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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

CIB Chief Data & Analytics Officer (CDAO)

Samik is the Chief Data & Analytics Officer for the Corporate & Investment Bank and is responsible for driving the data strategy and governance, data commercialization agenda as well as delivering data analytics solutions to the businesses.

He leads the Applied AI & ML organization for CIB and the firmwide Machine Learning Center of Excellence, where he is responsible for advancing the development and adoption of scalable analytics and AI solutions across its businesses. He also leads the CIB Chief Data & Analytics Office (CIB CDAO) where he partners with organizations across the firm to deliver best-in-class data management capabilities and platforms that offer secure and reliable data. Lastly he is responsible for driving the CIB data commercialization agenda including PricingDirect.

Samik has more than 22 years of experience at J.P. Morgan with the majority 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 JPMorgan 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.

Life as an AI Researcher & Machine Learning Engineer

Our J.P. Morgan office is a place where you can solve real-world problems using state of the art machine learning methods and cutting-edge AI research.

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Manuela Veloso: So, at J.P. Morgan, the interesting thing is that we are a firm that has been around for a long time. But it's a firm that has a lot of appetite.

Ashleigh Thompson: One thing's for sure, no two days here ever look the same. I like to start my day in London early. Since we're a global team, it gives me the chance to review work our New York team did last night and catch up live with my colleagues in India.

Virgile Mison: The Machine Learning Center of Excellence develops and deploys machine learning models across different trading and IT platforms of J.P. Morgan.

Saket Sharma: J.P. Morgan, as a bank, has been incorporating machine learning into a lot of our work flows. So, as a Machine Learning Engineer, this is a great time to work on problems with firmwide impact.

Samik Chandarana: We need humans and AI to work together because ultimately, having and learning from what people are doing today in the processes they do and how they operate today provides a great amount of information of how we design systems of the future.

Andy Alexander: External conferences are really important for a number of reasons. One - it allows us to bring in the best of academia and external thought to the organization. The other is that it allows the team to go out to continue to learn. We rely a lot on where we're going, as well as where we've been.

Lidia Mangu: So, we come back from a conference knowing where the field is. And how, you know, taking those state of the art methods and applying them to the problems in the bank.

Simran Lamba: The most exciting and novel thing about working with AI Research is getting to publish our work at the most esteemed academic conferences like ICML, AAAI, and NeurIPS. We not only participate, but we also host and sponsor workshops at these conferences.

Naftali Cohen: I get to focus on the hot topics in AI and machine learning, such as reinforcement learning, cryptography and explainability.

Ashleigh Thompson: Millions of people use and rely upon our products and services every day. Working here, you have the ability to be on the forefront of changing that interaction.

Manuela Veloso: We apply and discover new AI techniques to handle complex problems such as trading, multi-agent market simulations, fraud detection, anti-money laundering and issues related to data.

Virgile Mison: As a technologist I was the most surprised by the wide variety of problems that we have to tackle and that J.P. Morgan is in the unique position to solve thanks to the large amount of data available.

Samuel Assefa: We focus on a number of research problems. One of the most exciting ones is ensuring that AI models are explainable, fair and unbiased.

Andy Alexander: In my life span, I don’t expect to see generalized AI become something that's mainstream. And so for a lot of time we're expecting to see humans and machine helping each other.

Lidia Mangu: Every day is different. Every day we get a new challenging problem. Sometimes there is no known solution for that problem and it is like a new puzzle. Sometimes there is a known solution, but we show how we can do better using state of the art machine learning techniques.

Manuela Veloso: There is a lot of belief as we move that AI and machine learning is this one-shot deal. We do it, we are done. We'll never be done.

Naftali Cohen: I work with some of the best and most creative minds in the field and I have ownership over my work which is very rewarding.

Naftali Cohen: I'm researching how to apply innovative computer vision and deep learning techniques to understand the complexity of decision making in the financial market and recommend clients for market opportunities.

Simran Lamba: What excites me the most about my job here, in New York, is the opportunity to learn from our leaders and external professors. And my favorite part of the day would be brain-storming creative research ideas to solve challenges across all lines of businesses.

Simran Lamba: I’m currently using event logs of Chase customers called ‘Customer journeys’ to find ways to create an even better experience for our clients.

Manuela Veloso: We do believe that junior people are the ones, in some sense, that have that vision. That can think big and that they are not kind of like constrained.

Samik Chandarana: Our clients are getting younger they want to be interacting in different ways and we need fresh talent to come up and help us with those new ideas and actually implement them in a way that makes sense for the client experience.

Lidia Mangu: The advice I would give to a junior executive is to be open-minded. Not to be afraid to learn new things every day. The field is moving very fast.

Virgile Mison: There are many opportunities to learn at J.P. Morgan. Like collaborating with experts in natural language processing, deep learning, time series and reinforcement learning.

Ashleigh Thompson: I'm excited to be part of the transformation to a truly data-driven culture.


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.

December 2019: Vancouver, Canada

Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness and Privacy

J.P. Morgan served as a platinum sponsor for the Thirty-third Conference on Neural Information Processing Systems (NeurIPS) 2019 conference held in Vancouver, Canada. NeurIPS has established itself as one of the leading AI conferences in the world, with a record 13,000 attendees this year. To mark its growing interest in technology investment, AI and machine learning, J.P. Morgan sent nearly 50 employees to the conference with representation from all lines of business and three continents.

This year, the firm also hosted its first industry-focused EXPO workshop in partnership with Two Sigma and Hudson River Trading, which garnered over 450 attendees, filling every available seat in the room. In total, 14 research papers authored by JPMC employees were accepted to the workshop. With the growing interest and strong attendance in finance workshops, Tucker Balch and Manuela Veloso from the AI Research team are helping to organize the first international AI in Finance (ICAIF) conference in partnership with the Association for Computing Machinery (ACM), which will be held in New York City on October 15-16 in 2020.

December 2018: Montreal, Canada

Challenges and Opportunities for AI in Financial Services: the Impact of Fairness, Explainability, Accuracy, and Privacy

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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