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- Awards
INFORMS Data Mining Best Paper Award
Winner of the 2017 INFORMS Data Mining Best Paper Award for ”Learning Cost-Effective and Interpretable Treatment Regimes” with Cynthia Rudin. View Details
- 26 Nov 2012
- News
La mine d’or du Big Data
- Article
Mining Big Data to Extract Patterns and Predict Real-Life Outcomes
By: Michal Kosinki, Yilun Wang, Himabindu Lakkaraju and Jure Leskovec
Kosinki, Michal, Yilun Wang, Himabindu Lakkaraju, and Jure Leskovec. "Mining Big Data to Extract Patterns and Predict Real-Life Outcomes." Psychological Methods 21, no. 4 (December 2016): 493–506.
- May 2017 (Revised March 2018)
- Case
Predicting Consumer Tastes with Big Data at Gap
By: Ayelet Israeli and Jill Avery
CEO Art Peck was eliminating his creative directors for The Gap, Old Navy, and Banana Republic brands and promoting a collective creative ecosystem fueled by the input of big data. Rather than relying on artistic vision, Peck wanted the company to use the mining of big... View Details
Keywords: Retailing; Preference Elicitation; Big Data; Predictive Analytics; Artificial Intelligence; Fashion; Marketing; Marketing Strategy; Marketing Channels; Brands and Branding; Consumer Behavior; Demand and Consumers; Analytics and Data Science; Forecasting and Prediction; E-commerce; Apparel and Accessories Industry; Consumer Products Industry; Fashion Industry; Retail Industry; United States; Canada; North America
Israeli, Ayelet, and Jill Avery. "Predicting Consumer Tastes with Big Data at Gap." Harvard Business School Case 517-115, May 2017. (Revised March 2018.)
- Fast Answer
Text Mining Resources
Baker Library has licensed the following newspapers for data mining from ProQuest. Currently, the... View Details
- November 2017
- Teaching Note
Predicting Consumer Tastes with Big Data at Gap
By: Ayelet Israeli and Jill Avery
CEO Art Peck was eliminating his creative directors for The Gap, Old Navy, and Banana Republic brands and promoting a collective creative ecosystem fueled by the input of big data. Rather than relying on artistic vision, Peck wanted the company to use the mining of big... View Details
Keywords: Brands; Brand ＆ Product Management; Big Data; ＂Marketing Analytics＂; Consumer Behavior; Predictive Analytics; Forecasting; Preferences; Operation Management; Distribution Channels; Marketing; Marketing Channels; Marketing Strategy; Brands and Branding; Forecasting and Prediction; Data and Data Sets; Retail Industry; Fashion Industry; Apparel and Accessories Industry; United States; North America
- December 2022 (Revised January 2025)
- Case
Akooda: Charging Toward Operational Intelligence
By: Christopher Stanton and Mel Martin
The Akooda case describes the challenges confronting founder and CEO Yuval Gonczarowski (MBA ‘17) in 2022 as he attempts to boost sales. Launched in November 2020, Akooda was an AI company that mined 20 different sources of digital data, from tools like Slack, Google... View Details
Keywords: Data Mining; Productivity; Monitoring; Data Analysis; AI and Machine Learning; Knowledge Management; Operations; Problems and Challenges; Employee Relationship Management; Information Technology Industry; Technology Industry; Information Industry; Boston; Israel
Stanton, Christopher, and Mel Martin. "Akooda: Charging Toward Operational Intelligence." Harvard Business School Case 823-018, December 2022. (Revised January 2025.)
- 01 Dec 2014
- News
Making Big Data Fashionable
get designs to consumers in as little as four weeks—and at an affordable price. In 2012, Moon—who has a background in fashion design, investment banking, corporate strategy, and social commerce startups—launched Trendalytics, a visual analytics platform that View Details
- Teaching Interest
Overview
Paul is primarily interested in teaching data science to management students through the case method. This includes technical topics (programming and statistics) as well as higher-level management issues (digital transformation, data governance, etc.) As a research... View Details
Keywords: A/B Testing; AI; AI Algorithms; AI Creativity; Algorithm; Algorithm Bias; Algorithmic Bias; Algorithmic Fairness; Algorithms; Analytics; Application Program Interface; Artificial Intelligence; Causality; Causal Inference; Computing; Computers; Data Analysis; Data Analytics; Data Architecture; Data As A Service; Data Centers; Data Governance; Data Labeling; Data Management; Data Manipulation; Data Mining; Data Ownership; Data Privacy; Data Protection; Data Science; Data Science And Analytics Management; Data Scientists; Data Security; Data Sharing; Data Strategy; Data Visualization; Database; Data-driven Decision-making; Data-driven Management; Data-driven Operations; Datathon; Economics Of AI; Economics Of Innovation; Economics Of Information System; Economics Of Science; Forecast; Forecast Accuracy; Forecasting; Forecasting And Prediction; Information Technology; Machine Learning; Machine Learning Models; Prediction; Prediction Error; Predictive Analytics; Predictive Models; Analysis; AI and Machine Learning; Analytics and Data Science; Applications and Software; Digital Transformation; Information Management; Digital Strategy; Technology Adoption
- Article
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error
By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details
Keywords: Autoencoder Networks; Pattern Detection; Subset Scanning; Computer Vision; Statistical Methods And Machine Learning; Machine Learning; Deep Learning; Data Mining; Big Data; Large-scale Systems; Mathematical Methods; Analytics and Data Science
Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error." Proceedings of the International Joint Conference on Artificial Intelligence 29th (2020).
- Article
Private and Civil Society Governors of Mercury Pollution from Artisanal and Small-scale Gold Mining: A Network Analytic Approach
By: Kristin Sippl
Artisanal and small-scale gold mining (ASGM) is both a subsistence livelihood for millions of people and the leading source of mercury pollution globally. The United Nation’s 2013 Minamata Convention on Mercury aims to address this challenge, but such public regulatory... View Details
Keywords: Artisanal And Small-scale Mining (ASM); Private Governance; Gold; Mercury; Mining; Governance; Networks; Pollutants; Research
Sippl, Kristin. "Private and Civil Society Governors of Mercury Pollution from Artisanal and Small-scale Gold Mining: A Network Analytic Approach." Extractive Industries and Society 2, no. 2 (April 2015): 198–208.
- January 2022
- Article
The Private Impact of Public Data: Landsat Satellite Maps Increased Gold Discoveries and Encouraged Entry
By: Abhishek Nagaraj
How does public data shape the relative performance of incumbents and entrants in the private sector? Using a simple theoretical framework, I argue that public data reduces investment uncertainty, facilitates the discovery of new market opportunities and increases the... View Details
Keywords: Public Data; Maps; Gold; Microeconomic Behavior; Economics; Data and Data Sets; Private Sector; Market Entry and Exit; Mining
Nagaraj, Abhishek. "The Private Impact of Public Data: Landsat Satellite Maps Increased Gold Discoveries and Encouraged Entry." Management Science 68, no. 1 (January 2022): 564–582.
- 2015
- Article
Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and... View Details
Speakman, Skyler, Edward McFowland III, and Daniel B. Neill. "Scalable Detection of Anomalous Patterns With Connectivity Constraints." Journal of Computational and Graphical Statistics 24, no. 4 (2015): 1014–1033.
- 2011
- Article
Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and... View Details
- 13 Dec 2021
- News
The Unlikely Upside of Mergers: More Diverse Management Teams
- June 2014 (Revised July 2014)
- Background Note
An Overview of Project Finance and Infrastructure Finance—2014 Update
By: Benjamin C. Esty, Carla Chavich and Aldo Sesia
Provides an introduction to the fields of project finance and infrastructure finance, and gives a statistical overview of project-financed investments over the years from 2009 to 2013. Examples of project-financed investments include the Kashagan oil field development... View Details
Keywords: Globalization; Capital Expenditures; International Finance; Data; Financial History; Economic Development; Corporate Governance; Contracts; Industry Analysis; Banking; Capital Investments; Municipal Finance; Project Finance; Infrastructure; Investment; Projects; Trends
Esty, Benjamin C., Carla Chavich, and Aldo Sesia. "An Overview of Project Finance and Infrastructure Finance—2014 Update." Harvard Business School Background Note 214-083, June 2014. (Revised July 2014.)
- Research Summary
Customer Intelligence
- Data and Reality Mining for Business Applications
- Business Value of Social Networks
- Customer Behavior Patterns
- Analitical Customer Relationship Management
- 06 Aug 2024
- Op-Ed
What the World Could Learn from America's Immigration Backlash—100 Years Ago
immigrants with that of more recent, non-European immigrants to the US, they conclude that the pace of immigrant assimilation today is similar to what prevailed 100 years ago. When interpreting evidence from the past, it is important to note that historical View Details
Keywords: by Marco Tabellini
- 02 Sep 2020
- News
Inflation Is Higher Than the Numbers Say
- February 2018
- Case
Rosslyn Resource: Monetization and Sales Strategy
By: Robert J. Dolan and Sunru Yong
Rosslyn Resource identifies exploration targets (potential mineral deposits) in the mining industry and advances them until the project can be monetized, usually through sale to a larger mining company, in return for an upfront fee and a royalty on future revenues.... View Details
Keywords: Strategy; Decision Choices and Conditions; Business Model; Organizational Change and Adaptation; Mining Industry
Dolan, Robert J., and Sunru Yong. "Rosslyn Resource: Monetization and Sales Strategy." Harvard Business School Brief Case 918-509, February 2018.