Bio
Svetlozar (Zari) Todorov Rachev is a professor at Texas Tech University who specializes in mathematical finance, probability theory, and statistics. He is recognized for his significant contributions to probability metrics, derivative pricing, financial risk modeling, and econometrics. In the field of risk management, he is credited as the originator of the methodology behind FinAnalytica's flagship product which received several awards, including the "Best Market Risk Solution Provider" at the Waters Rankings in 2010, 2012, and 2015, and the "Most Innovative Specialist Vendor" at the Risk Awards in 2014. Rachev earned an MSc degree from the Faculty of Mathematics at Sofia University in 1974, a PhD degree from Lomonosov Moscow State University in 1979, and a Dr Sci degree from Steklov Mathematical Institute in 1986. Rachev's contributions to mathematical finance include his work on the application of non-Gaussian models for risk assessment, option pricing, and their applications in portfolio theory. He is also known for introducing a new risk-return ratio, the "Rachev Ratio," which measures the reward potential relative to tail risk in a non-Gaussian setting. In probability theory, Rachev's books on probability metrics and mass-transportation problems are widely cited. In the 2023 edition of the Research.com Ranking of Top Scientists in the field of Economics and Finance, Rachev was ranked 540 in the world and 364 in the United States. In the same edition, he was also ranked number 386 among the Best Mathematics Scientists in the world.

Bio
Dr. Ali Muqadas Jaffri, CFA, is an Assistant Professor of Practice in Finance at the College of Business, North Dakota State University (NDSU). He holds a Ph.D. in Economics from Texas Tech University, specializing in Financial Economics, and is a Chartered Financial Analyst (CFA) Charterholder. At NDSU, Dr. Jaffri teaches courses including Analysis of Fixed Income Securities, Advanced Data Analytics in Finance, and Advanced Bank Management, equipping students with analytical and applied skills to tackle complex financial challenges. Before joining academia, Dr. Jaffri built a strong foundation in the financial industry through leadership roles in risk management and financial institutions. He served as Associate Manager of Market Risk at Allied Bank and Manager of Financial Institutions Risk Management at MCB Bank Limited, where he specialized in market, credit, and operational risk frameworks and spearheaded the automation of regulatory reporting systems. Dr. Jaffri’s research and teaching approach integrates rigorous quantitative modeling, machine learning applications, and real-world financial practices. His published and ongoing works explore portfolio optimization, asset pricing, financial market volatility, geopolitical and environmental risk measurement, and advanced econometric and machine learning methods.

Bio
Dr. Hongwei Mei obtained his Ph.D. in Applied Mathematics in August 2016 from Wayne State University. He was a visiting assistant professor at the University of Central Florida (2016–2017) and the University of Kansas (2017–2020). Before joining TTU, he was a post-doc fellow at the Department of Statistics, Rice University. Dr. Mei is an applied probabilist, and his research interests include stochastic analysis, stochastic control and optimization, and optimal stopping. In those years, he published several papers in SICON, SPA, JDE, ESAIM-COCV, etc.

Bio
Ayush Jha is a PhD candidate in Economics at the Department of Economics at Texas Tech University. His research interests include financial economics, covering empirical asset pricing, modern portfolio theory, risk management, and topics in macro-finance, time series econometrics, and market microstructure. Ayush’s recent publications are featured in the Journal of Fixed Income, the Journal of Portfolio Management, and the Journal of Risk and Financial Management. He is also a co-author of several monographs covering Market Microstructure, Rational Asset Pricing, Behavioral Finance, and Financial Intermediation.