Jessica Stauth is a Managing Director in Fidelity Labs, an internal startup incubator with a mission to create new fintech businesses that drive growth for the firm. Dr. Stauth previously held roles as Managing Director of Portfolio Management, Research, and Trading at Quantopian, a crowd-sourced systematic hedge fund based in Boston, Director of Quant Product Strategy for Thomson Reuters (now Refinitiv), and as a Senior Quant Researcher at the StarMine Corporation, where she built global stock selection models including the design and implementation of the StarMine Short Interest model. Dr. Stauth holds a PhD in Biophysics from UC Berkeley, where her research focused on computational neuroscience.

Ravit Mandell, Managing Director, is the Chief Data Scientist within Intelligent Digital Solutions. Based in New York, she is responsible for delivering big data and machine learning solutions across Asset & Wealth Management.

An employee since 2010, Ravit was previously in our Corporate & Investment Bank as the Head of the Quantitative Market Making and Swap Trading desks. In addition, she led the Strategic Investments Portfolio, macro market strategy, big data analytics and market structure initiatives.

Prior to JP Morgan, Ravit was at Citi, where she served in various roles including Global Head of North America Rates Trading and Structuring. Ravit earned a B.S. in Mathematics and Physics at Tel-Aviv University in Israel and a Ph.D. in Mathematical Physics - String Theory from Columbia University. Prior to her studies, Ravit was in the Electronics and Computers Unit of the Israeli Air Force.

Claudia Perlich joined Two Sigma as a Senior Data Scientist from Dstillery, where she served as a Chief Scientist (2010 to 2017). As a research staff member in the Data Analytics Research Group at the IBM Watson Research Center (2004 to 2010), she led teams that completed successfully in KDD Data Mining Competitions, designed and executed wallet/opportunity estimation models for IBM Sales using quantile regression, and worked on blog and Twitter analysis tools for marketing. Since 2011, Claudia has also worked as an adjunct professor teaching Data Mining in the M.B.A. program at the New York University Stern School of Business where she received her Ph.D. in Information Systems in 2004.

Sameena Shah is a Managing Director in AI Research group at JPMorgan. She is a highly accomplished technology leader with over 20 years of educational and industry experience in engineering, AI, and leading development teams that created top AI technologies in the world for financial, news, commodities and legal businesses.

Previously, Sameena was Managing Director, Head of Data Science at S&P Global Ratings where she led the firm’s strategy and development for Augmented Intelligence. Prior to that, Sameena worked at Thomson Reuters for seven years in roles of increasing responsibility that involved building state of the art AI systems resulting in business growth and operational efficiencies.

Sameena is also the Founder and CEO of Aylan Analytics LLC, and has worked at Yahoo! Research, a NYC based hedge fund, an International hedge fund, and a global startup.

Sameena has a PhD in Distributed Machine Learning and a Masters in Computer Science from IIT Delhi. She is the winner of the top PhD in the country award, Cloudera top AI/ML application award, several best paper awards and recognitions. She has contributed 41 Publications, and 11 Patents.

Antigoni Polychroniadou is the cryptography researcher lead at J.P. Morgan AI research.

Polychroniadou explores one of the core questions in cryptography: How can we extract the benefits that big data offers while providing privacy to the owner of the data? Antigoni designed secure computation algorithms which allow (distributed) computer systems to perform complex computation on confidential data while preserving the privacy of the information. Applications of such systems include privacy preserving auctions and machine learning on encrypted data.

Prior to J.P. Morgan , Antigoni was a junior Simons fellow, awarded by the Simons Society of Fellows, at Cornell Tech and a postdoctoral researcher in the Computer Science Department at Cornell University. Antigoni completed her Ph.D. at Aarhus University under the supervision of Ivan Damgård. She was a research scholar at the Technion, University of California, Berkeley and IBM Research Thomas J. Watson. She holds an M.Sc. in mathematics of cryptography and communications from Royal Holloway University of London and B.Sc. in Computer Science and Economics from University of Macedonia, Greece.

Elette Boyle is Associate Professor and Director of the FACT (Foundations & Applications of Cryptographic Theory) Research Center at IDC Herzliya, Israel. She received her PhD from MIT, and served as a postdoctoral fellow at Cornell University and at the Technion Israel Institute of Technology.

Prof. Boyle’s research seeks new advancements in the foundations of cryptographically secure computation for safely maintaining and processing sensitive data, with applications to privacy-preserving machine learning, auctions, computations on sensitive financial data, secure exchange of digital currencies, and broad settings for protecting data privacy of individuals and enterprises.

Megan is currently a fifth year PhD student at the University of Michigan, where she is a member of the Strategic Reasoning Group and advised by Michael Wellman. She is also a 2019 JP Morgan AI Research Fellowship recipient. During her PhD, Megan have been a Visiting Research Fellow at IEX and interned at J.P. Morgan AI Research.

Lisa Huang, Ph.D., leads the AI team at Fidelity’s AI Center of Excellence for Asset Management. The AI Center of Excellence for Asset Management is focused on research and deployment of applications using machine learning for portfolio management and predictive modeling.

Previously, she was the Head of Investing at Betterment. In her role at Betterment, she led a team responsible for strategic portfolio optimization and personalization, investment fund selection, risk modeling and tax aware trading optimization. Prior to Betterment, Dr. Huang was a strategist at a hedge fund in Goldman Sachs.

Dr. Huang is a contributing author to the book, “Equity Smart Beta and Factor Investing for Practitioners. She holds a degree in mathematics from University of California, Los Angeles, and a Ph.D. in physics from Harvard.

Elaine is Head of Policy Research at IEX, which was featured in the book Flash Boys by Michael Lewis. IEX's flagship business is the Investors Exchange, a U.S. stock exchange that's setting new standards in the market for fairness and transparency. At IEX, Elaine conducts quantitative research on market structure, trading dynamics, and customer performance to inform IEX's policy initiatives.

Prior to joining IEX, Elaine conducted research at the U.S. Securities and Exchange Commission and Microsoft Research New York City. She holds a PhD in Computer Science & Engineering from the University of Michigan, where she used agent-based modeling to study the impact of different types of algorithmic trading strategies on investors. She also holds a BS in Electrical Engineering from the University of Illinois at Urbana-Champaign and an MS in Computer Science from UCLA. Her research has been cited by Bloomberg, Reuters, CNN Money, and the Wall Street Journal.

Rene Zhang is the Director of Data Science at Quantopian, a crowd-sourced quantitative investment firm. She holds a Ph.D. in Mathematics from Tufts University, specializing in machine learning, tensor algebra, and facial recognition. She joined Quantopian in 2016 and has been focusing on evaluating, selecting, and enhancing trading algorithms.

Parisa Hassanzadeh is a Research Scientist at J.P. Morgan AI Research in New York. Her current research focuses on applying AI and ML techniques such as network analysis to detect and prevent financial crimes, particularly money laundering and payment fraud. She received her Ph.D. degree in Electrical and Computer Engineering from New York University in 2019. Her Ph.D. research was in Wireless Communications and Information Theory with an emphasis on efficient content delivery in cache-aided wireless networks and applications for the next generation of cellular systems

Jennifer Rabowsky is a data scientist in J.P. Morgan’s Asset Management business. She specializes in Natural Language Processing, and has been applying her skills to the financial industry for the last five years. Jennifer graduated from Bryn Mawr College with a dual B.A. in Mathematics and History of Art.

Katherine Magee is an Investment Specialist representing J.P. Morgan’s Asset Management Solutions business. Based in London, Katherine works with client advisors to position the firm's factor investing platform – across strategic beta and alternative beta – and thematic strategies with clients across EMEA and Asia. Katherine previously supported the CEO of Asset Management, EMEA across regulatory, strategy, and day-to-day business management topics, and prior to that, worked on the Institutional Advisory & Sales team at J.P. Morgan in New York. Katherine graduated from Northwestern University with a B.A. in Economics and is a CFA Charterholder.

Veronica will be a senior analytics technical product manager at Fivetran, a newly minted technology unicorn company in Silicon Valley whose mission is to make access to data as simple and reliable as electricity. Previously, she studied Economics and Statistics at Columbia University and became a derivatives trader at J.P. Morgan to pursue her interest in macroeconomics. While being a trader, she discovered that JPMC did not have a modern data stack, despite being one of the biggest and most mature companies in the world. Two years ago, Veronica became the founding member of the Business Intelligence Group and spearheaded big data strategies and built data solutions at J.P. Morgan. Two of the large-scale data analytics products that she created have been demoed to the CEO, Jamie Dimon, in 2019 and 2020 for innovation and commercialization. In her spare time, Veronica enjoys dancing, writing, and running educational and leadership events for women’s networks.

Zhen Zeng is a roboticist interested in creating automated agents with the ability to perceive, understand, predict and act. Her works enable robots to assist people through probabilistic modeling and machine learning. She has recently received her Ph.D. degree in Electrical and Computer Engineering from the University of Michigan.

Before joining JP Morgan, she has developed perception techniques for mobile robots to search and manipulate objects to fulfill tasks. Given perceptual observations such as images or videos, she enabled robots to estimate object states robustly in cluttered environments, and effectively search for objects through predictions. She also led projects on brain tissue labeling in MRI images, real-time gesture recognition for human-computer interaction, and robot snack delivery project for fun. With her research background in dealing with perceptual data, she likes to explore the impacts of understanding financial data from a perceptual perspective.

Charese Smiley is an AI Research Lead on the AI Research team at J.P. Morgan. Her research interests center around computational linguistics and natural language processing. Before joining JPMorgan, Charese worked on the Vision & Language Technology team at Capital One where she led research to build complaint models for customer service channel dialogues and at Thomson Reuters, with the Research & Development group, building automatic summaries for Eikon financial software and natural language question answering for Westlaw legal search, ultimately leading to two patents. Charese is a winner of Turing tests for creative arts, claiming 1^st prize in Dartmouth’s 2017 PoetiX competition for machine-generated sonnet most indistinguishable from human poetry. She also won the 2018 LimeriX competition for machine-generated limericks. Charese holds a B.S. in Computer Science from Texas A&M University and a Ph.D. in Computational Linguistics from Indiana University.

Armineh is Vice President of AI Research at J.P. Morgan Chase. Her career spans a decade of applied research in Natural Language Processing in areas such as targeted sentiment analysis, event detection and verification, information extraction, and social data mining. Prior to J.P. Morgan, Armineh was a Director of Data Science at S&P Global, where she led efforts to transform operational workflows related to the ingestion and processing of financial disclosures. In addition to numerous publications and patents, Armineh’s research has been deployed in award-winning AI-driven technologies such as Reuters Tracer, and Westlaw Quick Check. Armineh was a member of the Rising Star class of 2019-2020, awarded by Women's Bond Club.