Hariri Institute 2025 Junior Faculty Fellows
The Hariri Institute for Computing is pleased to announce our 2025 Junior Faculty Fellows!
The Institute has awarded four Junior Faculty Fellows who are pursuing innovative computationally-driven research with the potential for high impact. Our 2025 cohort of fellows represents a variety of colleges and schools across Boston University. They are applying computational methods and tools to address complex challenges in diverse fields spanning anatomy & neurobiology, biomedical engineering, biostatistics, computer science, computing & data science, global health, neuroscience, physics, and systems engineering.
2025 Junior Faculty Fellows
Huitong Ding, PhD, Research Assistant Professor, Anatomy & Neurobiology, Chobanian & Avedisian School of Medicine, Boston University
Dr. Ding’s research explores brain aging and cognitive heterogeneity, using data science, AI, and digital tools to advance inclusive Alzheimer’s research. Ding’s work focuses on early detection, sex differences, and novel assessment methods to collect cognitive data without formal testing, bridging cognitive science and translational impact.
Hongwan Liu, PhD, Assistant Professor, Physics, College of Arts & Sciences, Boston University
Dr. Liu’s research spans particle and astro-particle physics to cosmology, aiming to uncover the nature of dark matter, dark energy, and the Universe’s evolution. Liu develops novel computational methods using machine learning, simulation-based inference, and variational techniques to tackle key challenges in cosmology and dark matter detection.
Allison Portnoy, PhD, Assistant Professor, Global Health, School of Public Health, Boston University
Dr. Portnoy’s work extends computational research to address global public health challenges. She uses data science to optimize vaccination strategies, assess cost-effectiveness, and inform equitable health policy. Portnoy’s research relies on large-scale modeling and multilateral datasets to guide infectious disease prevention in high-burden settings.
Pawel Przytycki, PhD, Assistant Professor of Computing & Data Science, Faculty of Computing & Data Sciences, Boston University
Dr. Przytycki is a computational scientist whose research combines machine learning, network science, and statistical modeling to study noncoding variants in development and disease. Przytycki’s work looks to integrate large-scale genomics data to decipher the role of the noncoding genome in dictating how cells change state.