Biography
Computer Engineering Professor & former Chair Liwen Shih, Ph.D. of U. of Houston – Clear Lake specializes in smart Quantum AI HPC Synergy Optimization. Professor Shih regularly teaches Quantum AI, Quantum Computing, Bio-Inspired AI, ANN, HPC Architecture, Heterogeneous QPU/GPU/FPGA/NPU/TPU Computing, and Capstone Research Projects. Pioneering Q<=>AI Duality for Discovery, Professor Shih is dedicated to meet AI's hunger by tackling the time/energy/data/discovery walls toward AGI. With unique topology-aware HPC workload scheduling, Dr. Shih helped speed up world’s fastest & largest CyberShake Earthquake Map computation 35% faster. With many awards & recognitions, Dr. Shih has been a Visiting Research Affiliate with Lawrence Berkeley National Lab & Oak Ridge National Lab on QAI^HPC, an XSEDE Campus Champion & nation's inaugural XSEDE CC Fellow for CyberShake with SDSC/SCEC/NCSA, Fulbright Computer Specialist, and Lekkos & Barrios Endowment Research Faculty Fellows. Dr. Shih holds a Ph.D. in Computer Engineering & Science from Case Western Reserve U. and first B.S. In Computer Engineering from National Chiao-Tung U., whose alumni serves 70% of Taiwan’s high tech CEOs/managers. Dr. Shih is a global prestigious Keynote Speaker: Georgia, India (7 times), Bulgaria, Germany, Thailand, Hong Kong, DC-Warsaw-Toronto, Dallas, Houston, South Africa, Oklahoma, Japan, DoE PNNL, Turkey, China, NASA (twice)…
Degrees Earned
PhD / Computer Engineering & Science / 1989 Case Western Reserve U. BS / Computer engineering / 1983 National Chiao-Tung U., whose alumni serves 70% of Taiwan’s high tech CEOs/managers.
Research Areas
Computer Science; Data Science; Machine Learning/AI; other
Research Interests
Quantum AI HPC synergy to meet intelligent computing demands of Energy/Data/Discovery toward AGI, especially passionate about Proactive Health/Environment applications. Q AI HPC synergy innovation research including: 1. QAI^HPC topology-aware HPC workflow scheduling optimization, 2. Q<=>AI Duality to use AI to discover concept/model/objective-function, and to use concept model to quantum generate/synthesize sample data for improving AI/ML robustness & accuracy. 3. QGenerativeAI, QStableDiffusion - augment data set with QA random sampling or error or near misses to better predict effect with increased learning accuracy. 4. QAI Machine Teaching – QA Generate Teaching Set from Augmenting/Perturb Seed ANN Learning Set. 5. QQuickProp/QGradientDecent: quick ideal weight approximation. 6. Designing & establish a new QAI Solution & Training Hub to apply Quantum AI Optimization to our area Space/Energy/Biomed/Eco/Logistic/Port/Transportation industry operations.
Topical Areas
Agriculture, Forestry, and Fisheries; Applied Computer Science; Applied Mathematics; Artificial Intelligence and Intelligent Systems; Astronomy and Planetary Sciences; Computer Science; Ecology; Economics and Business; Educational Sciences; Electrical, Electronic, and Information Engineering; Environmental Engineering; Health Sciences; Informatics, Analytics and Information Science; Materials Engineering; Medical Engineering; Other Computer and Information Sciences; Other Earth and Environmental Sciences; Other Engineering and Technologies; Particle and High-Energy Physics; Performance Evaluation and Benchmarking; Statistics and Probability; Training; Organization
Research Synergy
Q <=> AI Duality for Model/Theory/Data Discovery for auto solution optimization for any application problems in all areas, e.g., Quantum Boltzmann Machine, Recommender System with example seed data set or seed solutions without human manual problem analysis to create objective QUBO functions automatically, and to sample/generate alternative solutions. QAI^HPC Topology-Aware QAI optimized HPC Workflow Scheduling to cut cost/energy/time/network-traffic for mapping most any HPC applications on HPC clusters or Qubit network topology.
Motivation
1. Devote our innovations to Harness QAI Optimization techniques for Discovery/Data/Energy Sustainability. 2. Learn the latest Q AI HPC to prepare & train QAI workforce. 3. Establish a local QAI solution/Training hub to enhance community biomed/energy/space/port/logistic/transportation industry operations. 4. Create & lead a NSF CaRCC QAI interest group for exchange (Campus Research Computing Consortium). 5. Serve as QAI Science Advisory Committee for U of Houston system. 6. Contribute to National AI, National Quantum & Texas Quantum Initiatives. 7. Answer nation's call on Executive Order on Q AI Priority.
Supervising Students Plan
Student team will learn, brainstorm & develop knowledge/skill/codes to run examples to demonstrate concepts & prototypes of our innovation design. I have extensive mentoring experience, where my students won top global honors in competitions such as Intel Science & Engineer fair. In ISC22 conference, our students presented 2 of the global 18 research posters. Our MS. Computer Engineering students also got best poster awards with cash prizes in NASA conferences & world's largest Texas Medical Center, beating all other post doc researchers,
Student Merit
Students Yusra & Brandon are very motivated undergraduates and doing well in courses. Very impressed that both approached me to express interests in my computer engineering Q AI HPC research form their Computer Information System & Computation Physics majors. Yusra led multidisciplinary teams in NASA’s L’SPACE programs for space mission, and actively participate in a local robotics club and university IEEE, Cybersecurity, & Rocket club. Brandon has done a couple of summer REUs at prestigious Rice University.
Lightning Talk Title
Q<=>AI Duality for Discovery
Keywords
QAI HPC Synergy => Energy/Data/Speed/Discovery 1. QAI^HPC Workflow Scheduling; 2. Q<=>AI Duality => Discover Theory/Constraints/Model; 3. Q^GenerativeAI/Q^StableDiffusion; 4. Q^BM/Q^AI/Q^ML; 5. Q^QuickProp/Q^GradientDecent; 6. QAI Solution/Training Hub: Space/Energy/Biomed/Eco/Logistic/Port/Transportation.