Top Questions: QuantVision 2025 (Fordham’s Quantitative Conference & Data Summit)

Rebellion Research CEO Alexander Fleiss and his team have put together another all-star lineup at Fordham University on May 22nd. Here’s my questions for the speakers and panelists

On May 22nd, 2025, Fordham University hosts QuantVision 2025, a conference by Rebellion Research.

To help the data community prepare, I've created targeted questions for each speaker and panel. There are 3 key themes to my questions:

1. Strategic Adaptability to Market and Macro Shifts

2. Human-Machine Collaboration in the Quant Workflow

3. Infrastructure, Access, and Scalability of Data & Models

https://www.rebellionresearch.com/quantvision-2025-fordhams-quantitative-conference

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Welcome to the Data Score newsletter, composed by DataChorus LLC. This newsletter is your source for insights into data-driven decision-making. Whether you're an insight seeker, a unique data company, a software-as-a-service provider, or an investor, this newsletter is for you. I'm Jason DeRise, a seasoned expert in the field of data-driven insights. I was at the forefront of pioneering new ways to generate actionable insights from alternative data. Before that, I successfully built a sell-side equity research franchise based on proprietary data and non-consensus insights. I remain active in the intersection of data, technology, and financial insights. Through my extensive experience as a purchaser and creator of data, I have a unique perspective, which I am sharing through the newsletter.

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Note: Agenda as of May 17, 2025

08.45 – Opening Address from the Chairs

• Director, MSQF Fordham Director, Professor Qing Sheng,

• Conference Co-Chair Faruque Khan

• Conference Co-Chair Rebellion Research CEO, Alexander Fleiss

Question: How do you see Fordham’s MSQF program evolving its curriculum to integrate real-world AI-for-finance research in partnership with Rebellion Research to better equip graduates for production-level quant roles?

08.50 – Opening Fireside Chat

• Tony Berkman, MD Two Sigma

• Claudia Perlich, MD Two Sigma

Question: Given the pace of technological and data-driven change in markets over the past 15 years, what themes do you expect we’ll be discussing at QuantVision 2040?

09.20 – PANEL DISCUSSION: The Investment Process

• Moderator: Sean Slotterback, Quant Portfolio Manager

• Daniel DeWoskin, Quantitative Research Manager at Graham Capital Management,

• Rahul Gupta, Quant Research and Trading, DRW,

• Zach Squire, Portfolio Manager, Brevan Howard Tekmerion,

• Neal Berger, Hedge Fund Manager,

• Patrick Hop, Chief Investment Officer, Draco Ova Holdings,

• Yosef Zweibach, Chief Operating Officer of Quantic/Walleye Capital

Question: Thinking about uncertainty related to sudden volatility spikes and regime shifts, which systematic signal-management tactics have proven most resilient across your firms?

9:55 – Financial Mathematics or Financial Physics?

• Dr. Peter Cotton

• Dr. Igor Halperin

• Moderated by: Francesco Fabozzi, Research Director of Yale’s International Center of Finance

Question: How do financial mathematics and financial physics differ in managing uncertainty, especially with sparse, noisy, or regime-shifting data? How do your models handle feedback loops where their signals affect market behavior? Can these two approaches reinforce, rather than contradict, each other?

10:25 – Keynote: The Best US Corporate Bond Pricing Model is Deep Learning

• Nathaniel Powell, Deep Market Making, CEO & Fmr Director of Machine Learning Research, JPMorgan

Question: Given the infrequent trading of many corporate bonds, how do you meet market makers' demands for real-time fair-value estimates? Which ML models and strategies have best supported low-latency pricing in live trading workflows?

11.05 – PANEL DISCUSSION : Capturing Alpha & Quantitative Strategies & Global Outlook

• Moderator: Lisa Schirf, MD, Global Head of Data & Analytics, Tradeweb

• Dr. Sudip Gupta, Professor Johns Hopkins University Carey Business School,

• Dr. Argyro (Iro) Tasitsiomi, Head of Investments Data Science at T. Rowe Price,

• Caio Natividade, Global Head Quantitative Investment Solutions Deutsche Bank,

• Jonathan Larkin, Managing Director, Columbia Investment Management Company,

• Paul Krueger, Quant Trader @ Millenium

Question: Assuming ongoing political populism, protectionism, and AI-driven disruption of business models, how should quant strategies adapt to sustain alpha generation?

11.40 – Keynote: Generative AI for Modeling Stock Returns

• Samson Qian, Citadel

Question: In a world where fundamental analysts can “vibe-quant-code” backtested models and implement them leveraging Gen AI co-pilots, how do traditional quant researchers add value? Is it an opportunity or a risk?

1.00 – Keynote Speech: Is There Any Possibility of Cross-Functionality Between Digital Tokens and Tokens Used in Deep Learning?

• Albert An, CEO of Tower Research Capital

Question: How can we reframe market participants’ “jobs to be done” in a way that unlocks new opportunities for cross-functionality between digital and machine-learning tokens?

1.30 – PANEL DISCUSSION: Understanding The Future of Machine Learning in Quantitative Finance

• Moderator: Petter Kolm, NYU Professor & Director of NYU Mathematics in Finance

• Jae Ho Kim, PhD, Head of Portfolio Research, Cubist; Division of Point72,

• *V. Zach Golkhou, Ph.D., Director of GenAI & Data Science, JP Morgan,*

• *Dimitri Bianco, Head of Quant Risk & Research Agora Data,*

• *Arun Verma, Head of Quantitative Research Solutions at Bloomberg, LP,*

• *JD Opdyke, Chief Analytics Officer, DataMineit, LLC,*

• Eric Reiner, Professor, UCLA

Question: Amid the current hype around generative AI, are we overlooking other potential breakthroughs in machine learning? If so, which emerging ML approach is most likely to recapture the market’s imagination?

2.05 – PANEL DISCUSSION: Where is AI Going From Here?

• Moderator: Christina Qi, CEO Databento & Founder Domeyard LP

• Dr. Ioana Boier, Ai Expert, NVIDIA,

• Judith Gu, Head Equities Quantitative Strategist, Scotiabank,

• Petros Zerfos, Principal Research Scientist & Manager at IBM Research, Dr.

• Ihsan Erman Saracgil, CPO & Head of Quant Research, OpenBB,

• Amit Gandhi, Professor, Wharton & Airbnb Technical Fellow, Fred Viole, Hedge Fund Manager,

• Ernest Chan, Hedge Fund Manager,

• Dr Jim Kyung-Soo Liew, Johns Hopkins Professor

Question: Given that Databento and OpenBB democratize access to market data and AI research, which combination of analytical frameworks, technical skills, and investment-process guardrails will most reliably translate these tools into genuine, repeatable outperformance for lean teams and individual allocators?

3.00 – PANEL DISCUSSION: Future & Usability of Data For Quant Funds

• Moderator: Harvey Stein, Two Sigma

• *Samantha Mait, Manager, Equity Data Management, Balyasny Asset Management L.P.,*

• Lauren Crossett, Head of GTM, Spade,

• *Ethan Geismar, Head of US Data Strategy, Jefferies,*

• *Evan Reich, Verition Fund Management Head of Data Strategy & Sourcing,*

• George A. Lentzas, Co-Founder & C.I.O., Springfield Capital | Adjunct Professor, Columbia Business School (Machine Learning & Artificial Intelligence)

Question: How should lean data teams, quant pods, and portfolio managers choose between plug-and-play data subscriptions, open-marketplace offerings, or building in-house to ensure each data dollar spent drives the greatest alpha contribution?

4.00 – PANEL DISCUSSION: US VS. The World in 2025: Where Capital Flows The Next Decade? Can We Model Sudden Shifts in the Macro Environment? Trump & Tariffs: Good or Awful for the Market?

• Moderator: Malcolm Dorson, Senior Portfolio Manager & Head of Emerging Markets Strategy, Mirae Asset & Global X

• Manish Aurora, Hedge Fund Manager Rational Investing LLC,

• Abhi Kane, Managing Director Angel Oak Capital Advisors LLC,

• Samir Shah, Hedge Fund Manager,

• Kevin Gahwyler, Managing Director, Meteora Capital,

• Yury Dubrovsky, CFA Fmr Chief Risk Officer at Lazard Ltd & Lazard Asset Management,

• Nan Xiao, Greenland Capital CTO

Question: How might one design a unified modeling process that proactively anticipates and responds to sudden macro shifts driven by political policy changes, ensuring portfolios across U.S. and global markets are optimally positioned for next-decade capital flows?

4.35 – Innovations in Risk Modeling: Machine Learning Applications in Quantitative Finance:

• Arkin Gupta, Vice President Morgan Stanley

Question: In using black-box neural networks for risk modeling, which interpretability methods have best translated complexity into actionable insights trusted by portfolio managers?

4.55 – Closing Keynote:

• Dr. Dhagash Mehta, Head of Applied Artificial Intelligence Research for Investment Management Blackrock

Question: Which emerging AI paradigms are most likely to transform quant investing? And how can the systematic investing community build stronger academic-industry partnerships to rigorously adopt them?

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What questions do you have for the panelists? Leave a comment below

Know someone attending or presenting at the conference? Feel free to forward this to them.

- Jason DeRise, CFA