Dokyun (DK) Lee
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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, spanning topics such as social media analytics, digital consumer management, persuasion, platform design, innovation, human-ai collaboration, our studies are focused on providing empirical evidence and empirical generalization to develop or extend consumer behavior and market theories. In particular, we study friction and solutions in applying cutting-edge technologies to business arising from human-technology interface.
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BITLAB Meeting March 31 2023
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PI: Dokyun "DK" Lee
KELLI QUESTROM CHAIR ​ASSOCIATE PROFESSOR
OF INFORMATION SYSTEMS MANAGEMENT & COMPUTING AND DATA SCIENCE
@ BOSTON UNIVERSITY 


Postdoctoral Researcher

Mohamed Zaki Balboula

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Dr. Mohamed Zaki Balboula is a postdoctoral researcher in the Information Systems Department at Boston University, Questrom School of Business. He also held an Assistant Professor of Accounting position at Delta University for Science & Technology- Egypt. He employs predictive models to predict corporate going concern/bankruptcy to support the auditor's judgment via rough sets theory, neural networks, and particle swarm algorithm using structured financial data. He is currently exploring ways to apply machine learning, NLP, to address various research questions in corporate finance using textual data. His research interests include corporate disclosures, environmental, social, and governance (ESG), corporate social responsibility (CSR), corporate risk, and financial performance.

Luigi Longo

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Luigi Longo is a postdoctoral researcher at the Questrom School of Business, Boston University.
He holds a Ph.D. in economics at the IMT School for Advanced Studies in Lucca. His main research interest lies in the application of interpretable AI - with a particular focus on shallow and deep neural networks - to time series analysis within the context of macroeconomic and financial market dynamics. He is also interested in leveraging deep learning and generative AI tools to unravel nuanced trends and insights in the labor market dynamics.

Doctoral Students

Zhaoqi Cheng

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Zhaoqi Cheng is an Information Systems PhD student at Boston University, Questrom School of Business. 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.

Chen Jing

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​​Chen Jing is a PhD student in Quantitative Marketing at Questrom School of Business, Boston University. His research interests include applying machine learning, econometrics, and statistical models to study brand communication, corporate social responsibility, and brand activism.

Chengfeng Mao

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Chengfeng Mao is a 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.

Eric Zhou

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Eric will be a first year quant marketing doctoral student at Wash U. He holds a Bachelor’s degree in Finance and Marketing from Washington University In St. Louis and MBA from Tepper. He worked for one year at Nielsen BASES as a research analyst specializing in product innovation. 
In his free time, he enjoys exercising and dancing and plans on choreographing his own piece some day!

Sungjoon Park

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Sungjoon Park is an incoming PhD student in Computing & Data Sciences at Boston University Fall 2023. He is equipped with an interdisciplinary academic background composed of economics and data science. He pursues studies in extracting business insights via applying machine learning and natural language processing. This research interest stems from his professional experience, through which he worked as an economist at LG Economic Research Institute conducting research on capturing patterns and trends implied in economic phenomena.

Hazel Hyeseung Kang

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Hazel Hyeseung Kang is a PhD student in Information Systems at Boston University, Questrom School of Business.
She holds a bachelor's degree in Economics at Yonsei University and master's degree in Economics at Yonsei University.
Her research interests include applying econometrics and machine learning to derive business insights from the voice of customers on online platforms.

Zhuoyan Ma

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​Zhuoyan Ma is a PhD student in Marketing at Boston University, Questrom School of Business. She holds a bachelor’s degree in Economics and Mathematics at Boston University and a master’s degree in Data Science at Columbia University. Her research interests include leveraging machine learning and econometrics models to learn business insights from unstructured data and to study the creator economy.

Zhengrong (Jenn) Gu

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Zhengrong (Jenn) Gu is a PhD student in Marketing at Boston University Questrom School of Business. Prior to joining BU, she received her M.S. in Data Science from Georgetown University. Her research interests include deploying machine learning and econometrics to improve firms' business strategies and help consumers in decision-making.
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Yi Liu

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Yi Liu is a PhD student in Computing & Data Sciences at Boston University in Fall 2023.  She holds a master’s degree in Data Analytics from University of Southern California. Her research interests include extracting customer psychological or behavioral patterns via applying large language models & NLP models, and deriving explainable business insights through deploying machine learning algorithms


Master's and Undergraduate Students

Yicun Wu

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Yicun is pursuing a Master's in Artificial Intelligence at Boston University. His interdisciplinary research intersects neuroscience, cognitive science, statistics, and machine learning. Yicun is keen on enhancing the efficiency of AI models by aligning them with human cognitive processes, incorporating techniques like SITHCon's logarithmically compressed temporal representation. 

​​Yusen Wu

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​Yusen Wu is a senior undergraduate pursuing a dual degree in Statistics and Business Administration at Boston University. His research interest lies at the intersection of business and machine learning. He is currently working on large-scale pretrained language models to draw insights from unstructured text. ​​

Animikh Aich

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​Animikh is pursuing his M.S. in Artificial Intelligence at Boston University. He previously led a team of vision engineers to build real-time video analytics solutions in the industry. His research interests include autonomous systems, self-supervised learning, and generative AI. 

Jingran Xu

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Jingran Xu is an M.S. Applied Business Analytics candidate at Boston University. She got her BS degree in E-commerce. Her research interests include applying data-driven and technology-enabled methods to solve marketing and operation problems.

Esha Vaishnav

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Esha Vaishnav is an undergraduate student from Boston University pursuing her bachelor's in Biomedical Engineering. She has interests in data science and the utilization of ML to provide solutions to medical issues in device development and research. ​

Manyuan Lu

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Manyuan Lu is a recent graduate from Boston University with a dual degree in Computer Science (BA/MS). Her research interests include artificial intelligence and machine learning. She is excited to be joining the BIT Lab as a Research Assistant. She is eager to apply her knowledge and skills to make a meaningful impact in various industries such as healthcare, society, and transportation. ​

Yuan Gao

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Yuan Gao is a senior undergraduate student in Economics and Data Science in Beijing Normal University. His research interest lies in exploring how AI impacts the formation and diffusion of human beliefs on social media, and investigating the resulting business, economic, and social implications​

​​Amrutha Karthikeyan

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I am Amrutha Karthikeyan, currently pursuing MS in Applied Data Analytics at BU. I got my B.Tech. degree in Bioinformatics. I am a data-driven individual with a passion for using Data Science / Machine learning to develop innovative solutions that positively impact the healthcare industry. ​​

Chun Zhou ​

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Chun Zhou graduated from MSBA at BU Questrom and currently works as a data scientist. She got BS in Applied Mathematics from the University of Toronto. She is exploring research interests in Generative AI and LLM.

Ebrahim Arian

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Ebrahim completed his MSBA program at Worcester Polytechnic Institute (WPI) and is presently employed as an intern in the role of Generative AI Engineer. Prior to this, he earned his BS in Industrial Engineering, where he concentrated on machine learning algorithms. Throughout his master's studies, Ebrahim undertook several projects centered around NLP.

Aditya Bala

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Aditya is a Master of Science Graduate student at Boston University, studying Data Analytics. His research interests are focused on Natural Language Processing, Computer Vision, and Data Science. Ultimately, Aditya aspires to become a leading expert in Data Science and contribute to the development of innovative solutions that make a positive impact on society.

Divya Kumari

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Divya Kumari is pursuing her master's in Computer and Information Science at the University of Pennsylvania. With valuable experience as a Software Engineer at Cisco Systems and a focus on Natural Language Processing and Generative AI, she's passionate about harnessing technology to address real-world challenges.

Chung-Yeh Yang

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Chung-Yeh Yang is a senior undergraduate student in Boston University majoring in Data Science and minoring in Business Administration. His research interests include applying machine learning to improve the decision-making process of firms and deploying large language model to create unique chat models. ​

Handi Xie

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Handi is pursuing M.S. in Computer Science at Boston University. He earned his undergraduate degree in Computer Science from the University of Illinois at Urbana-Champaign. Following his graduation, he joined Tantan 探探 in Beijing, China, as a data scientist, where he led several marketing and advertising initiatives. Handi is now researching on generative models, simulated agents, and prompt engineering.


Affiliated Industry Leaders & Scholars

Christina Van Houten 
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Technology Executive & Board of Many Tech Companies
Founder of Women@Work &Unbiased|AI

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Christina is a veteran of the enterprise technology industry, having spent two decades with some of the world’s largest firms, including Oracle, IBM and Infor Global Solutions as well as Netezza and ProfitLogic, the entrepreneurial companies that were acquired by them.
Most recently, Christina was the Chief Strategy Officer for Mimecast (NASDAQ: MIME), a global leader in cyber-security, where she led Product Management, Market Strategy, Corporate Development, and M&A and also served as an employee Board Officer. Currently, Christina continues to be an Advisor to the CEO at Mimecast while also serving on the Board of Directors for TechTarget (NASDAQ: TTGT). She is also involved an Advisory Board member for several emerging technology firms, including Theatro, Ludis Analytics and Teikametrics.
Prior to evolving into the technology sector, Christina founded a women’s athletic apparel brand and spent her younger years focused on public interest work with The John D. & Catherine T. MacArthur Foundation, DC City Government, U.S. Treasury Department, and several political campaigns. In 2017, she launched a resource platform dedicated to the economic advancement and self‐reliance of women and girls around the world called Women@Work, which includes several books, a mentor matching program, and other related initiatives.
Christina earned a BA in Government and Theology from Georgetown University and attended the University of Chicago Booth School of Business where she received an MBA in Business Strategy. Originally from Oklahoma, Christina now resides in Boston with her husband and two teenage sons. 


Graduated

PhD
Emaad Manzoor: Assistant Professor at  Cornell University (previously U of Wisconsin-Madison)
Vitaly Meursault (Thesis Committee) [Federal Reserve]
Domonkos Ferenc Vamossy (Thesis Committee) [Amazon]
Daehwan Ahn (Co-author), The Wharton School PostDoc [Faculty at University of Georgia]
Federico Siano (Thesis External Reader) [Faculty at UTDallas]
Qinglai He (Co-author, General Advising) [Faculty at University of Wisconsin-Madison]
Dongwon Lee, (Reader, Thesis Committee, Co-author) [Faculty at HKUST]
Shunyuan Zhang (Co-author, general advising) [Faculty at HBS]
June Shi (Co-author, general advising) [Faculty at HKUST]

Master's Student
Alka Isac, Independent Study (Natural Language Processing using Deep Learning) (Fall 2016)
Adit Bharat Sanghvi, Independent Study (Machine Learning and Recommender Systems) (Spring 2017)
Sahil Gupte, Independent Study (Neural Networks and Word Embeddings) (Mini 4 2017)
Maksim Khaitovich, Independent Study (Deep Learning in Business) (Mini 4 2017, Fall 2017, 2018)
Jiati Le, Internship (Vision Algorithm in Real Estate) (Summer 2017)
Sangmin Cho, Internship (Vision Algorithm in Fashion) (Summer 2017, Fall 2017)
Akshay Thorat, Independent Study (Application of Generative Adversarial Networks) (Spring 2018)
Aniket Jain, Independent Study (Application of Generative Adversarial Networks) (Spring 2018)
Rohan Sangave, Independent Study (Interpretable Deep Learning Based Text Mining) (Summer, Fall 2018)
Harsh Johari, Independent Study (Project Management Insight Mining) (Summer, Fall 2018)
Adarsh Rajkumar Saboo, Independent Study (Project Management Insight Mining) (Summer, Fall 2018)
Yichen Chen (Tsinghua University), Independent Study (Heterogeneous Treatment Effect) (Summer 2018)
Philipp Schneider, Independent Research (Quantitative Persuasion) (Spring 2019)
Stella Xinci Weng, Independent Study (Deep Learning in Business) (Spring 2019, Fall 2019)
Yan Gao (Deep Learning for Patents) (Spring 2020)
Yuan Zhou (Deep Learning for Patents) 
Manyuan Lu (Generative AI)

"Causal Inference without Data Mining is Myopic and Data Mining without Causal Inference is Blind"

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