Applied AI &

Machine Learning

Key Initiatives

J.P. Morgan empowers today’s talent to solve real-world problems

Anomaly Detection

Identifies unusual patterns in order to minimize and mitigate risk

Intelligent Pricing

Complements traditional pricing models, enabling more accurate prediction and confidence intervals

News Analytics

Aggregates news from various sources and provides analytics for sentiment, summarization, topics and trading signals

Quantitative Client Intelligence

Draws insights from multi-channel client communications to be used to improve client service

Smart Documents

Identifies meaningful information and insights from lengthy text sources in order to reduce manual operations and improve workflow

Virtual Assistants

Automates responses to client queries, (chat, email, voice) with the goal of improving client service and operational efficiency

Meet the Team

Samik Chandarana

Head of Data Analytics, Applied AI & ML

In this role, he leads the Data Analytics, Applied AI and Machine Learning team and is responsible for a cohesive data science strategy, coordinating and prioritizing the portfolio of projects, as well as developing a framework for the appropriate sourcing and usage of data across businesses. He also works closely with the firm’s technology teams and the Chief Data Office to identify and build specialized capabilities that require long-term investments, build and maintain appropriate data and research platforms, develop and grow suitable external partnerships, and ensure a resilient, well-controlled and scalable data analytics and data science infrastructure.

Samik has more than 18 years of experience in Credit Markets where he was most recently the head of Global Credit Indices and Global Credit eTrading. He obtained a degree in Engineering and Management from the University of Manchester Institute of Science and Technology in England.

Machine Learning Center of Excellence

Pairing the unique and complicated data and problems of a bank, with machine learning expertise.

Lidia Mangu, PhD

Head of Machine Learning Center of Excellence

Lidia Mangu is the Head of the Machine Learning Center of Excellence at J.P. Morgan Chase. Prior to joining the bank, Dr. Mangu worked at IBM’s Watson Research Center for 17 years, where she managed the Advanced Speech Research group - a Machine Learning group specializing in Speech Recognition.

Dr. Mangu published more than 100 papers in conferences and journals, received several Best Paper awards and holds many US Patents. She has a Ph.D. in Computer Science from Johns Hopkins University.

The Team of Data Scientists & Machine Learning Engineers

The Applied AI and Machine Learning Center of Excellence (ML CoE) teams partner across the firm to create and share Machine Learning Solutions for our most challenging business problems. Comprised of a multi-disciplinary community of experts focused exclusively on Machine Learning, the ML CoE works together to employ cutting-edge techniques in disciplines such as Deep Learning and Reinforcement Learning. Areas of expertise include: Natural Language Processing, Speech/ Voice Analytics, Time Series and Computer Vision. Both partner with the AI Research team to advance cutting-edge AI research to solve these real-world problems.

Sponsored Events

Learn more about the upcoming conferences we’re attending and sponsoring

June 2019: Long Beach, California

J.P. Morgan sponsored the 2019 International Conference on Machine Learning (ICML) in Long Beach, California. ICML is a premier gathering of over 6,000 participants dedicated to the advancement of the branch of artificial intelligence known as machine learning. Participants span a range of backgrounds, from academic and industrial researchers, engineers and entrepreneurs, to graduate students and PhD postdocs. Professionals present and publish cutting-edge research on all aspects of machine learning.

This year, J.P. Morgan ramped up its presence by serving as a gold sponsor, sending 30 employees from across the firm on different teams to share and discuss the firm’s commitment to this space. This is a reflection of the firm’s growing commitment to key investments in AI and machine learning and it’s starting to pay off. Attendees were eager to hear how the firm is applying AI within the firm and what opportunities J.P. Morgan has available.

The firm hosted a workshop on AI in Finance, the first of its kind in the conference’s 36 year history. J.P. Morgan employees presented six research papers and garnered over 300 workshop attendees.

J.P. Morgan is a proud sponsor of CRYPTO. Join us for our workshop, “Privacy Preserving Machine Learning.” Check back after the event for a full recap.

NeurIPS
December 2019: Vancouver, Canada
December 2018: Montreal, Canada Learn More (Opens Overlay)

J.P. Morgan Hosts Workshop at NeurIPS 2018

With nearly 9,000 attendees, NeurIPS is one of the most prominent and longest-running machine learning and artificial intelligence conferences in the world, bringing together academics and tech giants like Google to share cutting-edge research.

For the first time since its inception 32 years ago, the conference hosted a workshop on AI in financial services. This workshop was jointly organized by J.P. Morgan and Capital One, with invited speakers from Georgia Tech, University of Michigan, Cornell, S&P Global.

J.P. Morgan’s head of AI Research Manuela Veloso and head of CIB Data Analytics, Applied AI & ML Samik Chandarana spoke at the workshop, which addressed key challenges to the adoption of AI in the financial system:

  • Ethical and regulatory needs to prove that models are fair and unbiased
  • Requirements around explainability and interpretability of models
  • Operating standards which require nothing short of perfect accuracy for certain use cases
  • Privacy issues around collection and use of consumer and proprietary data

In addition to the workshop, Veloso and Chandarana, joined by other J.P. Morgan employees, held “lightning talks” at the J.P. Morgan booth attracting hundreds of candidates and hosted a reception attracting leading AI researchers from industry and academia.

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