Computational Research Symposium 2026 Schedule of Events

COREY ADAMS is a Senior Software Engineer at NVIDIA, with a focus on AI and Physics. He received his PhD in High Energy Physics from Yale University in 2016, and was a postdoc at Harvard until 2018 when he joined Argonne National Laboratory. At Argonne, he held a joint appointment between the Leadership Computing Facility and the Nuclear Physics Division, and in 2021 he received the Department of Energy’s Early Career Award for his research into Neutrinoless Double Beta Decay. While at Argonne, he was the lead for machine learning frameworks on the Aurora Supercomputer, which debuted at #2 on the top-500 list. At NVIDIA, he works at the intersection of GPU computing, software development, and Physics-based surrogate modeling, as a senior developer and researcher for the PhysicsNeMo package.

DHRUV BARONIA is a senior analytics and AI leader in financial services, currently serving as SVP, Head of Data Analytics for Wealth Management at Northern Trust. He leads enterprise‑scale initiatives spanning advanced analytics, machine learning, and generative AI, with a focus on driving growth, productivity, and risk‑aware decision‑making across wealth management. His work bridges strategy and execution—modernizing data platforms, embedding AI into client and advisor workflows, and translating complex data into actionable business outcomes for senior leadership and frontline teams.

An innovator at the intersection of AI, data, and financial services, Dhruv is a U.S. patent holder and has built and scaled analytics solutions across sales enablement, client intelligence, and digital advice platforms. He holds an MBA and is a CFA charterholder, bringing a strong foundation in investment management, economics, and applied analytics. Recognized for thought leadership and practical innovation, he regularly contributes to industry forums and academic settings, sharing insights on responsible AI adoption, modern data architectures, and the evolving role of analytics in wealth management.

ANDREW BOYD is a Professor in the Department of Biomedical and Health Information Sciences at University of Illinois Chicago. He is also the Associate Vice Chancellor for Research in Computing and Data Initiatives/Chief Research Information Officer. He was awarded 2015 UIC Researcher of the Year in Clinical Sciences, Rising Star. He was awarded the 2024 AMIA Physician Innovator of the year. He has over 100 publications (with ~ 4000 citations). He has been a PI, Co-PI, Co-I on numerous grants from numerous agencies. Dr. Boyd’s research focuses on “data simplification to improve clinical outcomes” engaging administrators, researchers and patients. His recent work has measured the vocabulary differences between physicians, nurses, physical therapy, and occupational therapy to highlight the challenges and benefits to team-based care with a 10 million dollar ARPA-H project. Dr. Boyd was recognized as Crain’s Chicago Business Notable Leaders in Health Care Technology. Dr. Boyd is a Fellow of the American College of Medical Informatics (FACMI), American Medical Informatics Association (FAMIA) and New York Academy of Medicine (FNYAM).

TAYLOR CHILDERS is a physicist and computer scientist at Argonne National Laboratory, where he leads the development of next-generation infrastructure for AI-driven science. After earning his Ph.D. in Physics from the University of Minnesota, Taylor spent six years at CERN as a member of the ATLAS experiment—first as a post-doctoral researcher for Universität Heidelberg and subsequently as a CERN Fellow—contributing to the historic discovery of the Higgs boson. An early adopter of deep learning in the physical sciences, he began utilizing TensorFlow upon its release in 2015 to pioneer particle identification within the ATLAS detector using raw sensor data. Today, he serves as the Deputy Technical Director for ALCF-4, the flagship successor to the Aurora supercomputer, and leads the American Science Cloud project within the Genesis Mission. His current work focuses on enabling the use of artificial intelligence and large-scale computing to drive scientific discovery at an exascale level.

ALVIN CHIN is a Visiting Clinical Assistant Professor in the Dept of Information and Decision Sciences at the College of Business Administration, University of Illinois Chicago.  Previously, he was a Research Scientist at Discovery Partners Institute.   His expertise and interests are in mobile social networking, data science, machine learning and AI, IoT and responsible AI. He has worked in industry for over 15 years with RXO as a Principal Data Scientist; BMW Group as IT Innovation Engineer, Emerging Technology Researcher and Senior Machine Learning Researcher; and Microsoft and Nokia as Senior Researcher and Product Owner.  He was previously an Adjunct Professor at DePaul University in the College of Computing and Digital Media.   A recognized industry thought leader; Dr. Chin holds ~20 patents, has ~60 publications, and has spoken on international, national, and local panels.  He has a PhD in Computer Science from the University of Toronto, MASc in Software Engineering from University of Waterloo, and BASc in Computer Engineering at University of Waterloo. Dr. Chin serves on the leadership board of ACM as Chicago Chapter Chair, Chair of IEEE Computer Society Chicago and Chair of IEEE Vehicular Technology Society Chicago. Dr. Chin is a Senior Member of both IEEE and ACM, and an Advisory Council Member of the Chicago AI Council at AI 2030.

HANHEE PAIK is the IBM Director of the Quantum Algorithm Centers. In this role, she is responsible for the success of IBM’s major quantum algorithm and application research partnerships with leading institutions worldwide, including RIKEN, the University of Tokyo, the University of Illinois Urbana-Champaign, the University of Chicago, Yonsei University, RPI, and MIT. Previously, she served as Head of IBM Quantum Japan, where she established the IBM Quantum Japan team and mission to focus on the development of quantum‑centric supercomputing technologies in collaboration with Japanese partners.

Paik earned her Ph.D. in Physics from the University of Maryland, College Park. She was a postdoctoral fellow at the university’s Laboratory for Physical Sciences (LPS) before moving to Yale University to work with Professors Robert Schoelkopf, 2025 Nobel Laureate Michel Devoret, and Steve Girvin. She later joined IBM to advance quantum processor architectures and quantum computing systems, notably leading the technical team that developed IBM’s first 16-qubit quantum computers, which were made available to the world.

In 2021, Paik was elected a Fellow of the American Physical Society for pioneering a novel superconducting qubit architecture that catalyzed the commercialization of superconducting quantum computing and for her significant contributions to advancing quantum computing research across the industry.

MARY PASQUINELLI, DNP, APRN, FNP-BC, CTTS, is a doctorate-prepared nurse practitioner and Director of the Lung Cancer Screening Program at UI Health. Her work focuses on reducing lung cancer disparities by integrating artificial intelligence, risk prediction models, and biomarkers to advance equitable early detection.

She is a principal investigator on multiple funded studies, including national collaborations evaluating AI tools such as Sybil, and has published extensively on screening disparities and risk-based approaches. Dr. Pasquinelli serves on the Board of the International Association for the Study of Lung Cancer and on national policy committees, with her work recognized by leading organizations in early detection and health equity.

KATHERINE M. RILEY is the Director of Science for the DOE’s Argonne Leadership Computing Facility, leading the science mission and strategy for one of the largest compute and data resources for open science.  She ensures the facility delivers leading-edge computational and data science capabilities and expertise that help advance fundamental discovery and understanding in a broad range of scientific and engineering disciplines.  She has served as program manager for DOE’s INCITE program.

She collaborates extensively across the DOE complex, working to understand and improve the environment for computational science.