside collaborators from the departments of biomedical engineering, psychology, computer science, anatomy & neurobiology, computing & data sciences, and the Neurophotonics Center.