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.


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!

Kunhan Wu

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Kunhan Wu is a PhD student in Information Systems at Boston University, Questrom School of Business. He holds a bachelor's degree in Data Science at Northeastern University and master's degree in Information System Management at  Carnegie Mellon University. He is currently working on multi-agent framework with game theory and pretrain knowledge distillation.

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.
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​Nuo Yuan

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Nuo (Ben) Yuan is a Ph.D. student in the Operations and Technology Management
department at the Questrom School of Business, Boston University. His substantive
research interest includes topics in the OB-OM interface (with a special focus on corporate-level DEI, environmental sustainability, and CSR), finance-OM interface, and the economics of online platforms informed by methodological tools drawn from econometrics, field/lab experimentation, and machine learning. He holds a Bachelor’s degree in Mathematics and
Political Science.

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​. Yuan will start as a first year phd student at BU in 2024 September.
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Shihao Yang

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Shihao Yang is a PhD student in Information Systems at Boston University, Questrom School of Business. He holds a Bachelor’s degree in Statistics and Data Science from UW-Madison and a Master of Engineering degree in DS from UCLA.  His current research interests focus on AI's impact on improving information efficiency in online platforms and the use of machine learning tools to extract business insights from unstructured data on these platforms.

Runqing (Rayna) Yang

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Runqing (Rayna) Yang is a first-year PhD student in Business In Computer Information Systems at the University of North Texas. She holds a master's degree in Data Analytics from Boston University and previously worked as a biostatistician at a biotech company in Boston. Currently, her research focuses on multi-agent frameworks and analyzing unstructured data to discover unique business insights. In her free time, Rayna enjoys tennis, golf, and badminton, and has recently developed a passion for CrossFit.​

John Seon Keun Yi

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​John Seon Keun Yi is a PhD student in Computer Science at Boston University. He earned his Bachelors and Masters degrees in Computer Science from Georgia Institute of Technology. His research explores biases and misinformation in foundation models. Outside of research, John enjoys bouldering, weightlifting, and cooking.



Master's and Undergraduate Students

Junhui Cho

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Junhui Chi is currently a senior undergraduate at Boston University majoring in Computer Science. He has a profound interest in the field of generative AI and its transformative impacts in society, especially in business, and how they affect consumer behavior. He is passionate about leveraging machine learning and deep learning to address real-world challenges

​Daling Shi

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Daling Shi holds a master's degree in Computer Information Systems from Boston University. With experience of  building machine learning models and integrating generative AI into practical applications. Her research interests include analyzing large-scale data and harnessing various generative models to explore the transformative impact of AI on diverse fields.

Vrinda Kohli

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Vrinda Kohli is an undergraduate Computer Science student at Manipal University Jaipur, India. Her primary research interests lie within the domain of trustworthy machine learning and data privacy. She is also deeply engaged in computer vision, particularly generative architectures like GANs and diffusion based models.
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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. ​​

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. ​

Ian Tsai

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Ian Tsai is an undergraduate student from Boston University majoring in Computer Science. He is interested in full stack development and capitalizing on machine learning to address real-world problems. He is currently researching how big tech disrupts AI research and development.

​Vicky Dong

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Vicky Dong is a Master's student in the Computer Science-Align program at Northeastern University, Boston. With a dual academic background in Finance and Computer Science, her research interests include machine learning, big data models and data analytics, information systems, business research, and data mining.

Shuhan Wang

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Shuhan Wang is a master student of Data Science at Boston University. She also has a Bachelor's degree in Actuarial Science in Central University of Finance and Economics. Combined with her background and interests, she wants to use Language Models and Machine Learning to find out more correlationships between text message and business.

Pritam Pandit

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Pritam is a Master of Business Analytics student at the Questrom School of Business. He has a keen interest in the convergence of business and technology. Presently, he is delving into the potential of large language models to enhance and drive business value

Xinyu Zhang​

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​Xinyu Zhang is currently a master student in Data Science at Boston University. She obtained dual Bachelor's degrees in Data Science and Economics from University of International Business and Economics. She is driven by a passion for applying Generative AI across diverse fields to tackle real-world challenges, and also for exploring policy and ethical considerations surrounding them.

Karan Vyas

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Karan Vyas holds a Master’s degree in Artificial Intelligence from Boston University. Combining technical prowess with extensive business experience, he bridges the gap between both domains. Karan's research areas lie within Generative AI and Computer Vision, primarily focusing on practical applications in healthcare and autonomous systems. Adept at wearing multiple hats, he navigates various roles and scenarios to successfully drive initiatives. Karan also teaches AI and ML courses at MIT with iDTech Labs, encouraging students to explore the field of Artificial Intelligence.

​ Zehang Lin

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​Zehang Lin is currently a master's student in applied data analysis at Boston University, holding an undergraduate degree in software engineering. He has a strong interest in generative artificial intelligence, natural language processing, and large language models. He is passionate about exploring how these three fields can be integrated to address problems.

Yuezhu Zhao

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​Yuezhu Zhao is a graduate student in Financial Engineering at New York University Tandon School of Engineering. She holds a bachelor's degree in Applied Mathematics and a minor in CS. She is interested in unleashing the potential of large language models to solve real-world problems. She is committed to leveraging her skills to address complex challenges in the finance sector and beyond.



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)

Undergraduates
Esha Vaishnav

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

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