DM² Lab: Data Mining towards Decision Making

"We develop data-driven computational methods and intelligent systems to facilitate decision making." -- dm_square

Faculty

Meng Jiang

DM2 @ Github

Check our repositories!

Current Postdoc

Dr. Sobin Alosious: Lucy Postdoc Fellow (2024-)

AI for Material Science

Current Graduate Students

Mengxia Yu: PhD candidate (2020-) with CSE Select Fellowship

AI for Education: Natural Language Generation

Gang Liu: PhD candidate (2021-) with 2024-2025 IBM PhD Fellowship

AI for Science: Molecular Generative AI

Bang Nguyen: PhD candidate (2022-)

AI for Education: Simulation and Generation

Zheyuan (Frank) Liu: PhD candidate (2023-)

Trustworthy Generative AI and Machine Unlearning

Eric Inae: PhD student (2022-) with Dean's Fellowship

AI for Science: Graph Machine Learning

Hy Dang: PhD student (2022-)

AI Infrastructure: Tool-use Models

Noah Ziems: PhD student (2022-)

AI Infrastructure: Open-source LLMs

Zhaoxuan Tan: PhD student (2023-)

Personalized LLM and LLM for Personalization

Mengzhao Jia: PhD student (2023-)

Multimodal Models and Reasoning Models

Yihan Zhu: PhD student (2024-)

AI for Science: Foundation Model Training

Yining Lu: PhD student (2024-)

AI Training and Evaluation: Reinforcement Learning

Weijiang (Vicky) Li: PhD student (2026-)

AI for Science: Molecular Generative AI

Cesar Cervera: MSCSE student (2025-)

AI/LLM for Social Good

Current Undergraduate Student

Olivia Zino: REU (08/2024-)

AI for Education

Thomas Mitchell: REU (01/2025-)

Personalized LLMs / AI Ethics

Zach Petko: iTREDS Scholar (01/2025-)

AI as Coding Assistant

Vincent Andriacco: iTREDS Scholar (01/2025-)

AI as Coding Assistant

John Kim: iTREDS Scholar (01/2025-)

Safer AI with Unlearning

Katherine O'Roark (Saint Mary's College): iTREDS Scholar (01/2025-)

Safer AI with Unlearning

Max Johnson: REU (08/2025-)

Decentralized RAG

Patrick Williams: REU (08/2025-)

LLM for Circuit Design

Lang Li: REU (08/2024-12/2024, 01/2026-)

AI for Education

Current Highschool Student

Kaiyi Zhao (04/2025-): AI for Emotional Support and Mental Health
Vazgen Manukyan (08/2025-): Multimodal Generative AI for Education

Past Graduate Students

Daheng Wang: PhD (2021)

User Modeling, Graph Learning

Employment: Senior Applied Scientist at Amazon

Dissertation: Learning Complementarity and Dynamics for Contextual Behavior Modeling

Tong Zhao: PhD (2022) with Snap Fellowship

Graph Data Augmentation

Employment: Senior Research Scientist at Snap

Dissertation: Learning to Augment Data in Graphs

Wenhao Yu: PhD (2023) with Bloomberg Fellowship

LLM and Question Answering

Employment: Senior Research Scientist at Tencent

Dissertation: Improving Scientific Information Extraction with Text Generation

Qingkai Zeng: PhD (2024)

Taxonomy Construction

Employment: Postdoctoral Research Associate at Amazon; Assistant Professor at Nankai University

Dissertation: Learning Complementarity and Dynamics for Contextual Behavior Modeling

Zhihan Zhang: PhD (2025)

Instructing LLM

Employment: Applied Scientist at Amazon

Dissertation: Instructing Language Models as Intelligent Assistants

Lingbo Tong: PhD (2025); Joint PhD Program of Psychology and CSE

LLM for Mental Health

Employment: Assistant Professor at University of Wisconsin-Madison

Dissertation: Nonlinear Structural Equation Modeling with Text Data

Jianing Li: Master's Degree (2020)

Transfer Learning

Luke Siela: Master's Degree (2022)

Data Science

Employment: General Electric

Tianwen Jiang: Visiting PhD student (2018-2019)

Information Extraction

Employment: Tencent

Zhenyu Wu: Visiting PhD student (2024-2025)

LLM Reasoning

Past Undergraduate Students

Alvin Alaphat (01/2020-05/2020): Predicting outcomes of NSF projects from abstracts.
Xiangyu Dong (09/2019-05/2020): News generation using NLP.
Zaitang Li (09/2019-05/2020): Survey on natural language generation.
Matthew Malir (01/2018-05/2018): Actionable fraud detection.
Bo Ni (09/2019-02/2021): Graph learning for fraud detection.
Chan Hee (Luke) Song (09/2019-03/2020): Question answering for NER.
Yuhan (Tina) Wu (09/2018-05/2019): Supervised topic modeling.

Michael Lee: REU (05/2020-05/2021)

Social media analysis

Fangcong Yin: REU (09/2020-08/2021)

Diverse text generation

Joseph Kuebler: REU (01/2021-05/2021)

Scientific fact extraction

First authored in 1 IEEE ICBK

Ann Hermann: REU (05/2020-08/2021)

Extracting profiles and social networks from Chinese history text

Ryan Pairitz: REU (01/2022-05/2022)

Graph machine learning

Yunxiang Yan: REU (09/2021-08/2022)

Graph anomaly detection

Weike Fang: REU (01/2022-05/2023)

Natural langauge generation

Jackson Ballow: REU (01/2021-05/2023)

Graph machine learning

David Liu: REU (05/2023-12/2023)

Large language model

John Flanagan: REU (05/2023-12/2023)

Large language model

Jack Keller: REU (08/2025-12/2025)

Open-source LLM

Ethan Sotka: REU (08/2025-12/2025)

AI for Scientific Replication

Ralph Gonzalez: REU (08/2025-12/2025)

AI for Polymer Discovery

Christopher Bond: REU (08/2025-12/2025)

AI for Polymer Discovery

Tim Gunn: REU (08/2025-12/2025)

AI for Polymer Discovery

Luke Cao: REU (08/2025-12/2025)

AI Ethics

Past Highschool Students

Ishita Masetty (09/2022-12/2022): Analyzing LLM performance on emotional support
Jake Ciliberti (09/2022-12/2022): Analyzing graph data
Michael Florin (09/2019-07/2020): Analyzing peer responses on Reddit to suicidal ideation.
Eric Zhang (09/2018-07/2020): Predicting user gender based on clicked news articles.
Rebekah Fang and Libby Garnett (09/2020-12/2021): Predicting the category of emotional support in responses to suicidal thoughts: Won the second place in the 2021 Northern Indiana Regional Science and Engineering Fair. Recommended to the 33rd Annual Hoosier Science and Engineering Fair.
Albert Lu (05/2022-12/2024): First year at Culver Academies. Research on NLP and text classification. Published a first-author paper at KDD 2023 workshop. Won the first place in the 2024 Northern Indiana Regional Science and Engineering Fair.