Hans Josef Pesch | Mathematics | Trailblazing Popular Scientist Award

Prof. Dr. Hans Josef Pesch | Mathematics | Trailblazing Popular Scientist Award

University of Bayreuth Germany

Prof. Dr. Hans Josef Pesch is a distinguished mathematician specializing in numerical analysis and optimal control. Born on August 1, 1949, in Dormagen, Germany, he has significantly contributed to computational mathematics in science and engineering. With a career spanning several prestigious institutions, he served as Chair of Mathematics in Engineering Sciences at the University of Bayreuth until his retirement in 2015. Currently, he is a Professor Emeritus, continuing his academic influence in optimization and applied mathematics.

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Education 🎓

Prof. Pesch pursued his studies in Mathematics and Physics at the University of Cologne (1968–1974), earning a Diploma in Mathematics in 1974. He completed his Doctorate (Dr.rer.nat.) in 1978 at Munich University of Technology, followed by a Habilitation (Dr.rer.nat.habil.) in 1986. His early education included classical training in Latin and Greek, reflecting a strong foundation in analytical and logical reasoning.

Experience 🏛️

With a vast academic career, Prof. Pesch has held multiple prestigious positions:

  • University of Bayreuth (1999–2015): Full Professor and Chair of Mathematics in Engineering Sciences.

  • Clausthal University of Technology (1995–1999): Full Professor for Numerical Analysis and Scientific Computing.

  • Munich University of Technology (1989–1995): Associate Professor.

  • University of California, San Diego (1987): Visiting Professor.

  • University of the Armed Forces, Munich (1988–1989): Associate Professor.
    Throughout his tenure, he led Ph.D. programs, supervised over 170 master’s theses, 35 Ph.D. theses, and mentored postdoctoral researchers.

Research Interests 🔬

Prof. Pesch’s research revolves around optimal control theory, numerical analysis, and computational mathematics. He has worked extensively on real-time optimization, industrial process modeling, and optimal control of engineering systems. His contributions include applications in robotics, welding processes, fuel cell systems, and vehicle dynamics, impacting both academia and industry.

Awards & Honors 🏆

  • Recognition for his contributions to computational mathematics and optimal control.

  • Funding from prestigious institutions like the German National Science Foundation (GNSF), European Science Foundation (ESF), and the German Ministry of Research and Technology (BMBF).

  • Leadership roles in major doctoral programs and research networks.

Publications Top Notes: 📚

Prof. Pesch has authored two monographs, over 95 journal publications, and numerous conference papers. His work is widely cited, influencing advancements in mathematical optimization. Some of his key publications include:

Numerical treatment of delay differential equations by Hermite interpolation

Abort landing in the presence of windshear as a minimax optimal control problem, part 2: Multiple shooting and homotopy

Real‐time computation of feedback controls for constrained optimal control problems. part 1: Neighbouring extremals

Real‐time computation of feedback controls for constrained optimal control problems. part 2: A correction method based on multiple shooting

Abort landing in the presence of windshear as a minimax optimal control problem, part 1: Necessary conditions

Combining direct and indirect methods in optimal control: Range maximization of a hang glider

Complex differential games of pursuit-evasion type with state constraints, part 1: Necessary conditions for optimal open-loop strategies

The maximum principle of optimal control: a history of ingenious ideas and missed opportunities

A modified continuation method for the numerical solution of nonlinear two-point boundary value problems by shooting techniques

Comparing routines for the numerical solution of initial value problems of ordinary differential equations in multiple shooting

Shaohua Xu | Mathematics | Best Researcher Award

Mr. Shaohua Xu | Mathematics | Best Researcher Award

PhD candidate Nankai University China

Shaohua Xu is a Ph.D. candidate in Statistics at Nankai University, China. With a strong foundation in statistical methodologies and robust experimental designs, he excels in advancing subsampling techniques and online control experiments. His work reflects a dedication to innovative solutions for complex statistical challenges.

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Education 🎓

  • Ph.D. in Statistics (2019–2025*, Advisor: Prof. Yongdao Zhou)
    • Nankai University, Tianjin, China
  • B.S. in Statistics (2015–2019, Advisor: Assoc. Prof. Benchong Li)
    • Xidian University, Xi’an, China

Experience 🛠️

Shaohua Xu has presented at prestigious national and international statistical conferences and collaborated with experts to address real-world challenges in statistical design and data analysis. He also contributes through teaching assistance and mentoring at Nankai University.

Research Interests 🔍

  • Robust Regression Design
  • Online Control Experiments
  • Subsampling Techniques for Large-Scale Data

Awards & Honors 🏆

  • 2024: Poster Award, International Chinese Statistical Association China Conference
  • 2023: Best Paper Award, 2nd International Workshop on Statistical Theory and Related Fields
  • 2023: Zhong Jiaqing Outstanding Paper Award, 24th Beijing-Tianjin-Hebei Young Scholars Symposium
  • 2023: Second Prize, Academic Symposium on Uniform Design, Chinese Mathematical Society
  • 2020 & 2022: Gongneng Scholarship, Nankai University
  • 2018: National Scholarship & SAS China Analytics Championship Top 40

Publications Top Notes:📚

Xu, Shaohua, Liu, S., & Zhou, Y. (2024). MODE: Minimax Optimal Deterministic Experiments for Causal Inference in the Presence of Covariates. Entropy, 26(12), 1023. Link

Xu, Shaohua & Zhou, Y. (2024). Robust control experiments for multivariate tests with covariates and network information. Under review in Statistica Sinica.

Xu, Shaohua & Zhou, Y. (2024). Minimax designs for partially linear models. Under review in Journal of Statistical Planning and Inference.

Yang, J., Xu, Shaohua, Yang, Z., Zhang, A., & Zhou, Y. (2024). Stable subsampling under model misspecification and dataset shift. Under review in ACM Transactions on Knowledge Discovery from Data.

Xu, Shaohua, Zhou, Y., & Zhou, Z. (2024). Minimax designs for misspecified linear models. Submitted to Annals of Statistics.