Assoc. Prof. Dr. Adnan Ozsoy | Computational Methods | Best Researcher Award

Assoc. Prof. Dr. Adnan Ozsoy | Computational Methods | Best Researcher Award

Hacettepe University | Turkey

Dr. Adnan Ozsoy is a computer engineering academic specializing in blockchain, cryptocurrencies, distributed systems, parallel computing, HPC, GPGPU technologies, and big data problems. He has led and contributed to multiple prestigious funded research projects covering efficient parallelization on GPUs, lattice-based cryptographic protocols, and NTRU-based cryptosystems. His current research focuses on blockchain applications across sectors such as health, land registry, digital identity, secure distributed storage, scalable microservices, high-rate message handling, voltage scaling on GPUs, data compression, SDR-based real-time signal detection, and sequence alignment. He has supervised numerous Ph.D. and M.S. theses in blockchain technologies, parallel and embedded systems, cryptography, and secure distributed computing. At Hacettepe University, he teaches core and advanced subjects including data structures, algorithms, parallel programming, and blockchain, and has pioneered Turkey’s first undergraduate and graduate blockchain course. His professional engagements include consultancy at NETGSM on big data architecture, cloud and container technologies, microservices, scalability challenges, and academic R&D outcomes. His career is further supported by several major international and national awards, invitations for seminars and trainings, and industry collaborations in GPU computing and blockchain technologies.

Erdogan, H. T., & Ozsoy, A. (2025). CUDA-supported 5G multi-access edge computing modifications on 5G-air-simulator. EURASIP Journal on Wireless Communications and Networking, 2025(1), 29.

Ozsoy, A., Nazli, M., Cankur, O., & Sahin, C. (2025). CUSMART: Effective parallelization of string matching algorithms using GPGPU accelerators. Frontiers of Information Technology & Electronic Engineering, 26(6), 877–895.

Cihan, S., Yılmaz, N., Ozsoy, A., & Beyan, O. D. (2025). A systematic review of the blockchain application in healthcare research domain: Toward a unified conceptual model. Medical & Biological Engineering & Computing, 63(5), 1319–1342.

Zorlu, O., & Ozsoy, A. (2024). A blockchain-based secure framework for data management. IET Communications, 18(10), 628–653.

Fisne, A., Kalay, A., Yavuz, F., Cetintepe, C., & Ozsoy, A. (2023). Energy-efficient computing for machine learning based target detection. Concurrency and Computation: Practice and Experience, 35(24), e7582.

Assist. Prof. Dr. I-Ming Jiang | Dynamic Stochastic Processes | Best Researcher Award

Assist. Prof. Dr. I-Ming Jiang | Dynamic Stochastic Processes | Best Researcher Award

Yuan Ze University | Taiwan

Dr. I-Ming Jiang is an Assistant Professor in the College of Management at Yuan Ze University, specializing in financial engineering, risk management, big-data statistical applications, real options, and empirical financial studies. His work also covers asset pricing in incomplete markets and the use of artificial intelligence in trading systems and technical analysis. He teaches courses such as calculus, financial innovation, risk management, quantitative and computing methods, and money and banking. He has held multiple academic appointments in finance and has published 29 research works. His current research focuses on computational methods and dynamic stochastic processes.

Featured Publications

Huishui Su, Jiang, I.-M., & Liu, D. (2025). Detecting financial fraud risk using machine learning: Evidence based on different categories and matching samples. Finance Research Letters, 85(Part A), 107858.

Liu, Y.-H., Jiang, I.-M., & Hung, M.-W. (2025). Pricing vulnerable options when debts have performance-sensitivity provisions. International Review of Economics and Finance.

Johannes Krotz | Computational Methods | Best Researcher Award

Dr. Johannes Krotz | Computational Methods | Best Researcher Award

Postdoctoral Fellow at Notre Dame, United States

👨‍🎓 Profiles

🌟Summary

👨‍🎓 PhD candidate in Mathematics with a minor in Computer Science, specializing in probabilistic and data-driven methods for numerical PDEs and hybrid Monte Carlo methods for complex systems simulations. Experienced in statistical modeling, computational physics, and advanced simulations with a strong background in teaching and academic leadership. Currently working as a Postdoctoral Researcher at the University of Notre Dame.

🎓 Education

🎓 PhD in Mathematics (Minor in CS)
University of Tennessee Knoxville, 2021–2024

  • Dissertation on Probabilistic & Data-Driven Methods in Numerical PDEs
  • GPA: 4.0

📊 M.Sc. in Statistics
University of Tennessee, 2022–2024

  • GPA: 3.9

📚 M.Sc. in Mathematics
Oregon State University, 2019–2021

  • GPA: 4.0

⚛️ M.Sc. in Physics
University of Konstanz, 2015–2019

  • GPA: 4.0 (Honors)

🔢 B.Sc. in Mathematics & Physics
University of Konstanz, 2012–2018

  • GPA: 3.5 (Mathematics), 3.3 (Physics)

💼 Professional Experience

🔬 Postdoctoral Researcher
University of Notre Dame, 2024–Present

  • Research on hybrid Monte Carlo & deterministic kinetic transport algorithms for exascale simulations in neutron transport.

🧑‍💻 Graduate Research Assistant (GRA)
University of Tennessee/ORNL, 2023–2024

  • Advancing dynamic likelihood filters for stochastic advection-diffusion equations in collaboration with ORNL and UTK.

💼 Research Intern
Oak Ridge National Lab (ORNL), 2021–2022

  • Developed hybrid algorithms for simulating complex particle systems in 2D & 3D.

🌍 Research Intern
Los Alamos National Lab (LANL), 2020

  • Focus on high-fidelity discrete fracture networks and Poisson-disk sampling algorithms for triangulations.

🔬 Research Interests

  • 🧠 Computational Mathematics: Hybrid Monte Carlo methods, kinetic transport equations, and numerical simulations for complex physical systems.
  • 🔍 Stochastic Processes: Advanced data-driven filtering techniques and applications in fluid dynamics, advection-diffusion, and PDEs.
  • 💻 Statistical Modeling: Development of methods for high-dimensional data and stochastic modeling.
  • 🌐 Interdisciplinary Work: Collaborating across fields of mathematics, physics, and engineering to tackle real-world computational challenges.

🏆 Awards

  • 1st & 3rd place at the UTK SIAM Research Showcase (2023, 2024)
  • Randall E. Cline Award (2022) for research excellence

🖥 Technical Skills

  • Python, C++, R, Matlab, LATEX, and more
  • Basic Fortran, AWK

🔗 Professional Memberships

  • SIAM, AWM, AAAS, UCW

 Publications

A Hybrid Monte Carlo, Discontinuous Galerkin Method for Linear Kinetic Transport Equations

  • Authors: Johannes Krotz, Cory D. Hauck, Ryan G. McClarren
  • Journal: Journal of Computational Physics, Vol. 514
  • Year: 2024
Variable Resolution Poisson-Disk Sampling for Meshing Discrete Fracture Networks
  • Authors: Johannes Krotz, Matthew R. Sweeney, Jeffrey D. Hyman, Juan M. Restrepo, Carl W. Gable
  • Journal: Journal of Computational and Applied Mathematics, Vol. 407
  • Year: 2022
Dynamic Likelihood Filters for Advection Diffusion Equations
  • Authors: Johannes Krotz, Jorge M. Ramires, Juan M. Restrepo
  • Journal: The Monthly Weather Review
  • Year: Under review
Minimizing Effects of the Kalman Gain on Posterior Covariance Eigenvalues, the Characteristic Polynomial and Symmetric Polynomials of Eigenvalues
  • Authors: Johannes Krotz
  • Journal: Arxiv (preprint)
  • Year: 2024