Maximillian L. Chen
I am a 2nd-year PhD Candidate in Computer Science at Columbia University advised by Zhou Yu.
✉️ maxchen AT cs DOT columbia DOT edu
Research Interest: Dialogue Systems; Syntax; Multimodal NLP
I received my Bachelors at Cornell University, where I worked with Prof. Lillian Lee and Dr. Jack Hessel, Prof. Rene Kizilcec, and Prof. Joe Guinness.
My PhD is supported by a GFSD fellowship.
I completed my Candidacy Exam on Multiparty Conversation Modeling. You can find the talk slides here .
 M. Chen, Z. Yu Pre-Finetuning for Few-Shot Emotional Speech Recognition
 M. Chen, X. Yu, W. Shi, U. Awasthi, Z. Yu Controllable Mixed-Initiative Dialogue Generation through Prompting
 M. Chen, A. Papangelis, C. Tao, S. Kim, A. Rosenbaum. Y. Liu, Z. Yu, D. Hakkani-Tur PLACES: Prompting Language Models for Social Conversation Synthesis
Findings of EACL 2023
 M. Chen*, C. Chen*, X. Yu* and Z. Yu FastKASSIM: A Fast Tree Kernel-Based Syntactic Similarity Metric
 M. Chen, A. Papangelis, C. Tao, A. Rosenbaum, S. Kim, Y. Liu, Z. Yu, D. Hakkani-Tur Weakly Supervised Data Augmentation Through Prompting for Dialogue Understanding
SyntheticData4ML @ NeurIPS 2022
 M. Chen, W. Shi, F. Yan, R. Hou, J. Zhang, S. Sahay and Z. Yu Seamlessly Integrating Factual Information and Social Content with Persuasive Dialogue
 R. Kizilcec, M. Chen, K. Jasinska, M. Madaio and A. Ogan Mobile Learning During School Disruptions in Sub-Saharan Africa
AERA Open Vol. 7 No. 1 (Special Topic Collection on Educational Data Science)
 M. Chen and R. Kizilcec Return of the Student: Predicting Re-Engagement in Mobile Learning
Educational Data Mining 2020
 R. Kizilcec and M. Chen Student Engagement in Mobile Learning via Text Message
ACM Conference on Learning @ Scale 2020
 J. Guinness, D. Bhattacharya, J. Chen, M. Chen, and A. Loh An Observational Study of the Effect of Nike Vaporfly Shoes on Marathon Performance
- Amazon Science - Research/Applied Scientist Intern (Summer 2022), Alexa AI - Conversation Modeling
- Microsoft - Software Engineer Intern (Summer 2020), Excel - Data Visualization and Experiences
- Morgan Stanley - Technology Summer Analyst (Summer 2019), Enterprise Visualization and Analytics
- RapidRatings - Analytics Intern (Summer 2018), Analytics & Coverage
- TA: COMS 6998, Conversational AI - Fall 2022 (Columbia)
- TA: COMS 4156, Advanced Software Engineering - Fall 2021 (Columbia)
- TA: CS 4300, Language & Information - Spring 2021 (Cornell)
- TA: CS 4780/5780, Machine Learning for Intelligent Systems - Fall 2020 (Cornell)
- TA: INFO 5200, Learning Analytics - Fall 2019 (Cornell)
- TA: INFO 2950, Intro to Data Science - Spring 2019, 2020 (Cornell)