Financial services industry has been going through rapid changes in recent years and new technology development has played a pivotal role in the process. The current pandemic has further accelerated the pace of technology innovation and adoption, and at the same time presented new challenges as well as opportunities. Please join MIT thought leaders and startups for a series of discussions on the new trends in financial services and the driving forces behind them, including FinTech, BigTech, AI, and other disruptive technologies that will transform and reshape the future of the entire sector.
Sheri Brodeur is a Director of Corporate Relations at MIT. Prior to this, she spent 22 years at Hewlett-Packard Company in several roles. Her most recent position was in the HP Labs Strategy and Innovation Office. The role of this organization is to set HP Labs' research strategy and extend HP's internal research capacity by partnering with universities, governments, and other companies on a global scale to rapidly advance the positive impact of technology on the world.
Sheri spent 15 years with HP Labs, HP's corporate researcher center, managing major university alliances and programs, including a $25M program with MIT. She has been responsible for managing global higher education technology programs in the areas of Security, Digital Libraries (DSpace), Information Management, and Sustainability.
Prior to this role she spent the previous eight years at Hewlett-Packard in the sales organization moving from the position of Field Sales Engineer to Global Account Manager. In this role she was responsible for selling, supporting and delivering high end test and measurement solutions for the communications industry.
Brodeur has a BS in Ceramic Engineering from Alfred University and an MS in Solid State Science from the Materials Research Laboratory at Penn State University.
Dimitris Bertsimas is the Boeing Professor of Operations Research, the codirector of the Operations Research Center, and faculty director of the Master of Business analytics at MIT. His research interests include optimization, machine learning and applied probability and their applications in health care, finance, operations management, and transportation. Bertsimas has coauthored more than 200 scientific papers and four graduate level textbooks. He is the editor in Chief of INFORMS Journal of Optimization. He has supervised 67 doctoral students and is currently supervising 25 others. Bertsimas is a member of the National Academy of Engineering, an INFORMS fellow, and has received numerous prestigious research and teaching awards. He holds an SM in applied mathematics and a PhD in operations research from MIT.
We live in an era of unprecedented data, powerful algorithms, and computational capacity. Technology adoption rates are accelerating at an astounding pace. There are tremendous opportunities to be realized by using Analytics which combines the realms of data, modeling, and decisions for business insight and value. Real world problems are usually complex and often ill defined and often companies see the incredible power of this new capability but gaining adoption across the organization is a challenge. We will discuss both the opportunity to ‘operationalize analytics’ and provide solutions to help organizations move toward this new world with better, interpretable methods and organizational training and adoption strategies.
Daisy Zhuo is a cofounding partner of Interpretable AI. She has extensive experience developing business solutions using advanced predictive and prescriptive analytics and AI systems in a variety of industries, including healthcare, banking, insurance, and information technology. She holds a PhD in operations research from MIT, during which she developed a range of cutting-edge machine learning techniques such as Optimal Imputation and Robust Classifications, with publications in top academic journals.
Jack Dunn is a cofounding partner of Interpretable AI. He has developed many novel analytics approaches, including the Optimal Trees methodology, and has considerable experience applying machine learning and AI to problems in both research and industry settings. Dunn holds a PhD in operations research from MIT.
Current approaches to artificial intelligence such as deep learning are black boxes, which humans cannot understand. In contrast, Interpretable AI builds machine learning solutions that bridge the gap between interpretability and performance, delivering state-of-the-art results while allowing the solutions to be fully understood, audited, and trusted by everyone. The technology is based on cutting-edge research invented and pioneered by the co-founders. The Interpretable AI solutions have been adopted in many leading companies across a wide variety of industries including banking, insurance, manufacturing, and health care.
Jordan Levine is a partner at Dynamic Ideas, an organization committed to spreading powerful ideas in the areas of analytics, operations research, and their applications. He focuses his energy on creating digitally accessible training and education products that make analytics accessible to leaders. After serving as a communications officer in the United States Marine Corps, Jordan spent seven years at McKinsey & Company. The latter half of his time, he served as the global learning and development lead for analytics. There, he designed a strategy and oversaw a learning team that engaged ~4,000 McKinsey colleagues per year at the executive, manager, and technical talent levels. Key milestones included the creation of a cohort of 1,000+ ‘Analytics Translators’ and the development of novel approaches to on-board and integrate analytics technical talent as well as assess their technical competence in a business environment. Prior to leading analytics learning, he was an engagement manager in the operations practice with a focus in supply chain management. Jordan holds a Masters in Engineering from the Massachusetts Institute of Technology (MIT) and a Bachelors of Mathematics from the United States Naval Academy.
The Analytics Edge for Leaders is dedicated to supporting business and organizational leaders become "analytics equipped" leaders. We recognize that mid-career professionals with busy lives do not have the ability to return to a graduate program or spend hours learning to code. Thus, we focus on up-skilling leaders with the must have skills of today and position them to guide and lead analytics efforts. Our programs are designed for general managers, senior executives, consultants, data and technology specialists, functional leaders, individual contributors, and business owners.
Sheri Brodeur, Director of Corporate Relations, MIT Corporate Relations
Dimitris Bertsimas, Boeing Professor of Operations Research, MIT
Daisy Zhou, Cofounding Partner, Interpretable AI
Jack Dunn, Cofounding Partner, Interpretable AI
Jordan Levine, Partner, Dynamic Ideas
Dr. Bohn is the Chief Research & Innovation Officer and Head of Research & Engagement at the Swiss Re Institute. Most recently, he served as Chief Science Officer and Head of GX Labs at State Street Global Exchange in San Francisco. Before moving back to California, he established the Portfolio Analytics and Valuation Department within State Street Global Markets Japan in Tokyo. Dr. Bohn often conducts seminars on topics ranging from credit instrument valuation & portfolio management to machine learning. He has published widely in the area of credit risk. He co-authored with Roger Stein Active Credit Portfolio Management in Practice (Wiley, 2009). His recent research focuses on socially responsible machine intelligence, causal inference to improve machine-learning interpretability, natural-language processing to improve risk modeling, and on a range of machine-intelligence-enabled tools to assess company & urban risk plus resilience in environmental, social, & governance areas.