Business Insights through Text
The BIT LAB

We explore, examine, and extract consumer behavior or market insights through abundantly available, yet severely untapped text data. Via a variety of methodologies including causal inference, generative models, deep learning, neural NLP, bayesian statistics, interpretable machine learning, etc spanning topics such as social media analytics, digital consumer management, persuasion, patents, and promotion, our studies are focused on providing empirical evidence and empirical generalization to develop or extend consumer behavior and market theories. 

Doctoral Students

Emaad Manzoor

Emaad Manzoor is a PhD student in Information Systems at the Heinz College, CMU. He works on machine learning and causal inference methodology for data with complex structure, such as networks and text. Substantively, he examines causal questions pertaining to persuasion and its linguistic determinants.

Zhaoqi Cheng

Zhaoqi Cheng is a PhD student in Business Technology at Tepper School of Business, CMU. He combines machine learning with econometrics models to explore large-scale data with text-heavy attributes, such as patent files, online forums and user reviews. He is currently working on generative models related to the representation and characterization of innovations.

Samuel Levy

​Sam Levy is a Marketing Ph.D. candidate in the Tepper School of Business, CMU. He uses and combines Bayesian {statistics, machine learning and econometrics} to (1) build predictive models of browsing and buying behavior using unstructured data (2) flexibly model consumer behavior and make policy recommendations for pricing and promotional strategies. 

Chengfeng Mao

Chengfeng Mao is an incoming PhD student in Marketing at the MIT Sloan School of Management. He obtained his master's degree in Computer Science at Carnegie Mellon University. His research interests include applying machine learning to draw business and economic insights from unstructured data, such as text, image, and network graph.

Master's Students

Eric Zhou

Eric is a second year MBA student studying Business Technologies and Operations Research at Tepper. He holds a Bachelor’s degree in Finance and Marketing from Washington University In St. Louis and worked for one year at Nielsen BASES as a research analyst specializing in product innovation. Eric plans to pursue a PhD in Quantitative Marketing.
In his free time, he enjoys exercising and dancing and plans on choreographing his own piece some day!

Yuxin Yao

Master in Information System Management – BIDA. Recently researching in predicting patent value with deep learning methods.

Chaaran Arunachalam​

Chaaran is a graduate student pursuing Masters in Mechanical Engineering, with a focus on Machine Learning and Artificial Intelligence. His research interests include developing deep learning solutions for sequential data and reinforcement learning.

Yuan Zou

​Yuan is a graduate student in School of Heinz - Public Policy and Data Analytics. Her research interest in NLP grew during final year where she constructed a simple neural network for stock price prediction. She holds a bachelor's degree from Nanyang Technological University in Infocomm and have worked in financial industry for 3 years. She loves playing mahjong, reading about politics, and backpacking to many corners of the world.

Pragya Jain​

Kylie Huang

Kaiqi Zhong

Pragya is a graduate student in ‘Statistics and Data Science’ department at CMU. She is an Associate Actuary from Institute and Faculty of Actuaries, UK and has worked in the insurance industry for 4 years. Her interests include applying statistical machine learning to inform business decisions, generate insights for product pricing and aid policy design.​

​Kylie is a graduate student in Information System Management - Business Intelligence and Data Analytics program at Heinz College. Before that, she holds a graduate degree in statistics at CMU. She is interested in extracting actionable or impactful business insights from the structure and unstructured dataset using statistics or machine learning algorithms. During her free time, she loves running and making origami. 

Kaiqi is a graduate student at Heinz College majoring in Information System Management - BIDA. He is always curious about how causal inference and machine learning can be applied and interpreted in the business scenarios. He is a big fan of football, video games and rock music.