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Curriculum Vitae

General Information

Full Name Ravi Madduri
Position Senior Computer Scientist and Group Leader
Institution Argonne National Laboratory, Data Science and Learning Division
Email madduri@anl.gov

Education

  • 2002
    MS in Computer Science
    Illinois Institute of Technology, Chicago, US
  • 2000
    BS
    Sri Krishna Devaraya University, Anantapur, India

Professional Experience

  • 2001–Present
    Senior Scientist and Group Leader
    Argonne National Laboratory, Data Science and Learning Division
    • Accelerate Science by developing and applying high-performance computing (HPC) and large-scale data management technologies.
  • 2009–Present
    Senior Scientist
    University of Chicago Consortium for Advanced Science and Engineering
    • Collaborations in developing and applying artificial intelligence (AI)/HPC methods to biomedicine.
  • 2021–Present
    Research Scholar
    University of Illinois, Chicago
    • Collaborations in developing and applying AI/HPC methods to biomedicine.
  • 2021–Present
    Senior Scientist
    Northwestern Argonne Institute of Science and Engineering (NAISE)
    • Collaborations in developing and applying AI/HPC methods to biomedicine.
  • 2021–Present
    Adjunct Clinical Assistant Professor
    University of Illinois at Urbana Champagne, Department of Bioengineering
    • Collaborations in developing and applying AI/HPC methods to biomedicine.
  • 2021–Present
    Research Scientist
    Department of Veterans Affairs, Jesse Brown Medical Center, Chicago
    • Collaborations in developing and applying AI/HPC methods to biomedicine.

Honors and Awards

  • 2025
    • Clinical Research Forum's Top 10 Clinical Research Achievement Award
  • 2021
    • Best presentation and best poster awards at the annual MVP Science meeting
    • Impact Argonne award for the work on the U.S Department of Energy (DOE)/U.S. Department of Veteran Affairs (VA) collaboration
  • 2017
    • DOE Secretary's Appreciation Award for responding to the Vice President's Cancer Moonshot program
    • Senior Scientist at the Center for Research Collaborations, University of Chicago
  • 2012-2016
    • Received $800K in Research Credits from Amazon Web Services
  • 2011
    • Best Paper award in International Conference in Web Services, Washington, D.C.
  • 2010
    • Invited to participate in the National Academy of Engineering's 2010 U.S. Frontiers of Engineering Symposium
    • Pacesetter Award at Argonne National Laboratory
    • Multiple awards from NIH on Cancer Grid
    • Selected for Strategic Lab Leadership Program (SLLP) at University of Chicago Booth School of Business
  • 2008
    • Best Technology Track Award at Teragrid
  • 2004
    • Globus Alliance Certificate of Excellence for outstanding performance on the GRAM, RFT, and NEESgrid projects
  • 2000
    • Young Engineer award from the Institute of Engineers Hyderabad, India

Selected Publications

  • Recent High-Impact Publications (2024-2025)
    • Hoffmann et al. (2025). Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves prediction across ancestry groups. Nature Genetics 57(2):334-344.
    • Carrillo-Perez et al. (2025). Generation of synthetic whole-slide image tiles of tumours from RNA-sequencing data via cascaded diffusion models. Nature Biomedical Engineering 9(3):320-332.
    • Hoang et al. (2025). Enabling end-to-end secure federated learning in biomedical research on heterogeneous computing environments with APPFLx. Computational and Structural Biotechnology Journal 28:29-39.
    • Verma et al. (2024). Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program. Science 385(6706):eadj1182.
    • Justice et al. (2024). A landmark federal interagency collaboration to promote data science in health care: Million Veteran Program-Computational Health Analytics for Medical Precision to Improve Outcomes Now. JAMIA Open 7(4).
  • Privacy-Preserving Federated Learning
    • Li et al. (2024). Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources: A Case Study on Federated Fine-Tuning of LLaMA 2. Computing in Science & Engineering 26(3):52-58.
    • Li et al. (2023). Appflx: Providing privacy-preserving cross-silo federated learning as a service. IEEE e-Science.
    • Ryu et al. (2022). APPFL: open-source software framework for privacy-preserving federated learning. IEEE IPDPSW.
  • Genomics and Precision Medicine
    • Kimbrel et al. (2023). Identification of novel, replicable genetic risk loci for suicidal thoughts and behaviors among US military veterans. JAMA Psychiatry 80(2):135-145.
    • Levin et al. (2023). Genetics of varicose veins reveals polygenic architecture and genetic overlap with arterial and venous disease. Nature Cardiovascular Research 2(1):44-57.
    • Vassy et al. (2023). Cardiovascular disease risk assessment using traditional risk factors and polygenic risk scores in the million veteran program. JAMA Cardiology 8(6):564-574.
    • Chen et al. (2022). Validation of a multi-ancestry polygenic risk score and age-specific risks of prostate cancer: A meta-analysis within diverse populations. eLife 11:e78304.
  • Science as a Service and Reproducible Research
    • Madduri et al. (2019). Reproducible big data science: A case study in continuous FAIRness. PLoS ONE 14(4):e0213013.
    • Madduri et al. (2015). The Globus Galaxies platform: delivering science gateways as a service. Concurrency and Computation: Practice and Experience 27(16):4344-4360.
    • Madduri et al. (2014). Experiences building Globus Genomics: a next-generation sequencing analysis service using Galaxy, Globus, and Amazon Web Services. Concurrency and Computation: Practice and Experience 26(13):2266-2279.

Major Software Projects

  • APPFL - Argonne Privacy Preserving Federated Learning
    • Open-source framework for privacy-preserving federated learning with 141+ pull requests, 38 GitHub stars, 7 forks
    • Successfully applied across diverse scientific fields from smart grid to COVID prediction
    • GitHub: https://github.com/APPFL
  • APPFLx - Federated Learning as a Service
    • Privacy-preserving federated learning platform deployed on AWS
    • Used by NIH-funded Bridge2AI and multiple research groups
    • Service: https://appflx.link
  • MapperTrac
  • Globus Genomics
    • Next-generation sequencing analysis service using Galaxy, Globus, and AWS
    • Used by thousands of users to analyze millions of genomes
    • Led to successful commercial spinoff funded by UChicago Polsky Center, NIH, and NSF SBIR
    • GitHub: https://github.com/globusgenomics
  • caGrid
    • Grid infrastructure for secure data sharing and high-performance workflows in cancer research
    • Adopted by multiple NCI-designated cancer centers across the country
    • Used by hundreds of researchers
    • Archived at: https://github.com/NCIP/cagrid
  • RFT - Reliable File Transfer
    • First 'grid service' created for Wide Area Networks
    • Part of Globus Toolkit versions 3 and 4
    • Integral component of Globus GRAM service for data staging in/out of HPC resources
    • Adopted by thousands of institutions worldwide

Major Funded Projects

  • 2017–Present
    VA-DOE Collaboration: MVP-CHAMPION
    • Development of scalable data analytics, secure computing for PHI on HPC systems, and large-scale AI applied to VA data
    • Total funding: $27M (ANL: $5M)
    • Role: Principal Investigator
  • 2021–Present
    PALISADE-X: Privacy-preserving Analysis and Learning in Secure and Distributed Enclaves
    • DOE/ASCR project developing privacy-enhancing technologies for exascale systems
    • Funding: $2.5M
    • Role: Principal Investigator
  • 2021–Present
    Privacy-Preserving Federated Learning on Multimodal Data
    • DOE/ASCR project
    • Funding: $900K
    • Role: Co-Principal Investigator
  • 2016–2020
    Hardening Globus Genomics (NHGRI R01)
    • Making large-scale genomics analysis available for everybody
    • Funding: $1.58M
    • Role: Principal Investigator
  • 2022–Present
    Medical Imaging Data Resource Center (NIH/UChicago)
    • Funding: $110K
    • Role: Key Personnel
  • 2021–2022
    Medical Imaging Domain-Expertise ML for COVID (C3.ai DTI)
    • Funding: $1M
    • Role: Co-Principal Investigator
  • 2014–2019
    Big Data for Discovery Science (NIH subaward with USC)
    • Funding: $1.43M
    • Role: Key Personnel
  • 2005–2010
    Cancer Bioinformatics Grid (NIH/NCI caBIG)
    • Total program: $100M; ANL/UC: $5M
    • Role: Principal Investigator
  • 2011–2015
    Cardiovascular Grid (NIH/NHLBI)
    • Funding: $1.5M for UC/ANL
    • Role: Co-Lead

Mentoring

  • Postdoctoral Researchers
    • Mitch Conery
    • Wei Tan
    • Bo Liu
    • Ketan Maheshwari
    • Jordan Fuhrman
  • Graduate Students
    • Kyle Chard
    • Ryan Chard
    • Zillinghan Li
    • Pranshu Chaturvedi
    • Paul Landes
    • Shilan He
    • Minseok Ryu
  • Undergraduate Students
    • Cem Onyukusel
    • Ishan Buyyanapragada
    • Akhil Kodumuri
    • Manya Davis
    • Sadkrith Malladi
    • Madhav Hota
    • Daniel Chechelnitsky
    • Annie Ma

Books and Book Chapters

  • Workflows in a service-oriented cyberinfrastructure/grid environment. Springer Service Oriented Computing, Part of the Lecture Notes in Computer Science book series (LNPSE, volume 5472), 2008.
  • Cyberinfrastructures for Life Sciences and Biomedicine. S. Krishnan and R. Madduri. In Cambridge University Press: Cyberinfrastructures for Geoinformatics, Chapter 4, pp. 37–46, 2011.

Research Impact

  • Publications Metrics
    • 90+ journal articles in high-impact venues including Nature, Science, Nature Genetics, JAMA, PLoS ONE
    • 26 conference proceedings
    • 4 preprints
    • 2 books/book chapters
  • Key Contributions
    • Co-lead of landmark DOE-VA collaboration (MVP-CHAMPION) analyzing genetic data from 658,000+ veterans
    • Identified genetic risk loci for suicide, prostate cancer, cardiovascular disease, and 2,000+ traits
    • Pioneered privacy-preserving federated learning for biomedical research
    • Developed Science-as-a-Service platforms used by thousands of researchers worldwide
    • Created Argonne Biomedical Learning Enclave for secure analysis of sensitive health data