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  • June 2021
  • Technical Note

Introduction to Linear Regression

By: Michael Parzen and Paul Hamilton
This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical... View Details
Keywords: Linear Regression; Regression; Analysis; Forecasting and Prediction; Risk and Uncertainty; Theory; Compensation and Benefits; Mathematical Methods; Analytics and Data Science
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  • 01 Dec 2018
  • News

Alumni and Faculty Books for December 2018

step-by-step, room-by-room guidance on how to create a welcoming and functioning space that expresses your unique individuality. Breaking Through: Leadership Disciplines from Top Performing Staffing Firms by Mike Cleland View Details
  • 01 Nov 1999
  • Research & Ideas

John H. Patterson and the Sales Strategy of the National Cash Register Company, 1884 to 1922

objection, he acknowledged the legitimacy of the complaint, and then tried to counter. My method of taking orders, I presume, does not vary much from that of other managers. If the party calling is a... View Details
Keywords: by Walter A. Friedman
  • 2023
  • Article

MoPe: Model Perturbation-based Privacy Attacks on Language Models

By: Marvin Li, Jason Wang, Jeffrey Wang and Seth Neel
Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training... View Details
Keywords: Large Language Model; AI and Machine Learning; Cybersecurity
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  • Teaching Interest

Applied Business Analytics

Course Overview:

Business Analytics has become a core function in many firms today and is driving innovation in the form of new business and operating models. Data-driven decision-making requires understanding of statistics, computer... View Details

  • 2023
  • Working Paper

In-Context Unlearning: Language Models as Few Shot Unlearners

By: Martin Pawelczyk, Seth Neel and Himabindu Lakkaraju
Machine unlearning, the study of efficiently removing the impact of specific training points on the trained model, has garnered increased attention of late, driven by the need to comply with privacy regulations like the Right to be Forgotten. Although unlearning is... View Details
Keywords: AI and Machine Learning; Copyright; Information
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  • Teaching Interest

Data Science for Managers

  • Served as a teaching fellow; assisted MBA students with classroom coding exercises. 
  • Developed course materials, including new case studies, technical notes, and code notebooks students used to analzye case data. 
  • Developed interactive web... View Details
  • 06 Feb 2018
  • First Look

First Look at New Research and Ideas: February 6, 2018

and Machine Learning By: Choudhury, Prithwiraj, Evan Starr, and Rajshree Agarwal Abstract—The advent of artificial intelligence in the form of... View Details
  • February 2021
  • Tutorial

What is AI?

By: Tsedal Neeley
This video explores the elements that constitute artificial intelligence (AI). From its mathematical basis to current advances in AI, this video introduces students to data, tools, and statistical models that make a computer 'intelligent.' Through an explanation of... View Details
Keywords: Artificial Intelligence; Digital; Technological Innovation; Leadership; AI and Machine Learning; Mathematical Methods
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  • 2024
  • Working Paper

Using LLMs for Market Research

By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have rapidly gained popularity as labor-augmenting tools for programming, writing, and many other processes that benefit from quick text generation. In this paper we explore the uses and benefits of LLMs for researchers and practitioners... View Details
Keywords: Large Language Model; Research; AI and Machine Learning; Analysis; Customers; Consumer Behavior; Technology Industry; Information Technology Industry
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  • 01 Dec 1999
  • News

Covering the Issues

standards and social responsibility, technology, globalization, the School's Soldiers Field campus, and the essential contributions that women are making in the business world. While a lot has changed at HBS... View Details
Keywords: Susan Young, Deborah Blagg, and Garry Emmons
  • Article

Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

By: Eva Ascarza and Ayelet Israeli

An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details

Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods
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    Antonio Moreno

    Antonio (Toni) Moreno is the Sicupira Family Associate Professor in the Technology and Operations Management Unit. He teaches courses related to technology and operations management in the MBA, executive, and doctoral programs. Before joining HBS, he was an... View Details

    Keywords: retailing; internet; e-commerce industry
    • 22 Aug 2005
    • Research & Ideas

    The Hard Work of Failure Analysis

    outside facilitators, can help keep the process productive. Next, skills for managing a group process of analyzing a failure with a spirit of inquiry and sufficient understanding of the scientific method are... View Details
    Keywords: by Amy Edmondson & Mark D. Cannon
    • 2023
    • Article

    Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators

    By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill
    Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in... View Details
    Keywords: Regression Discontinuity Design; Analytics and Data Science; AI and Machine Learning
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      Eliminating unintended bias in personalized policies using Bias Eliminating Adapted Trees (BEAT) - PNAS

      An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those... View Details

      • 02 Aug 2022
      • Blog Post

      From HBS to Cutting-Edge Tech

      enough to join Ford as a Machine Learning Researcher. I wrote software, generated intellectual property, and talked about autonomous vehicles in international industry... View Details
      • 16 Nov 2020
      • Blog Post

      Flatiron School: Reflections from Summer 2020

      In the summer of 2020, HBS Career & Professional Development (CPD) partnered with Flatiron School to provide students with an opportunity to gain practical skills, statistics fundamentals, and real-life... View Details
      Keywords: All Industries
      • Research Summary

      Overview

      By: Iavor I. Bojinov
      Over the last decade, technology companies like Amazon, Google, and Netflix have pioneered data-driven research and development processes centered on massive experimentation. However, as companies increase the breadth and scale of their experiments to millions of... View Details
      • Forthcoming
      • Book

      The Experimentation Machine: Finding Product–Market Fit in the Age of AI

      By: Jeffrey J. Bussgang
      Leverage AI to be a 10x Founder

      Today’s most successful founders know that the startups that learn the fastest will win. In The Experimentation Machine, I reveal how AI is transforming the way startups find product-market fit and scale.... View Details
      Keywords: AI; Founder; Startup; AI and Machine Learning; Technology Adoption; Business Startups; Entrepreneurship; Market Entry and Exit
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