Talks

[keynote] [tutorial] [seminar/conference] [panel]

Keynote

  • “Looking at the  big picture: Computational analysis of graphs that represent the topology of complex networked systems”
    Keynote speech, 3rd International Conference on Smart Grid Technology and Data Processing (SGTDP 2017), Suzhou, China, Feb. 16-17, 2017.
  • “Making Sense of Large-Scale Biological Networks – Computational Approaches for Comparative Network Analysis and Network Module Detection”
    Keynote speech, IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2016), Chiang Mai, Thailand, Oct. 5-7, 2016.

Tutorial

  • “Generative AI Models for Signal and Data Processing: Theory, Methods, and Applications”
    Tutorial, 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024), Seoul, Korea, 14~19 April 2024. (Joint presentation with Dr. Youngjoon Hong)
  • “A Novel Bayesian Paradigm for Designing Robust Operators and Optimal Experiments for Complex Systems Under Uncertainty”
    Tutorial, 1st Workshop on Materials Informatics in Xi’an (MIX) & 2nd Joint Xi’an Jiaotong University and Shanghai University Materials Genome Initiative Workshop, X’ian, China,, May 29-31, 2019.
  • “Machine Learning Applications in Computational Network Biology”
    Tutorial, Seoul National University, Big Data Institute, Seoul, Korea, February 18, 2019.
  • “Models and algorithms for analysis of large-scale biological networks”
    Tutorial, The 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2017), Jeju Island, Korea, July 11-15, 2017.
  • “Soft Wireless Bioelectronics and Signal Processing for Hacking Nervous System: Opportunities and Challenges”
    Tutorial, 50th IEEE International Symposium of Circuits and Systems (ISCAS 2017), Baltimore, MD, May 28-31, 2017.

Seminar & Conference Presentation

  • “Generative AI in Action: How It’s Changing Science and Engineering”
    Invited lecture, Computational Research Leadership Council (CRLC) Seminar Series, Fort Hays State University, Feb. 2, 2026.
  • “Generative AI in Action: How It’s Changing Science and Engineering”
    Invited lecture, Computational Research Leadership Council (CRLC) Seminar Series, Fort Florida International University, Nov. 21, 2025.
  • “Accelerating Molecular Discovery through Uncertainty-Aware AI”
    Invited seminar, School of Medicine, University of Missouri, Nov. 12, 2025.
  • “Generative AI in Action: How It’s Changing Science and Engineering”
    Invited lecture, Computational Research Leadership Council (CRLC) Seminar Series, Skyline College, Oct. 7, 2025.
  • “Learning Under Uncertainty: AI Approaches for Accelerating Molecular Design and Discovery”
    Invited seminar, Korean American Society in Biotech and Pharmaceuticals (KASBP) Boston Chapter, Sep. 23, 2025, Cambridge, MA.
  • “Confronting Uncertainty in AI for Science”
    Invited talk, 61st Allerton Conference on Communication, Control, and Computing, Sep. 17–19, 2025, Urbana, IL.
  • “Generative AI in Action: How It’s Changing Science and Engineering”
    Invited lecture, Computational Research Leadership Council (CRLC) Seminar Series, Florida A&M University, Sep. 4, 2025.
  • “Design Smarter, Discover Faster: AI for Molecular Discovery Under Uncertainty”
    Invited seminar, AI-CRED Institute (AI Co-Research & Education for Innovative Drug Institute), Korea Advanced Institute of Science and Technology (KAIST), August 18, 2025.
  • “From Small Data to Big Insights – AI/ML Solutions for Uncertainty and Complexity in Science”
    Invited seminar, Applied Machine Learning (AML) Seminar Series, Los Alamos National Laboratory, July 29, 2025.
  • “Enabling Small-Data AI for Science”
    Invited lecture, Computational Research Leadership Council (CRLC) Seminar Series, Seattle Pacific University, April. 9, 2025.
  • “Data-Efficient Strategies for Enhancing Generative AI Models in Multi-Objective Molecular Design”
    Invited talk, Session on “Harnessing Generative AI: Revolutionizing Toxicology Research”, The SOT 64th Annual Meeting, March 16-20, 2025, Orlando, FL.
  • “Enabling Small-Data AI for Science”
    Invited lecture, Computational Research Leadership Council (CRLC) Seminar Series, The University of Texas at El Paso, Feb. 7, 2025.
  • “Enabling Small-Data AI for Science”
    Invited lecture, Computational Research Leadership Council (CRLC) Seminar Series, Arizona State University, Jan. 27, 2025.
  • “Objective-Driven Optimal Experimental Design: Quantifying the Uncertainties that Matter and Reducing Them Efficiently and Effectively”
    Invited seminar, University of Massachusetts Boston, Department of Physics, Oct. 2, 2024.
  • “Objective-Driven Optimal Experimental Design: Quantifying the Uncertainties that Matter and Reducing Them Efficiently and Effectively”
    Invited seminar, Argonne National Laboratory, Laboratory for Applied Mathematics, Numerical Software, and Statistics (LANS), March 13, 2024.
  • “Leveraging AI/ML in Science to Enable Optimal Design and Accelerate Novel Discoveries”
    Invited seminar, Michigan Technological University, Mechanical Engineering-Engineering Mechanics Graduate Seminar, Oct. 12, 2023.
  • “Accelerating Scientific Discoveries Through Optimal Experimental Design and Machine Learning”
    Invited lecture, Computational Research Leadership Council (CRLC) Seminar Series, Morgan State University, Sep. 15, 2023.
  • “Accelerating Drug Discovery Through High-Throughput Virtual Screening and Generative Molecular Design”
    Invited seminar, Baylor College of Medicine, Department of Pharmacology and Chemical Biology, May 2, 2023.
  • “Accelerating Scientific Discoveries Through Optimal Experimental Design and Machine Learning”
    Invited lecture, Tennessee State University, Mar. 29, 2023.
  • “Multi-Objective Molecular Design Using Generative Models”
    Invited seminar, Baylor College of Medicine, Computational and Integrative Biomedical Research (CIBR) Center, Mar. 29, 2023.
  • “Machine Learning Strategies for Scaling Up Optimal Experimental Design”
    SIAM Conference on Computational Science and Engineering (CSE23), Amsterdam, Netherlands, Feb. 26 – March 3, 2023.
  • “Accelerating Scientific Discoveries Through Optimal Experimental Design and Machine Learning”
    Invited lecture, University of Washington, Department of Chemistry, Jan. 17, 2023.
  • “AI for enabling optimal design of complex systems”
    Invited Tech Talk, Korea-US Industrial Technology Cooperation Forum, Washington DC, Dec. 8, 2022.
  • “Accelerating Scientific Discoveries Through Optimal Experimental Design and Machine Learning”
    Invited lecture, Florida International University, Knight Foundation School of Computing and Information Sciences, Oct. 28, 2022.
  • “A Bayesian Framework for Objective-Based Uncertainty Quantification, Optimal Experimental Design, and Active Learning”
    Invited lecture, Department of Mathematics, Sungkyunkwan University (SKKU), July 29, 2022.
  • “Machine Learning for Complex Networks”
    Invited seminar, Sustainable Horizons Institute (SHI) Computational Research Leadership Council (CRLC) Seminar Series, Tufts University, July 21, 2022.
  • “Optimal Experimental Design and Active Learning Through Objective-Based Uncertainty Quantification”
    SIAM Conference on Uncertainty Quantification (UQ22), Atlanta, GA, USA, April 12 – 15, 2022.
  • “Machine Learning for Computational Network Biology”
    Invited lecture, IEEE EMBS BHI Technical and Educational Lecture Series, Dec. 15, 2021.
  • “Machine Learning for Complex Networks”
    Invited seminar, Sustainable Horizons Institute (SHI) Computational Research Leadership Council (CRLC) Seminar Series, Texas State University, Department of Computer Science, Oct. 29, 2021.
  • “Optimal experimental design for complex uncertain systems based on coupled ordinary differential equations”
    Invited talk, TAMIDS SciML Workshop, Oct. 26, 2021.
  • “Objective-Based Optimal Experimental Design for Materials Discovery”
    Invited talk, 1st Workshop on Materials Informatics in Xi’an (MIX) & 2nd Joint Xi’an Jiaotong University and Shanghai University Materials Genome Initiative Workshop, X’ian, China,, May 29-31, 2019.
  • “Machine Learning for Complex Networks”
    Invited seminar, Seoul National University, Big Data Institute, Seoul, Korea, February 18, 2019.
  • “Objective-Based Uncertainty Quantification and Optimal Experimental Design”
    Invited seminar, Brookhaven National Laboratory, Upton, NY, March 26, 2019.
  • “Probabilistic framework and efficient algorithms for comparative analysis of large-scale biological networks”
    Invited seminar, Hong Kong University of Science and Technology (HKUST), Department of Electronic & Computer Engineering, January 19, 2017.
  • “Optimal hybrid sequencing and assembly: Feasibility conditions for accurate genome reconstruction and cost minimization strategy”
    Paper presentation, 15th Asia Pacific Bioinformatics Conference (APBC 2017), Shenzhen, China, January 16-18, 2017.

Panel