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David Han

Romo Endowed Professor, Associate Professor of Management Science and Statistics, Honors College

David Han

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Bio

Languages: English, Korean

Website: https://business.utsa.edu/faculty/profiles/han-david.html

Mesmerized by the incredible possibilities of biotechnology and genetic engineering since I was just a kid (not inspired by a zombie movie), I pursued my undergraduate degree in Honors B.Sc. in biochemistry with a specialization in biotechnology and genetic engineering at McMaster University in Canada. But my curiosity didn’t stop there. Soon, fascinated by the computational and algorithmic analyses applied to traditional bio and chemical sciences, I became eager to explore the field of bioinformatics, for which I also earned another Honors B.Sc. in computer science with a minor in business. During this time, I was exposed to the world of quantitative sciences with very different perspectives and thought processes. It was truly an eye-opening experience (transformative indeed) and ignited my desire to learn more! Traveling across various academic disciplines and fields (science, engineering, business, medicine, education, etc.) helped satisfy my deeper philosophical hunger. Soon, I realized that there have always been statistical concepts and analyses at the core of any knowledge discovery process (and innovations!). These have always been the way we (humans) understand everything around us and perceive the universe. So, I continued my education at McMaster to earn a Master of Science and Doctor of Philosophy in statistics, which now forms the foundations of analytics, data science, machine learning, AI, etc. Over 15 years of my teaching and research at UTSA, my passion for data science grew even bigger as my  belief got continuously confirmed (now I am looking for something beyond).
The journey to complete my education was never easy, though. There were many obstacles I had to face and challenges I had to overcome. Along the way, I worked as a store cashier, dishwasher, assistant cook, cafeteria supervisor, summer camp chaperone, computer lab print operator, pharmacy assistant, research lab assistant, teaching assistant, math and science tutor, teacher in a local school district, etc. Guess what? It was all a part of my learning experience! I am a lifelong learner and will be your friendly guide to the world of data science, empowering you to explore the endless possibilities it offers. I strive to be more than just an instructor. Appreciating a spectrum of diverse viewpoints (both Western and Eastern), I am dedicated to creating an inclusive and supportive learning environment. I hope to continue learning and growing, fostering my love for education in every student. Fun fact about me? I am an origami enthusiast, a taekwondo (Korean martial art) student, and a karaoke lover (not a good singer though HAHA).
Research Interest

My main research interests include statistical modeling, data science and analytics, operations research in the areas of reliability, survival analysis, lifetime and degradation analyses, predictive maintenance planning with applications to healthcare, biomedicine, chemometrics, cybersecurity, renewable energy, industrial engineering and beyond. My work has appeared in numerous peer-reviewed journals such as IEEE Transactions on Reliability, Reliability Engineering & System Safety, Naval Research Logistics, Quality and Reliability Engineering International, Chemometrics & Intelligent Laboratory Systems, Quality Engineering, Computational Statistics & Data Analysis, Journal of Statistical Planning & Inference, Communications in Statistics, PLoS ONE, and others. Below is a list of my selected publications.

  • Book on  Fiber Bundles: Statistical Models and Applications, with Gleaton, Lynch, Ng, and Ruggeri, SpringerBriefs: Emerging Topics in Statistics and Biostatistics, 2023.

  • “Bayesian point and interval estimation for step-stress accelerated life tests under order restriction,” with C. Wiedner,  Procedia Manufacturing, Vol. 55, 2021, pp. 147-153.

  • “Parameter Estimation using EM Algorithm for Lifetimes from Step-stress and Constant-stress Accelerated Life Tests with Interval Monitoring,” with T. Bai,  IEEE Transactions on Reliability, Vol. 70, 2021, pp. 49-64.

  • “Optimal Design of a Simple Step-stress Accelerated Life Test under Progressive Type-I Censoring with Non-uniform Durations: Comparison between Continuous and Interval inspections,” with T. Bai,  Reliability Engineering & System Safety, Vol. 199, 2021, e106875.

  • “On the Existence of the Optimal Step-stress Accelerated Life Tests under Progressive Type-I Censoring,”  IEEE Transactions on Reliability, Vol. 69, 2020, pp. 903-915.

  • “Expected Termination Times of Progressively Type-I Censored Step-stress Accelerated Life Tests under Continuous and Interval Inspections,”  Statistica Neerlandica, Vol. 74, 2019, pp. 112-124.

  • “Optimal Design of a Simple Step-stress Accelerated Life Test under Progressive Type-I Censoring with Non-uniform Durations for Exponential Lifetimes,”  Quality and Reliability Engineering International, Vol. 35, 2019, pp. 1297-1312.

  • “Bayesian Estimation of the Analyte Concentrations using the Sensor Responses and the Design Optimization of a Sensor System,” with K. Johnson,  Chemometrics & Intelligent Laboratory Systems, Vol. 176, 2018, pp. 149-156.

  • “Optimal Accelerated Life Tests under a Cost Constraint with Non-uniform Stress Durations,”  Quality Engineering, Vol. 29, 2017, pp. 409-430.

  • “Time and Cost Constrained Optimal Designs of Constant-stress and Step-stress Accelerated Life Tests,”  Reliability Engineering & System Safety, Vol. 140, 2015, pp. 1-14.

  • “Inference for a Step-stress Model with Competing Risks from the Generalized Exponential Distribution under Type-I Censoring,” with D. Kundu,  IEEE Transactions on Reliability, Vol. 64, 2015, pp. 31-43.

  • “Estimation in Step-stress Life Tests with Complementary Risks from the Exponentiated Exponential Distribution under Time Constraint and Its Applications to UAV Data,”  Statistical Methodology, Vol. 23, 2015, pp. 103-122.

  • “Comparison between Constant-stress and Step-stress Accelerated Life Tests under Time Constraint,” with H.K.T. Ng,  Naval Research Logistics, Vol. 60, 2013, pp. 541-556.

  • “Exact Inference for Progressively Type-I Censored Exponential Failure Data,” with N. Balakrishnan and G. Iliopoulos,  Metrika, Vol. 73, 2011, pp. 335-358.

  • “Inference for a Simple Step-stress Model with Competing Risks for Failure from the Exponential Distribution under Time Constraint,” with N. Balakrishnan,  Computational Statistics & Data Analysis, Vol. 54, 2010, pp. 2066-2081.

  • “Optimal Step-stress Testing for Progressively Type-I Censored Data from Exponential Distribution,” with N. Balakrishnan,  Journal of Statistical Planning & Inference, Vol. 139, 2009, pp. 1782-1798.

  • “Exact Inference for a Simple Step-stress Model with Competing Risks for Failure from Exponential Distribution under Type-II Censoring,” with N. Balakrishnan,  Journal of Statistical Planning & Inference, Vol. 138, 2008, pp. 4172-4186.

Recognized for the teaching and research excellence, I have received the University of Texas System Regents’ Outstanding Teaching Award (the highest teaching award in the University of Texas System), the UTSA President’s Distinguished Achievement Award for Teaching Excellence, the UTSA Distinguished Teaching Professorship, the Carlos Alvarez College of Business Faculty Leadership Fellowship, the Carlos Alvarez College of Business Faculty Teaching Excellence Award and the Carlos Alvarez College of Business Dean’s Research Excellence Award. I am a member of the UTSA Academy of Distinguished Teaching Scholars and have been serving on numerous committees as well as actively serving as the president and vice president of the American Statistical Association chapter. In addition, I have been serving as an editorial board member and peer reviewer for numerous academic journals in broad and diverse disciplines. I am here for everyone to realize and unleash the power of data!

Teaching Interest

I have taught physical and statistical/mathematical sciences over 23 years from the grade school to the undergraduate, graduate and doctoral levels. My teaching interest includes anything and everything about statistics, data science, analytics, data mining, machine learning, neural networks, artificial intelligence in addition to probability and mathematical statistics, applied statistics, business statistics, engineering statistics, biostatistics and survival analysis. Being a part of the UTSA family, I cherish every opportunity to contribute to the academic journey of our students as I see teaching as a shared adventure, a collaborative exploration of knowledge.

Favorite thing about working in the Honors College: This is no brainer. Our wonderful students, of course, who are here “to explore strange new worlds and to boldly go where no man has gone before!”

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