Quantum Computing: New Frontiers in Biomedical Research Innovation Lab

In December 2024, the NIH Office of Data Science Strategy (ODSS) and the National Cancer Institute (NCI) hosted an Innovation Lab to explore the transformative potential of quantum computing in biomedical research. Over five days, 27 experts specializing in quantum computing, quantum simulation, and quantum physics with researchers in biomedical sciences, computational biology, and data science collaborated to develop groundbreaking research ideas.

To support promising projects, a challenge prize competition awarded a total of $100,000 to winning teams. This innovation lab marked a significant step in NIH’s efforts to apply quantum computing to complex biomedical challenges.

Outcomes: Teams, Projects, Winners

$25,000 Challenge Prize Winners

  • Team QSim4BM – To develop Quantum Simulator for Biomedicine (QSim4BM)
    • Zhenhua Jiang, PhD, University of Dayton Research Institute - Quantum simulation, density functional theory, stochastic modeling, and quantum algorithms
    • Rozita Laghaei, PhD, Pittsburgh Supercomputing Center, Carnegie Mellon University – Computational biology, statistical mechanics, multi-scale modeling of biological systems.
  • Team Quantum Networks – To explore an application of quantum networks to solve real-world biomedical research problems
    • Yong Chen, PhD, Associate Professor of Biological and Biomedical Sciences at Rowan University - deep learning, single cell -omics, systems biology, and mathematical modeling.
    • Fei Li, PhD, Associate Professor of Computer Science at George Mason University - quantum computing.
    • Chi Zhang, PhD, Associate Professor of Biomedical Engineering at Oregon Health & Science University - bioinformatics and systems biology.
  • Team Quantum Heart – To transform the current clinical decision-making paradigm using quantum computing's ability
    • Iman Borazjani, PhD, Texas A&M University - image-based fluid and tissue simulations, cardiovascular flows, classical computations.
    • Wookjin Choi, PhD, Sidney Kimmel Comprehensive Cancer Center at Thomas Jefferson University - computational medical physics, AI for medical imaging.
    • Jiaqi (Jimmy) Leng, PhD, University of California, Berkeley - quantum Computing, quantum optimization, scientific computing.
    • Zhenhua Jiang, PhD, University of Dayton Research Institute - quantum computing, scientific computing.

$12,500 Challenge Prize Winners

  • Team Baymax – To explore the application of quantum Bayesian networks (BN) and apply to biological and nanomaterial domains
    • Lisa Stabryla, PhD, Assistant Professor at the University of Illinois Chicago – engineering, antimicrobial resistance and nanomaterial design.
    • Laia Domingo, Chief Scientific Officer at Ingenii - quantum computing quantum Bayesian networks, and the application of quantum methods for biomedical research.
    • Noah Huffman, PhD candidate from Stanford University - quantum computing, specifically in the area of error characterization, contributing to the robustness of quantum algorithm development.
    • Shagun Gupta, Data Scientist II from Cornell University - biostatistics, focusing on biomarker discovery to bridge computational models with clinical relevance.
  • Team QMAP – To determine tissue and electrophysiological properties of the heart in vivo based on existing imaging approaches using quantum computing
    • Talita Perciano, PhD, Research Scientist, Lawrence Berkeley National Laboratory - quantum algorithms (especially efficient encoding of classical data), image processing, machine learning, scientific data analysis, probabilistic graphical models, high-performance computing.
    • John Mayfield, MD, PhD, Clinical Neuroradiology Fellow, Massachusetts General Hospital - clinical application of novel technologies including medicine, medical physics and imaging, quantum computing, and machine learning including variational quantum circuit algorithms to predict multiple sclerosis disability.
    • Himanshu Thapliyal, PhD, Associate Professor of Electrical Engineering and Computer Science at the University of Tennessee Knoxville - quantum circuits, quantum design automation, and quantum machine learning.  
    • Yang Yang, PhD, Applied mathematician at the Michigan State University - computational math, biomedical imaging sciences, quantum algorithms, scientific computing.
    • Sunho Park, PhD, Research Scientist at the Mayo Clinic - machine learning and deep Bayesian learning to quantify uncertainty in model predictions.
    • Laia Domingo, PhD, Chief Science Officer at Ingenii - quantum machine learning and quantum optimization for life sciences data.

Other Notable Teams & Projects

  • Team Quantum Galaxy – To create a new virtual platform to democratize access to quantum computing for the biomedical health sciences
    • Ariosto Siqueira Silva, PhD, H. Lee Moffitt Cancer Center and Research Institute – evolutionary dynamics and molecular mechanisms driving progression and therapy resistance in cancer.
    • Ben Cordier, PhD, Knight Cancer Institute, Oregon Health & Science University – cancer genomics, quantum algorithms, quantum simulation, machine learning, computational complexity, open-source software, and scientific reproducibility.
    • Roel Van Beeumen, PhD, Lawrence Berkeley National Laboratory – applied mathematics, quantum computing and quantum algorithms.
    • Peter White, PhD, The Abigail Wexner Research Institute at Nationwide Children’s – integrating and analyzing diverse data, such as genomic data and electronic health records, for diagnosing and treating pediatric diseases.
  • Team Quantum-enhanced Antibody Design – To develop a hybrid quantum-classical approach for antibody engineering
    • Luis Aparicio, PhD, Columbia University - Computational and Systems Biology, Cancer Genomics, Theoretical Physics.
    • Michele Vischi, PhD, University of Trieste - Quantum computing, noisy quantum circuits, quantum error mitigation.
    • Jiaqi (Jimmy) Leng, PhD, University of California - Berkeley, Quantum Computing, Quantum Optimization, Scientific Computing.
  • Team Quantum Digital Twins – To create and leverage a digital twin methodology for predicting cancer treatment
    • Wei Wu, PhD, UC San Francisco - Cancer Biology
    • Ahmad Najafi, PhD, Drexel University - Engineering
    • Wandi Ding, Middle Tennessee State University - Math/Data Science

This page last reviewed on April 24, 2025