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Also Attend: 
Model Management Workshop: The magic behind making decisions happen; ML, AI, & prescriptive analytics within business design & control constraints
New York City: February 26th & 27th 2018  

Pre-Conference Workshop day: Wednesday February 28th 2018

Machine Learning in Finance: A Practical View by Miquel Noguer Alonso: UBS & Columbia University

Thursday March 1st 2018: Main Conference Day One Stream

Friday March 2nd 2018: Main Conference Day Two Stream


Keynote: O. Ediz OzkayaO. Ediz Ozkaya: (Machine Learning)

Executive Director, Machine Learning Labs, Securities,

Goldman Sachs

Keynote: Marcos Lopez de PradoMarcos Lopez de Prado

Research Fellow

Lawrence Berkeley National Laboratory

Miquel Noguer AlonsoDr. Miquel Noguer Alonso

Adjunct Assistant Professor

Columbia University

Abdel LantereAbdel Lantere

Data Scientist, Quantitative Consultant


Michael Beal


Data Capital Management

Gordon Ritter Gordon Ritter

Senior Portfolio Manager

GSA Capital 

Jess StauthJess Stauth

Managing Director


Yves HilpischImage result for yves hilpisch

Founder and Managing Partner

The Python Quants 

Paul Bilokon Paul Bilokon, PhD

Founder, CEO,Thalesians

Senior Quantitative Consultant, BNP Paribas

George A. Lentzas George A. Lentzas

Manager & Chief Data ScientistSpringfield Capital

Adjunct Associate Professor, ColumbiaNew York University  

Arun Verma Arun Verma

Quantitative Research Solutions

Bloomberg, LP

Peter Hafez Image result for peter hafez ravenpack

Chief Data Scientist


Suhail Shergill

Suhail Shergill

Director | Data Science and Model Innovation

Scotiabank | Global Risk Management

Seong Seog Lee

Director of Quant Strategy


Joe Jevnik

Senior Software Engineer



  • Predictive Power vs. Expressiveness of Machine Learning Models
  • Machine Learning - Recent Trends and Applicability to Risk and Related Areas 
  • Black-box Machine Learning: Improving Transparency
  • Machine Learning - Recent Trends and Applicability to Risk and Related Areas
  • Applying Machine Learning to Evaluate Systemic Risk and Contribution of Individual SIFIs 
  • Fast MVA Optimisation using Chebyshev Interpolants 
  • The 7 Reasons Most Machine Learning Funds Fail
  • Machine Learning, High-Frequency Trading and Kdb+/q for Quants and Data Scientists 
  • Machine Learning for Trading 
  • Big Data and AI Strategies: Machine Learning and Alternative Data Approach to Investing
  • Text Mining and Market Sentiment 
  • Machine Learning & Event Detection for Trading Energy and Metal Futures
  • Extracting embedded alpha in Stocks and Commodity underlyings using statistical arbitrage/ML techniques from News/Social data

Conference Bookings: Discount Structure:

  • Super Early Bird Discount: 25% Until January 26th 2018
  • Early Bird Discount: 10% Until February 9th 2018
  • SPECIAL OFFER: When 2 colleagues attend the 3rd goes free!
  • Main Conference + Workshop ($250 Discount)
  • 70% Academic Discount (FULL-TIME Students Only) 

 Important notes:

Main Conference presentation files on USB memory sticks will be provided on arrival. The Main Conference files will also be made available for download via a password protected website before the event. Please print out each presentation if you wish to have hard copies before the conference and bring them with you.

Also, Wi-Fi access will be available at the venue to view presentations on laptops and mobile devices