Petter Kolm is a Professor at Miami Herbert Business School, University of Miami. He was previously a Professor at NYU Courant where he directed the Mathematics in Finance Master’s program. In 2021, he was honored as “Quant of the Year” by Portfolio Management Research and the Journal of Portfolio Management for his significant contributions to quantitative portfolio theory. In 2026, he was named “Buy-Side Quant of the Year” by Risk.net.

He has co-authored numerous influential articles and books on quantitative finance, portfolio management, and financial data science. Petter serves on several company advisory boards; editorial boards for leading academic journals; and boards of directors for professional associations. Previously, he worked in Quantitative Strategies at Goldman Sachs Asset Management.

As a consultant and expert witness, Petter provides expertise in machine learning, portfolio management, risk management, and systematic trading. He earned his Ph.D. in Mathematics from Yale University, an M.Phil. in Applied Mathematics from the Royal Institute of Technology (KTH), and an M.S. in Mathematics from ETH Zurich.

Hariom has years of experience bridging AI, machine learning, quantitative techniques, and finance. He is an O’Reilly author and published researcher, with multiple research contributions in AI, machine learning, and mechanistic interpretability, particularly focused on making large language models more transparent and reliable in financial and agentic AI settings. He has been a featured speaker at several conferences and industry forums and received the Indian Achiever Award in Machine Learning. He completed his MS at UC Berkeley and his BE at IIT (India).

Yuyu Fan is a Senior Vice President and Director of AI Research on the Data Science team at AB, where she leads the development and implementation of advanced artificial intelligence (AI) and machine learning (ML) models to meet critical business needs. Fan collaborates with various business units within the firm to transform business requirements into data-driven solutions. For instance, she leverages AI to generate investment signals for portfolio managers and partners with the Client team to create models that optimize sales processes. Prior to joining the firm in 2018, Fan worked at the College Board as a psychometrician intern for two years, using ML models to monitor test validity, reliability and security. She holds a BA in sociology from Zhejiang University (Hangzhou, China), MAs in sociology and psychology from Fordham University, and a PhD in psychometrics and quantitative psychology from Fordham University. Location: New York.

Jörg is a Quantitative Finance professional for more than 25 years. After holding positions as Head of Quant with Postbannk/Deutsche Bank, Deloitte or LSEG, he is now Director of Quantiative Methods at mrig, a Frankfurt based consultancy. He also works as an adjunct associate professor at UCT, Cape Town, and as an assistant professor at BUW, Wuppertal. Jörg is frequently speaking on conferences, (co-) authored four books with Wiley and Springer and published many research and practiitioners papers in Quantitätive Finance, Journal of Computational Finance, RISK or Wilmott.

Tony Guida is a Quantitative Portfolio Manager, researcher, and author with expertise in systematic investing, machine learning, and financial data science. He currently works on the integration of large language models (LLMs) and knowledge graphs into investment processes for a Swiss asset manager.

Tony began his career at Unigestion in 2006, joining the quantitative equity team as a research analyst. He later became a member of the Research and Investment Committee for Minimum Variance Strategies, where he led the factor investing research group for institutional clients. In 2015, he joined EDHEC-Risk Scientific Beta as a Senior Consultant, focusing on risk allocation and multi-factor strategies. In 2016, Tony moved to a major UK pension fund, where he built an in-house systematic equity strategy and co-managed a £8 billion portfolio as Senior Quantitative Portfolio Manager.

In 2019, he joined RAM Active Investments as a Senior Quantitative Researcher in equities, later co-heading the systematic macro hedge fund offering. In 2023, Tony co-founded a hedge fund, where he served as Co-Head of Research and Portfolio Manager, leading the development of cross-asset, machine learning-driven investment strategies.

Tony holds Bachelor’s and Master’s degrees in Econometrics, and a Master’s in Economics and Finance. He has authored and edited several industry-leading books, including:

• Big Data and Machine Learning in Quantitative Investment (Wiley, 2018)
• Machine Learning for Factor Investing: R Version (CRC, 2020)
• Machine Learning for Factor Investing: Python Version (CRC, 2023)

He is also an Advisory Board Member for the Financial Data Professional Institute and serves as a peer reviewer for academic journals in machine learning and finance.

Lorenc Kapllani is a Senior Quantitative Finance & Machine Learning Consultant at mrig, a Frankfurt-based consultancy specializing in quantitative finance. Prior to joining mrig, he worked as a Credit Risk Analyst at GEFA Bank in Germany.

He holds a PhD in Applied Mathematics from the University of Wuppertal, where his research focused on deep-learning methods for pricing high-dimensional nonlinear derivatives, risk management, and uncertainty quantification — published across peer-reviewed papers in journals including the IMA Journal of Numerical Analysis.

Alongside his industry role, he continues to research at the intersection of quantitative finance and machine learning.

After a lectureship in mathematics and statistics at the Economic Academy Kiel, Gunter Meissner PhD, joined Deutsche Bank in 1990, trading interest rate futures, swaps, and options in Frankfurt and New York. He became Head of Product Development in 1994, responsible for originating algorithms for new derivatives products, which at the time were Lookback Options, Multi-asset Options, Quanto Options, Average Options, Index Amortizing Swaps, and Bermuda Swaptions. In 1995/1996 Gunter Meissner was Head of Options at Deutsche Bank Tokyo. From 1997 to 2007, Gunter was Professor of Finance at Hawaii Pacific University and from 2008 to 2013 Director of the Master in Financial Engineering Program at the University of Hawaii. Currently, he is President of Derivatives Software (www.dersoft.com), Adjunct Professor of Mathematical Finance at Columbia University and NYU, and Executive Research Director at Bhodi research group, www.Bodhiresearchgroup.com.

Gunter Meissner has published numerous papers and seven books on financial derivatives, risk management, and statistics. His new book “AI Applications in Finance – Opportunities and Limitations” will be published in fall 2026. Gunter can be reached at meissner@hawaii.edu. His CV is at www.dersoft.com/cv.pdf.