4 December 2017, Monday

9:05am Opening Address
mitch-ackles-112x128 Mitch Ackles
The Hedge Fund Association

Mitch Ackles is the founder and CEO of Hedge Fund PR, and the global president and spokesman of the Hedge Fund Association, an international non-profit organization that promotes the understanding and development of the hedge fund industry.

With over 20 years experience, Mitch has a track record of excellence. He has executed campaigns for hedge funds, political and economic leaders, service providers, luminaries, conferences, charitable organizations and local, national and global hedge fund groups. Previously, Mitch was marketing director for vFinance, VP of hedge fund capital introduction for Global Partners Group and worldwide marketing manager for Dow Jones TradeStation. Mitch holds a B.A. in PR and communications, is fluent in English and Spanish, and manages reputations for some of the brightest minds and brands in the hedge fund industry.

When raising visibility, his efforts have resulted in thousands of successes, including product and company awards, news articles, cover stories, speaking engagements, broadcast interviews, events, alliances, and product placements on TV and in books, blogs, and movies. His contact network is coveted and includes virtually every editor, reporter, producer, blogger, lawmaker and influencer that has used the term hedge fund. In times when a low profile is preferred, Mitch has insulated clients from the press, influenced search engines, and provided guidance on communicating with media, investors, employees, and counterparties.

Mitch is devoted to service, demonstrated by the pro-bono support of non-profit organizations. As Hedge Fund Association president and spokesman, Mitch is an advocate for the entire hedge fund community. For HFA, he directs media relations, member events and lobbying on Capitol Hill. Mitch also serves as the media contact for Help For Children, a global charitable organization which raises funds for programs that work to prevent and treat child abuse and A Leg To Stand On, a non-profit organization providing free orthopedic care to children in the developing world.

9:10am Keynote Address
mark-yusko-112x128 Mark Yusko
Founder, CEO & Chief Investment Officer
Morgan Creek Capital Management

Mark Yusko is the Founder, CEO and Chief Investment Officer of Morgan Creek Capital Management. Prior to forming Morgan Creek, Mr. Yusko was President, Chief Investment Officer and Founder of UNC Management Company, the Endowment investment office for the University of North Carolina at Chapel Hill, from 1998 to 2004. Throughout his tenure, he directly oversaw strategic and tactical asset allocation recommendations to the Investment Fund Board, investment manager selection, manager performance evaluation, spending policy management and performance reporting. Total assets under management were $1.5 billion ($1.2 billion in endowment assets and $300 million in working capital). Until 1998, Mr. Yusko was the Senior Investment Director for the University of Notre Dame Investment Office where he joined as the Assistant Investment Officer in October of 1993. He worked with the Chief Investment Officer in all aspects of Endowment Management. Mr. Yusko received his Bachelor of Science Degree, with Honors, in Biology and Chemistry from the University of Notre Dame and a Master of Business Administration in Accounting and Finance from the University of Chicago. Mr. Yusko is an Advisory Board member of a number of private capital partnerships and alternative investment programs and has served as a consultant on alternative investments to a select group of institutions. Mr. Yusko is an Investment Committee member of the MCNC Endowment, President and Chairman of the Investment Committee of The Hesburgh-Yusko Scholars Foundation at the University of Notre Dame, and President and Head of the Investment Committee of the Morgan Creek Foundation.

9:50am Next Generation Investment Systems with AI and Alternative Data

  • Using AI-enhanced predictive analytics to improve investment and trading strategies
  • Alternative data to generate new investment ideas
  • Is cognitive collaboration between human and AI the best of both worlds?
michael-o-rouke-112x128 Michael O’Rouke
Head of Machine Intelligence and Data Services

Mike O’Rourke has spent 18 years of his two-decade-long career in technology at Nasdaq. As Global Head of Machine Intelligence and Data Services, he leads Nasdaq’s machine intelligence Innovation Lab that combines proprietary data with advanced analytics and machine learning to produce high-impact results for customers, including the Lab’s newest products: Trading Insights and the Nasdaq Analytics Hub.

Morning Refreshments & Networking Session
Case Study – Picking Stocks with AI

  • Demonstrate the value of unstructured data with Natural Language Processing to company disclosures
  • Reacting to the qualitative information reported in firms’ disclosures by investors
  • Corporate problems in 10-K and 10-Q filings on average leads to share price underperformance over the following quarter and future negative earnings surprises
andy-moniz-112x128 Andy Moniz
Chief Data Scientist
Deutsche Bank
Andy Moniz is the Chief Data Scientist for Deutsche Bank Global Markets. Andy was previously a quantitative equity portfolio manager responsible for long-short text mining strategies at UBS O’Connor. Prior to UBS, Andy was a senior portfolio manager at APG Asset Management focused on text-based stock-selection strategies. Andy began his career in 2000 as a macroeconomist at the Bank of England. Between 2003-2011, Andy worked in Quantitative Equities for various investment banks. Andy holds a BA and MA in Economics from the University of Cambridge, an MSc in Statistics from the University of London, and a Ph.D. in Information Retrieval and Natural Language Processing from Erasmus University, The Netherlands. He is also a CFA Charterholder and an academic referee for text mining papers for the Financial Analyst Journal.
11:20am Applying Different Machine Learning Techniques to Different Trading Strategy

  • Supervised Learning – Predicting Market Trends
  • Unsupervised Learning – Identifying Correlations
  • Deep Learning
  • Reinforcement Learning
Alex-Fleiss-112x128 Alexander Fleiss
CEO, Chairman, and Co-Founder
Rebellion Research
Rebellion Research logo
Alexander Fleiss serves as CEO of an online financial advisory & hedge fund that invests across all asset classes and utilizes a proprietary Machine Learning that monitors data from 53 countries on a daily basis. Mr. Fleiss has spoken about Artificial Intelligence investing in the Wall Street Journal, Fox News, BusinessWeek, Bloomberg News, MIT Technology Review, Wired, Mathematical Association of America, Financial Times, CNBC, Geo Magazine, Institutional Investor and the Wall Street Journal Reporter Scott Patterson’s book Dark Pools. In addition, Mr. Fleiss has lectured on Artificial Intelligence & Machine Learning at Princeton University, Amherst College, Yale School of Management, Booth School of Business at the University of Chicago, Tufts University, Cornell University, The Wharton School of Business at The University of Pennsylvania and Columbia Business School.

Prior to co-founding in 2007, Mr. Fleiss served as a Principal at KMF Partners LP, a long-short US equity fund. Mr. Fleiss began his investment career as an analyst for Sloate, Weisman, Murray & Co which was acquired by Neuberger Berman. Mr. Fleiss developed investment algorithms with the firm’s CEO, Laura Sloate who is now a partner at Neuberger Berman and is one of the investors featured in Peter Tanous’ book Investment Gurus. Mr. Fleiss received a BA Degree from Amherst College.

11:50am Autonomous Learning Investment Strategies (ALIS): Third Wave of Investment Management

  • Confluence of big data, data science, machine learning, and computing power
  • Differentiating factors of ALIS
  • Upending investment management with technology and engineering
adil-abdulali-112x128 Adil Abdulali
President and Chief Science Officer
MOV37 and Protégé Partners
Mov37_FINAL Logo-01 Protege Logo 2
Adil has 26 years of experience in the markets. He received an M.A. in pure mathematics from MIT and B.A. in mathematics from the University of Pennsylvania. He spent the first half of his career trading fixed income derivatives at JP Morgan, Nikko, Nomura, and Barclays. At Nomura and Barclays, he ran the systems and analytics groups for these products. He subsequently joined Capital Market Risk Advisors as a Senior Advisor specializing in structured products and hedge fund valuation. He joined Protégé in 2003 and specializes in risk measurement as well as quantitative and relative value strategies. Adil used geometry to invent the Bias Ratio, a metric that detects return smoothing by active managers.
12:20pm Deep Learning framework with NLP and Bayesian Statistics for stock selection and portfolio management

  • Selecting stocks with Reinforcement Learning algorithms.
  • Adjustments by NLP and Bayesian Statistics techniques.
  • High-Performance Computer infrastructure for this framework.
  • Backtesting
juan_brana-112x128 Juan Pablo Braña
Co-Founding Partner and Chief Data Officer
Eye Capital

Juan Pablo Braña is a co-founding partner and Chief Data Officer at Eye Capital, a technology company which develops trading algorithms based on Artificial Intelligence and implements its own multi-market FIX and DMA platform with strong cryptographic and security properties being a pioneer in Algorithmic Trading in the Argentinian markets.

Mr. Braña has a strong academic background as a researcher and professor of Data Science in the financial arena with more than 15 years of experience in Statistics and Applied Math in the industry. He developed braiNY algorithm which is based on Reinforcement Learning techniques, Bayesian Statistics, and Natural Language Processing selects stocks from U.S. markets and manages an equities portfolio. He also designed globalEYE, an algorithm which operates in U.S., London, Hong Kong and Spain markets and also uses Markov Process techniques. Both strategies have shown excellent returns and are on continuing development.

Mr. Braña is part of a multidisciplinary team at Eye Capital, composed by Alexis Sarghel who leads the High-Performance Computing Department, Alejandra M. J. Litterio in the Research and Computational Linguistics area, Federico Massa specialist in Cybersecurity, Nicolás Paladini and Adrian Raguza, both in charge of the finance and business affairs.

Networking Luncheon
2:00pm Panel DiscussionChallenges in Automated Trading With AI

  • When the unexpected happens
  • Determining the correct strategy
  • Cybersecurity and privacy issues
Alex-Fleiss-112x128 Alexander Fleiss
CEO, Chairman, and Co-Founder
Rebellion Research
 Rebellion Research logo
ambika-sukla-112x128 Ambika Sukla
Executive Director, AI & Machine Learning
Morgan Stanley
Ambika Sukla heads Morgan Stanley’s Center of Excellence for AI and ML. He helps set Morgan Stanley’s AI strategy and promotes the application of machine learning techniques in algorithmic trading, risk management, operations, compliance and wealth/investment management, and other areas of finance. He has extensive experience in different types of machine learning problems such as recommendation systems, classification/regression, clustering, anomaly detection, natural language processing and optimal control. His current area of expertise is in incorporating latest research in AI such as Recurrent Neural Networks, Deep Reinforcement Learning, Deep Generative Models and Optimization based Bayesian Learning to financial use cases. He is a major proponent of unsupervised/semi-supervised learning methods and ideas that help with learning without labels or learning with synthesized labels. Prior to Morgan Stanley, Ambika was with Goldman Sachs and has spent most of his career working on deriving insights from data using a combination of visualization, analytics, and modeling. Ambika’s background is in signal processing and information theory and he has a Masters in Telecommunication Engineering from NJIT.
peter-yesley-112x128 Peter Yesley
Vice President of E-Trading Quants
Bank of America Merrill Lynch
Peter Yesley, a quant, develops algorithms for the electronic trading of corporate bonds at Bank of America.  He has developed a number of statistical techniques to measure client demand and inventory holding time.  Peter joined Bank of America in 2015.  From 2010 to 2015 worked Goldman Sachs also in the electronic trading of bonds. Prior to finance, Peter work as an image scientist for the visual effects industry.  Here he built algorithms for producing images of oceans inside the computer.  This work was featured in “James Bond: Die Another Day”. Peter holds a Ph.D. in Physics from Harvard University.  His doctoral thesis was on how to make and confine atoms of antimatter.
david-c-coggins-112x128 David C. Coggins
Principal, Co-Founder, Portfolio Manager
Coral Gables Asset Management
David launched Coral Gables Asset Management (“CGAM”), in 2014 where he is Co-Founder, Principal, and Board Member. CGAM is an equity market neutral L/S hedge fund located in Miami, Florida that employs sophisticated quantitative equity strategies. CGAM offers a unique method to investing that is scientific in its approach that eliminates human emotion and the known biases and heuristics that can lead to systematic mistakes in investment decisions.  He is known as a subject matter expert in the fields of Behavioral Finance, Asset Pricing, and sophisticated quantitative equity strategies. David’s research interests include psychology based trading strategies, analyst forecasts, return predictability and portfolio choice. He has an M.A., Quantitative Finance from I.E., Business School, Madrid Spain, M.A. from Indiana Kelley School of Business, M.B.A, Finance & Management Science from the University of Miami School of Business Administration, B.A., Finance and Economics from the University of Hartford Barney School of Business. 
2:40pm Applying Machine Learning and High-Frequency Trading to Asset Management

  • Why are Deep Learning and HFT needed together in asset management and why now?
  • How is deep Learning applied in trading? What’s the secret sauce?
  • Demystifying deep learning – understanding the intuition behind the strategy
gaurav-chakravorty-112x128 Gaurav Chakravorty
Gaurav Chakravorty is co-founder and CIO at qplum. Qplum is an asset management firm that offers A.I. based trading strategies. Gaurav has been one of the early pioneers in machine learning based high-frequency trading. He built the most profitable algo trading group at Tower Research from 2005-2010 and was the youngest partner in the firm. Gaurav’s strategies have made more than $1.4bln to-date. He believes in the potential of using Deep Learning to reduce fees and make investing a science that is universally accessible.
3:10pm The Big Data & Machine Learning Revolution

  • Preparing for the big data revolution
  • Using machine learning to create predictive models
  • Are you part of the change or will you be overthrown?
armando-gonzalez-112x128 Armando Gonzalez
Chief Executive Officer
Armando Gonzalez is President & CEO of RavenPack, the leading provider of real-time news and social media analysis. Armando is an expert in the field of text analytics and applied semantic technologies. He has designed systems that turn unstructured content into structured data, primarily for financial trading applications. Armando is widely regarded as one of the most knowledgeable authorities on automated text and sentiment analysis.

His commentary and research have appeared in leading business publications such as the Wall Street Journal, Financial Times, CNBC, among many others. Armando holds degrees in Economics and International Business Administration from the American University in Paris and is a recognized speaker at academic and business conferences across the globe.

Afternoon Refreshments & Networking Session
3:50pm Case Study – Reinforcement Learning with J.P. Morgan

  • Using RL to maximize final (or cumulative) reward
  • Deep Q –Learning: From self-driving cars to quant strategies
  • Alternatives (evolutionary strategies) and Future (beyond simple Bellman’s equation)
rajesh-krishnamachari-112x128 Rajesh T. Krishnamachari, Ph.D.
Quantitative Strategist and Data Scientist
J.P. Morgan
JPM Logo
Rajesh Tembarai Krishnamachari is a researcher on systematic cross-asset (Equity/FX/Commodity/Rates; Delta-one and Derivative-based) strategies with the Macro Quantitative and Derivatives Strategy team. Before joining the team, he was a quant with the Equity Derivatives QR at J.P. Morgan, where his research spanned both high-frequency algorithmic trading as well as equity quantitative strategy development. Dr. Krishnamachari ‘s extensive and highly-cited research record includes 1 book and 7 papers on signal processing & machine learning, 3 papers on mathematics, and 13 papers on social sciences & economics. Dr. Krishnamachari was educated at New York University, University of Colorado and Indian Institute of Technology, Madras.
4:30pm Developing Robust Investment Algorithms with AI and Deep Learning

  • How to start and overcomes common obstacles
  • Overfitting: Overcoming a big cause of poor performance
  • Challenges and potential that lie ahead
jeffrey-yau-112x128 Jeffrey Yau
Chief Data Scientist

Jeffrey currently works as the Chief Data Scientist at AB, formerly known as AllianceBernstein, a leading global investment management, and research firm, where he is building a data science team and leading all of the data science initiatives. Prior to AB, he was the Vice President and Head of Data Science at Silicon Valley Data Science, a boutique consulting firm focusing on data science, data engineering, and data strategy consulting. Jeffrey led a team of Ph.D. computer scientists, statisticians, and scientists from various domains to help Fortune 500 companies transform their businesses using data science and emerging data technologies.

With extensive experience in applying a wide range of data science techniques to develop analytic, predictive, and prescriptive solutions, he has expertise in combining high-performance computing and modern data technology to analyze massive databases to generate analytic insights for strategic decision making. Jeffrey held various positions before SVDS, including the Head of Risk Analytics and Quantitative Research at Charles Schwab Corporation, Director of Financial Risk Management Consulting at KPMG, Assistant Director at Moody’s Analytics, and Assistant Professor of Economics at Virginia Tech. During his doctoral study and the last two years of his undergraduate study, Jeffrey worked in research teams at RAND Corporation, the World Bank, the Wharton School, and University of Pennsylvania School of Medicine. Jeffrey holds a Ph.D. and an M.A. in Economics (with a focus on econometrics) from the University of Pennsylvania and a B.S. in Mathematics and Economics from UCLA.

5:00pm Q&A Session & Closing Remark by Forum Chairperson
5:05pm image-3
Champagne Networking Session

Enjoy a glass of champagne whilst networking with other like-minded individuals on topics that are of most interest to you and fellow delegates.

 5 December 2017, Tuesday

9:00am Welcome speech
mitch-ackles-112x128 Mitch Ackles
The Hedge Fund Association
9:05am Highlights on Conference Day Two Key Sessions by Chairperson
Theme: Machine Learning and AI Approach to Investments
9:10am Keynote Address: Machine Learning and Big Approach to Investing

  • Changes in Investment Industry
  • Use of Big and Alternative Data
  • Application of Machine Learning methods
marko-kolavnic-112x128 Marko Kolanovic
Global Head of Macro Quantitative and Derivatives Research
J.P. Morgan
JPM Logo

Marko Kolanovic is the Global Head of Macro Quantitative and Derivatives Strategy team at J.P. Morgan. His team is responsible for developing macro, derivatives and quantitative equity strategies, as well as systematic cross-asset portfolios for clients. His team currently holds 5 top rankings in the Institutional Investor surveys in the US, Asia, and Europe, and Marko individually ranks #1 in the category of Americas Equity Derivatives. Prior to joining J.P. Morgan, Dr. Kolanovic was Global Head of Derivatives and Quantitative Equity Strategies at Bear Stearns and a derivatives research analyst at Merrill Lynch. His trading methods have been implemented by major hedge funds and investment offices around the world. Dr. Kolanovic’ s work is frequently quoted in financial press, and for his timely and accurate short term forecasts of stock market returns, the media dubbed him ‘The Man who moves Markets’ (CNBC) and ‘Gandalf’ (Bloomberg). Marko graduated from New York University with a Ph.D. in theoretical high-energy physics. He has developed a number of scientific theories/models and has authored top-cited research publications. He currently resides in New York City.

9:50am Utilizing AI and Machine Learning to Establish Market Predictions and Placing High Probability Trades

  • Sourcing alternative data sets
  • Building an Alpha library of predictive machine learning models
  • Combining data sets to strengthen alpha generation
tim-harrington-112x128 Tim Harrington
Co-founder and CEO
BattleFin Asset Management
BattleFin with capital B and F

Tim is a co-founder and CEO of BattleFin Asset Management which is an S.E.C. registered investment adviser.  He is CIO of the BattleFin Alternative Data and Machine Learning Strategy.  Tim is also responsible for strategy selection and for external allocations.  He has over 20 years of experience in the financial services industry.  Most recently Tim was the President and a Partner at Lion’s Path Capital, a hedge fund strategy incubator.  He sat on the Lion’s Path Investment Committee and identified and on-boarded 30 fundamental portfolio managers since the launch in 2009.  From January 2006 until 2009, Mr. Harrington was a Vice President at J.P. Morgan Ventures where he was in charge of Global Technology, Media & Telecom Investments and served as a Portfolio Manager. From February 2002 until January 2006 he was a Telecom & Media Portfolio Manager at Sigma Capital, a subsidiary of SAC Capital and managed a team of four investment professionals. Mr. Harrington graduated from Columbia College in 1998.  He was a member of the Columbia University Judiciary Board as well as a member of the varsity crew team.

Morning Refreshments & Networking Session
Optimizing Asset Allocation with Artificial Intelligence

  • Applying network analysis concepts for optimal asset allocation
  • Influence of market regimes on portfolio performance and robustness
cristian-homescu-112x128 Cristian Homescu
Director, Portfolio Analytics
Chief Investment Office
Global Wealth and Investment Management (GWIM)
Bank of America Merrill Lynch
BAML logo
  Cristian is part of the Portfolio Analytics team within Chief Investment Office, Global Wealth and Investment Management division Bank of America Merrill Lynch. He is developing and investigating quantitative solutions in areas such as investment strategies, goals-based wealth management, asset allocation, machine learning and big data analysis, factor-based investing and risk factor models, portfolio risk, and attribution, stress testing, and scenario construction.

He is very interested in the application of state-of-the-art algorithms and numerical methods in wealth and investment management and in high-performance computing.

Prior to joining Bank of America Merrill Lynch, Cristian was a front office quant for Wachovia and Wells Fargo. After supporting interest rate trading desk, he was the lead quant for FX and Commodities trading desks.

He has a Ph.D. from Florida State University in computational and applied mathematics, and MSc degrees from University of Paris XI and University of Craiova.

11:30am How AI & Deep Learning Can Learn Your Past Successful Trades and Replicate It Forward

  • Discovering profitable strategies
  • How to replicate profitable trades under dynamic market conditions
max-margenot-112x128 Maxwell Margenot
Data Scientist and Lecturer
Max’s background is in applied mathematics, statistics, and quantitative finance. He runs the online lecture series at Quantopian and is responsible for workshop curriculums and educational content. In addition to having experimented with algorithmic trading of cryptocurrencies and Bayesian estimation of covariance matrices, Max has published work in theoretical mathematics. He works with top universities including Columbia, U Chicago, and Cornell and holds an MS in Mathematical Finance from Boston University.
12:10pm Reserved for Gold/Platinum Sponsor for Project Showcase
Networking Luncheon
2:00pm Assembling an Effective AI Team to Identify Investment Trends – Who and What Expertise You Need

  • Challenges of forming the team: How to attract talent
  • Synergy or conflict in the team
  • Mixing the old and new
harold-hean-baptiste-112x128 Harold Jean-Baptiste
Executive Director – Chief Data Scientist
Harold Jean-Baptiste is the Executive Director-Chief Data Scientist at Segmint, where he is responsible for managing the data science ecosystem and developing progressive algorithms. Harold is a seasoned data scientist with over 15 years of experience in the financial services and insurance industries.

Harold joined Segmint from General Electric Asset Management (GEAM) where he developed investment algorithms for fixed income and equities in his role as the Quantitative Strategist & Senior Data Scientist. Prior to GEAM, Harold led a group at Infosys Data Science where he implemented Big Data Hadoop technology architecture and solutions for Fortune 500 companies.

Earlier in his career, Harold held various data science roles at Citi Group and Wyndham Worldwide.

Harold holds a Bachelor of Integrated Information Systems and a Master of Business Administration in Finance from Long Island University.

2:40pm Pairing AI Strengths With Asset Managers’ Knowledge to Outpace Competition

  • Overcoming “algorithm aversion” of asset managers
  • Driving adoption of systematic processes with discretionary managers
  • Towards integrated human-machine interactive investing
norman-niemer-112x128 Norman Niemer
Director, Quant & Data Science Team Lead
UBS O’Connor

Norman Niemer leads a quant & data science team for the Chief Investment Officer at UBS O’Connor, the hedge fund unit of UBS, where he leverages machine learning and AI to build investment strategies and systematize fundamental investment processes. He is also responsible for both the business as well as technical aspects of multiple innovation projects that augment human decision makers with machine intelligence. Outside of investment management, he has led teams that built data- and AI-based products that won several high profile coding competitions including Techcrunch NY, Fintech NY and Mastercard Masters of Code NY. Prior to UBS O’Connor, Norman worked at Caxton Associates and Morgan Stanley as well as startup hedge funds and he even founded a tech company in high school! He holds a MS Financial Engineering from Columbia University and a BS in Banking and Finance from Cass Business School (London).

Afternoon Refreshments & Networking Session
Theme: Risks and Pitfalls of AI Approach to Investments
3:40pm Panel DiscussionBefore the Pitch: Understanding Machine Learning in Investment Models

  • What can machine learning do wrong and how to avoid the pitfalls
  • Dangers of data mining and overfitting, and how to prevent them
  • How to sell the concept of using AI to automate investment for clients and investors
pamela-finelli-112x128 Pamela Finelli
Managing Director, Head Equity Derivatives & Delta1 Strategy
Deutsche Bank

Pamela Finelli is the Global Head of Equity Derivatives Research for Deutsche Bank.  Her team provides an in-depth analysis and ideas across a broad range of equity derivatives and delta-one instruments.  She also co-leads Data Innovation Research at Deutsche – a group responsible for leveraging developments in Artificial Intelligence and Big Data.

Pamela started her career in at Bankers Trust Fixed Income Derivatives in a trading risk role and then moved to Equity Derivatives Strategy for Deutsche Bank in NY.  She was a lead architect for, Deutsche Bank’s award-winning data and analytics website.  From 2007 to 2014, she was based in London and led DB’s European equity volatility, dividend and index-based research group  Her team was ranked #1 in the European Institutional Investor survey from 2010-2014.

Pamela lives in NJ with her husband and three children.  She currently serves on committees for several charitable organizations in her community and was appointed to the Girls’ Board of the UK Chance to Shine charity while she was in London.


Dr. Arun Verma
Quantitative Researcher
Bloomberg LP

Dr. Arun Verma joined the Bloomberg Quantitative Research group in 2003. Prior to that, he earned his Ph.D from Cornell University in the areas of computer science & applied mathematics. At Bloomberg, Mr. Verma’s work initially focused on Stochastic Volatility Models for Derivatives & Exotics pricing and hedging. More recently, he has enjoyed working at the intersection of diverse areas such as data science (for structured data such as financial time series & unstructured data such as sentiment analysis using NLP), innovative quantitative & machine learning methods for statistical arbitrage, and, interactive Visualization & Analytics to help reveal embedded signals from the data.

david-c-coggins-112x128 David C. Coggins
Principal, Co-Founder, Portfolio Manager
Coral Gables Asset Management
andrej-rusakov-112x128 Andrej Rusakov
Co-Founding Partner and Seed Investor
Data Capital Management
DCM logo
Andrej Rusakov is the co-founding partner and seed investor in Data Capital Management – a systematic hedge fund built on novel big data technologies, real-time data feeds and artificial intelligence computer science.  He is passionate about investing, the onset of the “Data Economy”, and effectively motivating teams to consistently exceed expectations and have fun while doing so!

Mr. Rusakov previously founded Open Capital, a global holding and investment company with assets and portfolio companies in the USA, Europe, and Russia.  Prior to that, he worked for Apax Partners where he was involved in $1 billion worth of buy-outs worldwide.  He started his career in the Mergers & Acquisitions team of Morgan Stanley in London.

Andrej holds an MBA from Harvard Business School and an
MSc. (Summa Cum Laude) in Mathematics (Statistics and Theory of Probabilities) from the Department of Mechanics & Mathematics of Moscow State University.

Andrej is a serial entrepreneur having launched multiple businesses utilizing his team building, leadership, and investing expertise.

 4:10pm Understanding the Weak Points of AI and ML
andrej-rusakov-112x128 Andrej Rusakov
Co-Founding Partner and Seed Investor
Data Capital Management
DCM logo
4:40pm Model Risk Management for Machine Learning and Trading Strategies  
ben-steiner-112x128 Ben Steiner
Director – Quantitative Strategies
Ben Steiner is the Head of Quantitative Strategies at CIT Group. His experience covers quantitative modeling, portfolio management and business development for alternative investments. Now focusing on the less liquid asset class of private debt, his previous experience covered the more liquid strategies of Non-traditional Bond; Managed Futures; Global Macro & Equity Long/Short.

At CIT, Ben is now responsible for model development, research and analysis of credit and default risk. This includes probability of default, loss severity & stress testing (CCAR, DFAST). Ben joined CIT in 2015 and is based in New Jersey.

Before joining CIT, he was an Absolute Return Portfolio Manager and Senior Quantitative Researcher at FFTW (a subsidiary of BNP Paribas). Prior to that, he was with Aspect Capital as the Research Manager for financial engineering. Ben started his career at Deutsche Bank as a member of the quantitative research and portfolio construction team. He has 16 years of alternative investment experience.

Ben has a BA in Economics (with honors) from The University of Manchester and an MSc in Mathematical Finance from Imperial College London. He serves as a Director of the Society of Quantitative Analysts (SQA) – which celebrated its 50th-anniversary last year – and sits on the Big Data Advisory Board at Rutgers.

5:10pm Q&A Session & Closing Remarks by Conference Chairperson

Post-Conference Workshop – 6 December 2017, Wednesday

Workshop Timetable:

Workshop A will run from 9:00 am – 12:00 pm with a mid-morning and luncheon breaks.
Workshop B will run from 1:30 pm – 4:30 pm with a mid-afternoon refreshment break.

Registration begins 30 minutes before each workshop commences.

9:00 am – 12:00 pm

Post-Conference Workshop A: Using Alternative Data to Generate Alpha

aaron-goldenberg-112x128 Aaron Goldenberg
Data Scientist
QuantRisk Trading
Aaron is a quantitative consultant applying data science techniques to analyzing financial and alternative data sets. He holds degrees in math and law from Johns Hopkins, NYU, and Fordham and has worked previously with investment banks, hedge funds and technology startups including Bridgewater Associates, CIG, Crosstree, Prudential Securities, Sakura Global Capital and Societe Generale.
1:30 pm – 4:30 pm

Post-Conference Workshop B: Implementing State-of-the-Art AI and Machine Learning Algorithms for Use in Trading & Capital Markets

  • Applying machine learning algorithms to trading decisions
  • Developing automated trading strategies based on high performing models
  • Understanding the real-world challenges of implementing machine learning based trading strategies
george-lentzas-112x128 George A. Lentzas
Manager & Chief Data Scientist, Springfield Capital Management
Adjunct Associate Professor of Business, Machine Learning, Columbia Business School
Adjunct Associate Professor of Economics, New York University
Springfield Capital Management
Dr. George A. Lentzas (Springfield Capital Management, Columbia Business School and NYU) is a statistics expert with a decade of experience in applying quantitative models in the real world. He has worked in various capacities at a number of leading financial institutions, including Morgan Stanley, BNP Paribas, Citigroup and Hutchin Hill Capital. He has also held faculty positions at both Columbia University and New York University, where he has taught courses in Machine Learning and Applied Statistics & Econometrics. His professional expertise includes the application of statistics, machine learning and artificial intelligence to finance and economics. He is currently the Chief Data Scientist and Manager of Springfield Capital Management, a NY based start-up quantitative hedge fund, as well as an Adjunct Associate Professor of Business at Columbia Business School and of Economics at New York University. He holds a PhD, MPhil and BA from Oxford University, an MPhil from Cambridge University and has been a Visiting Fellow at the Department of Economics, Harvard University.