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).

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.

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.