Jake Y. Chen, Ph.D.
Triton Endowed Professor of Biomedical Informatics & Data Science
Founding Director, Systems Pharmacology AI Research Center (SPARC)
Adjunct Professor of Computer Science; Adjunct Professor of Biomedical Engineering
Senior Member, O’Neal Comprehensive Cancer Center; Member, Immunology Institute
UAB School of Medicine
Over 25 years advancing AI-driven biomedical informatics, network/systems biology, and computational drug discovery. Developing systems pharmacology models, multi-omics AI frameworks, and digital twin simulations that integrate clinical, genomic, and real-world data for precision medicine. 200+ peer-reviewed publications and 200+ invited talks worldwide.
Contact MPI for CONNECT, an NIH U54-funded national AI-infrastructure initiative building AI-ready biomedical knowledge networks. Fellow of ACMI, AIMBE, and AMIA; ACM Distinguished Member; named among the “Top 100 AI Leaders in Drug Discovery and Healthcare” (2019); finalist for the MIRA “Technology Educator of the Year” Award in Indiana.
As the founding PI of the AI.MED Lab, Prof. Chen previously served as Chief Bioinformatics Officer and Associate Director of the UAB Informatics Institute — the predecessor unit that became today’s Department of Biomedical Informatics and Data Science.
Current Positions
Triton Endowed Professor
Biomedical Informatics & Data Science
UAB School of Medicine · 2023–present
Founding Director
Systems Pharmacology AI Research Center (SPARC)
UAB School of Medicine · 2023–present
Adjunct Professor
Computer Science
UAB College of Arts & Sciences · 2017–present
Adjunct Professor
Biomedical Engineering
UAB College of Engineering · 2018–present
Senior Member
O'Neal Comprehensive Cancer Center
UAB · 2017–present
Member
Immunology Institute
UAB · 2019–present
Contact MPI, CONNECT (NIH U54)
Collaborative Network for Nurturing Ecosystems of Common Fund Team Science
NIH Office of the Director · 2024–2029
Selected Leadership
Chief Bioinformatics Officer & Associate Director
Informatics Institute, UAB · 2016–2023
MPI, Cell Maps for AI (CM4AI), Bridge2AI Program (NIH OT2)
NIH Common Fund Program · 2022–2026
Past President
Mid-South Computational Biology & Bioinformatics Society (MCBIOS) · 2021–2022
Founding Director, Indiana Center for Systems Biology and Personalized Medicine
Indiana University–Purdue University · 2007–2016
Founder & Chairman, MedeoLinx, LLC
Indianapolis, IN · 2006–2016
Co-founder & Chief Informatics Officer, Predictive Physiology and Medicine, Inc.
Bloomington, IN (raised >$6M in venture funding) · 2006–2008
Head of Computational Proteomics & Principal Bioinformatics Scientist
Myriad Proteomics (Prolexys Pharmaceuticals), Salt Lake City, UT · 2002–2003
Our Vision
Where Drug Discovery
Meets AI
Through SPARC, we build intelligent systems that bridge computational innovation and clinical impact — accelerating how new therapies are discovered, validated, and delivered to patients.
Explore Our ResearchResearch Focus
Five Pillars of AI.MED
Systems Pharmacology & Drug Discovery
Computational approaches for drug target identification, molecular modeling, and therapeutic development.
Biomedical Knowledge Networks
Large-scale biomedical data ecosystems, knowledge graphs, and semantic data integration.
Multi-omics & Interpretable AI
Visualization, interpretable machine learning, and multi-scale biological data analysis.
Digital Twins & Precision Medicine
Patient-level computational models for personalized therapeutic strategies.
Translational Data Infrastructure
Scalable data platforms, clinical informatics pipelines, and research-to-bedside tools.
Honors & Recognition
Distinctions
Why Students Join AI.MED
- Direct mentorship from a globally recognized leader with 25+ years of experience bridging AI and biomedicine.
- Access to cutting-edge multi-omics datasets, high-performance computing, and deep industry collaborations.
- A proven track record of placing graduates in top academic, pharma, and tech positions worldwide.
Ready to advance AI-driven medicine?
Explore our research or join the lab to shape the future of biomedical AI.