Rama Ramakrishnan

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Rama Ramakrishnan is a Professor of the Practice at the MIT Sloan School of Management.

His teaching, research, and advisory interests center on the practical application of Predictive and Generative AI techniques to problems and opportunities in industry and in the creation of intelligent products and services.

Prior to joining MIT Sloan, Rama was a tech entrepreneur and executive for over 20 years. He has founded or has been a senior executive in four software companies that have exited to technology titans: Oracle, Salesforce, and Demandware. He is active in the startup ecosystem as an advisor, angel investor, and board member.

Most recently, Rama was senior vice president at Salesforce (NYSE: CRM) and chief data scientist for Salesforce Commerce Cloud. In this role, he led Salesforce Einstein for Commerce—the analytics/machine-learning platform that powers Salesforce Commerce Cloud—and was responsible for product management, engineering, data science, and cloud production operations. The Einstein platform uses analytics techniques to predict and influence the shopping behavior of hundreds of millions of unique shoppers monthly.

The path that led Rama to Salesforce started in July 2010 when he founded a startup, CQuotient, to build a data-science-based personalization platform for retail and e-commerce. Backed by funding from Bain Capital Ventures, Rama built and grew the company to a successful exit to Demandware (NYSE: DWRE) in October 2014. As a member of the Demandware executive team, Rama was involved in the successful sale of Demandware to Salesforce in July 2016 for $2.8 billion. CQuotient technology, now known as Salesforce Einstein for Commerce, is one of the top B2C recommendation engines in the world and influences the shopping behavior of billions of consumers annually.

Prior to founding CQuotient, Rama taught analytics at MIT Sloan, was chief scientist and vp of R&D at ProfitLogic, was chief analytics officer and vp of R&D for the retail business of Oracle, founded two analytics companies, and was a consultant at McKinsey & Company.

Rama has a BTech degree from the Indian Institute of Technology, Chennai and MS and PhD degrees from MIT.

Recent Writing

Extract just what you need from long LLM responses (August 2024) Using LLMs in business: A few guidelines (May 2024) How to use LLMs as "helpers" to build and customize other LLMs (January 2024) Get better answers from ChatGPT by using custom instructions (December 2023)

How ChatGPT can answer complex questions and execute actions on your behalf using external tools - A non-technical explainer, June 14, 2023

The Road To ChatGPT - An Informal Explainer On How ChatGPT Was Built, March 5, 2023

How Big Should Your Sample Size Be? A Handy Little Formula Every Data Scientist Should Know, December 14, 2022

How to Build Good AI Solutions When Data Is Scarce, MIT Sloan Management Review, November 23, 2022

From Prediction to Action — How to Learn Optimal Policies From Data (4/4), August 12, 2021

From Prediction to Action — How to Learn Optimal Policies From Data (3/4), August 7, 2021

From Prediction to Action — How to Learn Optimal Policies From Data (2/4), July 21, 2021

From Prediction to Action — How to Learn Optimal Policies From Data (1/4), June 10, 2021

... more

Recent Press

Meet Khan Academy’s chatbot tutor, CNN, August 21, 2023

A technophobe's guide to chatbots, The Boston Globe, July 10, 2023

Honors

Ramakrishnan wins MIT teaching award

June 13, 2024

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