Supervised Machine Learning - Publications - Faculty & Research - Harvard Business School

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Teaching Interest

Overview

Teaching has been a lifelong passion of mine. As the third generation of academics in my family, I see good teaching as a means to give back and to encourage others to share my passion for discovery. I’ve been very lucky to have many teaching opportunities, both as an... View Details

Forthcoming
Article

Serving with a Smile on Airbnb: Analyzing the Economic Returns and Behavioral Underpinnings of the Host’s Smile

By: Shunyuan Zhang, Elizabeth Friedman, Kannan Srinivasan, Ravi Dhar and Xupin Zhang

Non-informational cues, such as facial expressions, can significantly influence judgments and interpersonal impressions. While past research has explored how smiling affects business outcomes in offline or in-store contexts, relatively less is known about how smiling... View Details

Keywords: Sharing Economy; Airbnb; Image Feature Extraction; Machine Learning; Facial Expressions; Prejudice and Bias; Nonverbal Communication; E-commerce; Consumer Behavior; Perception

December 2018
Case

Choosy

By: Jeffrey J. Bussgang and Julia Kelley

Founded in 2017, Choosy is a data-driven fashion startup that uses algorithms to identify styles trending on social media. After manufacturing similar items using a China-based supply chain, Choosy sells them to consumers through its website and social media pages.... View Details

Article

A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects

By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun

We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public... View Details

Keywords: Prescriptive Analytics; Heterogeneous Treatment Effects; Optimization; Observed Rank Utility Condition (OUR); Between-treatment Heterogeneity; Machine Learning; Decision Making; Analysis; Mathematical Methods

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Web

Hands-on Learning About Global Markets | MBA

Hands-on Learning About Global Markets By Jennifer Gillespie on September 21, 2023 Share via Facebook Share via LinkedIn Print Share via email The challenge posed to students in HBS’s FIELD Global Capstone (FGC) course sounds a bit like a... View Details

October 2018
Case

American Family Insurance and the Artificial Intelligence Opportunity

By: Rajiv Lal and Scott Johnson

2020
Article

A Practical Approach to Sales Compensation: What Do We Know Now? What Should We Know in the Future?

By: Doug J. Chung, Byungyeon Kim and Niladri B. Syam

Personal selling represents one of the most important elements in the marketing mix, and appropriate management of the sales force is vital to achieving the organization’s objectives. Among the various instruments of sales management, compensation plays a pivotal role... View Details

Keywords: Sales Compensation; Sales Management; Sales Strategy; Principal-agent Theory; Structural Econometrics; Field Experiments; Machine Learning; Artificial Intelligence; Salesforce Management; Compensation and Benefits; Motivation and Incentives; AI and Machine Learning

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2024
Working Paper

Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python

By: Melissa Ouellet and Michael W. Toffel

This paper describes a range of best practices to compile and analyze datasets, and includes some examples in Stata, R, and Python. It is meant to serve as a reference for those getting started in econometrics, and especially those seeking to conduct data analyses in... View Details

Keywords: Empirical Methods; Empirical Operations; Statistical Methods And Machine Learning; Statistical Interferences; Research Analysts; Analytics and Data Science; Mathematical Methods

2020
Working Paper

Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion

By: Ryan Allen and Prithwiraj Choudhury

Past research offers mixed perspectives on whether domain experience helps or hurts algorithm-augmented work performance. To reconcile these perspectives, we theorize that domain experience affects algorithm-augmented performance via two distinct countervailing... View Details

Keywords: Automation; Domain Experience; Algorithmic Aversion; Experts; Algorithms; Machine Learning; Decision-making; Future Of Work; Employees; Experience and Expertise; Decision Making; Performance

2021
Chapter

Towards a Unified Framework for Fair and Stable Graph Representation Learning

By: Chirag Agarwal, Himabindu Lakkaraju and Marinka Zitnik

As the representations output by Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes important to ensure that these representations are fair and stable. In this work, we establish a key connection between counterfactual... View Details

Keywords: Graph Neural Networks; AI and Machine Learning; Prejudice and Bias

29 Aug 2018
Blog Post

From the Classroom to the Workplace: How I Applied Learnings to my Internship

The first year at Harvard business School gives you a breadth of courses to sink your teeth into. One of the real benefits of studying such a range of materials in the first year, is how easily I was able to apply my learnings while... View Details

Keywords: Consumer Products / Retail

January–February 2022
Article

Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion

By: Ryan Allen and Prithwiraj Choudhury

How does a knowledge worker’s level of domain experience affect their algorithm-augmented work performance? We propose and test theoretical predictions that domain experience has countervailing effects on algorithm-augmented performance: on one hand, domain experience... View Details

Keywords: Automation; Domain Experience; Algorithmic Aversion; Experts; Algorithms; Machine Learning; Future Of Work; Employees; Experience and Expertise; Decision Making; Performance

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June 30, 2020
Article

Scaling Up Behavioral Science Interventions in Online Education

By: Rene F. Kizilcec, Justin Reich, Michael Yeomans, Christoph Dann, Emma Brunskill, Glenn Lopez, Selen Turkay, Joseph J. Williams and Dustin Tingley

Online education is rapidly expanding in response to rising demand for higher and continuing education, but many online students struggle to achieve their educational goals. Several behavioral science interventions have shown promise in raising student persistence and... View Details

Keywords: Online Learning; Behavioral Interventions; Scale; Education; Online Technology; Performance Improvement

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2020
Article

Public Sentiment and the Price of Corporate Sustainability

By: George Serafeim

Combining corporate sustainability performance scores based on environmental, social, and governance (ESG) data with big data measuring public sentiment about a company’s sustainability performance, I find that the valuation premium paid for companies with strong... View Details

Keywords: Sustainability; ESG; ESG (Environmental, Social, Governance) Performance; Investment Management; Investment Strategy; Big Data; Machine Learning; Environment; Environmental Sustainability; Corporate Governance; Performance; Asset Pricing; Investment; Management; Strategy; Human Capital; Public Opinion; Value; Analytics and Data Science

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26 Apr 2020
Other Presentation

Towards Modeling the Variability of Human Attention

By: Kuno Kim, Megumi Sano, Julian De Freitas, Daniel Yamins and Nick Haber

Children exhibit extraordinary exploratory behaviors hypothesized to contribute to the building of models of their world. Harnessing this capacity in artificial systems promises not only more flexible technology but also cognitive models of the developmental processes... View Details

Keywords: Exploratory Learning Behaviors; Modeling; Artificial Intelligence; AI and Machine Learning

November 2024
Supplement

AlphaGo (C): Birth of a New Intelligence

By: Shikhar Ghosh and Shweta Bagai

This case, the final of a three-part series, explores DeepMind's pivotal transition from mastering games to solving real-world scientific challenges. In December 2020, DeepMind's AI system AlphaFold 2 achieved a breakthrough by solving protein folding—a 50-year-old... View Details

Keywords: AI; Artificial Intelligence; Machine Learning; Research; Autonomy; Deep Learning; Drug Discovery; Healthcare Innovation; Neural Networks; Information Technology; Research And Development; Scientific Research; Technology Startup; AI and Machine Learning; Technological Innovation; United States

August 2018 (Revised October 2019)
Case

C3.ai—Driven to Succeed

By: Robert Simons and George Gonzalez

CEO Tom Siebel navigates his artificial intelligence (ai) startup through a series of pivots, market expansions, and even an elephant attack to become a leading platform ad service provider. The case describes his unusual management approach emphasizing employee... View Details

December 2024
Case

Blue Cross Blue Shield of Michigan (BCBSM): The AI Journey

By: Shikhar Ghosh

In early 2024, Bill Fandrich, Executive VP and CIO of Blue Cross Blue Shield of Michigan (BCBSM), faced a critical decision about AI adoption within the organization. Fandrich had championed AI implementation at BCBSM. After successfully developing three AI... View Details

March 2019
Case

DayTwo: Going to Market with Gut Microbiome

By: Ayelet Israeli and David Lane

DayTwo is a young Israeli startup that applies research on the gut microbiome and machine learning algorithms to deliver personalized nutritional recommendations to its users in order to minimize blood sugar spikes after meals. After a first year of trial rollout in... View Details

January–February 2025
Article

Want Your Company to Get Better at Experimentation?: Learn Fast by Democratizing Testing

By: Iavor Bojinov, David Holtz, Ramesh Johari, Sven Schmit and Martin Tingley

For years, online experimentation has fueled the innovations of leading tech companies, enabling them to rapidly test and refine new ideas, optimize product features, personalize user experiences, and maintain a competitive edge. The widespread availability and lower... View Details

Keywords: Technological Innovation; AI and Machine Learning; Analytics and Data Science; Product Development; Competitive Advantage

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