Mohit Bansal

Assistant Professor
Computer Science Dept., UNC Chapel Hill
SN-258, 201 S. Columbia St.
Chapel Hill, NC 27599-3175
mbansal -atsign- cs -dot- unc -dot- edu
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Updates/News:

I am looking for motivated PhD students in NLP, ML, and multimodal AI for fall-2018: [Info for Prospective Students] [Department's Why-UNC Page]



 CV / Bio           Work Experience           Publications/Code/Data           Teaching           Students/Interns           Professional Service           Colloquium Series

About Me

I am assistant professor in the Computer Science department at the University of North Carolina (UNC) Chapel Hill. Prior to this, I was a research assistant professor (3-year endowed position) at TTI-Chicago. I received my Ph.D. in 2013 from the University of California at Berkeley, where I was advised by Dan Klein. I did my B.Tech. from the Indian Institute of Technology at Kanpur. I have also spent time at Google Research, Microsoft Research, and Cornell University.

Research Interests

Statistical natural language processing and machine learning, with a focus on multimodal, grounded, and embodied semantics (i.e., language with vision and speech, for robotics), human-like language generation and Q&A/dialogue, and interpretable and structured deep learning.

Work Experience

Computer Science department, UNC Chapel Hill (August 2016 — present)
Assistant Professor

Toyota Technological Institute, Chicago (September 2013 — July 2016)
Research Assistant Professor

IARPA Babel Project, Swordfish team (February 2014 — June 2014)
Member/Consultant

EECS, UC Berkeley (August 2008 — August 2013)
Graduate Student Researcher (Advisor: Dan Klein)

Google Research, Mountain View (May 2011 — August 2011)
Research Intern (with John DeNero and Dekang Lin)

Microsoft Research, Redmond (May 2010 — August 2010)
Research Intern (with Chris Quirk and Bob Moore)

Cornell University, Ithaca (May 2007 — August 2007)
Research Intern (with Lillian Lee and Claire Cardie)

Publications (+Code/Data)

(most conferences below (incl. short paper proceedings) have a <25% acceptance rate; google scholar based list of top-ranked conferences in NLP, vision, AI/ML, robotics)

Teaching

Instructor, Advanced Topics in NLP: Conversational Models, UNC Chapel Hill, Spring 2018.

Instructor, Graduate Natural Language Processing, UNC Chapel Hill, Fall 2017.

Instructor, Advanced Topics in NLP: Language Grounding for Robotics, UNC Chapel Hill, Spring 2017.

Instructor, Seminar on Natural Language Processing, UNC Chapel Hill, Fall 2016.

Guest Lecturer, Computational Linguistics (Instructor: John Goldsmith), University of Chicago, Spring 2015.

Guest Lecturer, Robotics and Artificial Intelligence (Instructor: Matthew Walter), TTI-Chicago, University of Chicago, Spring 2015.

Guest Lecturer, Visual Recognition with Text (Instructor: Sanja Fidler), University of Toronto, Winter 2015 — short course on 'Topics, Trends, and Resources in NLP' [slides].

Grad Student Instructor, Introduction to Artificial Intelligence (Instructor: Dan Klein), UC Berkeley, Fall 2011. Received an Outstanding Graduate Student Instructor Award by UC Berkeley for excellence in teaching.

Grad Student Instructor, Advanced Topics in Artificial Intelligence (Instructors: Pieter Abbeel, Dan Klein, Jitendra Malik), UC Berkeley, Spring 2009. Sole TA for new course with 30 advanced students.

Students/Interns

Student openings: I am looking for highly motivated PhD students. If you are interested in the broad areas of multimodal NLP (with vision and speech, for robotics), language generation and dialogue/Q&A, and structured+interpretable deep learning, please see my prospective student page and contact me at mbansal-AT-cs-DOT-unc-DOT-edu for further details.

UNC Advisees:
Robbie Allen (UNC, PhD)
Lisa Bauer (UNC, PhD)
Yen-Chun Chen (UNC, MS)
Tsion Coulter (UNC, BS)
Han Guo (UNC, BS)
Yichen Jiang (UNC, BS)
Sweta Karlekar (UNC, BS)
Jie Lei (UNC, PhD; co-advised with Tamara Berg)
Yixin Nie (UNC, PhD)
Ramakanth Pasunuru (UNC, PhD)
Hao Tan (UNC, PhD)
Yicheng Wang (UNC, BS)
Licheng Yu (UNC, PhD; co-advised with Tamara Berg)

Other Advisees:
Arjun Chandrasekaran (Georgia Tech, PhD; advisor = Devi Parikh) (PhD Thesis Committee Member)
Nitish Joshi (Visiting student; IIT Bombay, BS)
Tong Niu (Visiting student; Duke, MS)

Past Advisees:
Malika Aubakirova (UChicago, BS)
Dhivya Eswaran (IIT-Madras, BTech --> CMU, PhD)
Rasool Fakoor (UT-Arlington, PhD --> MSR)
Arnab Ghosh (IIT Kanpur, BTech --> Oxford, PhD)
Yuchen He (UIUC, PhD)
Myungin Kim (UChicago, MS)
Zuyao Li (USC, MS --> Google/Nest)
Ang Lu (Tsinghua, BS --> CMU, MS)
Pranava S. Madhyastha (UPC Barcelona, PhD)
Hongyuan Mei (UChicago/TTIC, MS --> JHU, PhD) (MS Thesis Co-Advisor)
Aravind L Srinivas (IIT Madras, BTech --> UC Berkeley, PhD)
Ryan Stout (UIUC, MS)
Trang Tran (UWash, PhD)
Jing Wang (UIC, PhD --> Conversant)
John Wieting (UIUC/TTIC MS --> CMU, PhD)
Zhengyang Wu (GeorgiaTech, BS --> MagicLeap)

Professional Service

Area Chair EMNLP 2018

Tutorial Chair: NAACL 2018

Area Chair (Vision, Robots, and Grounding): ACL 2017

Area Chair (Machine Learning): EMNLP 2017

Demo Chair: ACL 2017

Tutorial Chair: NAACL 2016

Area Chair: NAACL 2016

Program Committee Member / Reviewer:

Conferences: EMNLP (best reviewer award, 2012), NAACL (best reviewer award, 2018, 2015), ACL, NIPS, ICLR, IJCAI, EACL, COLING, *SEM, IJCNLP, ICON

Journals: TACL, TPAMI, TALIP

Workshops: ACL Workshop of Women in Natural Language Processing (2017), ACL Workshop on Representation Learning for NLP (2017), EACL Workshop on Ethics in Natural Language Processing (2017), NAACL Multilingual and Crosslingual Methods in NLP (2016), NAACL Human-Computer Question Answering (2016), ACL Evaluating Vector-Space Representations for NLP (2016), NAACL Vector Space Modeling for NLP (2015)

University Research Proposals: ORAU

Organizer: NLP/ML Colloquium Series at UNC, Language Grounding for Robotics at ACL 2017, Midwest Speech and Language Days 2015

Committee Member: Graduate (PhD) Admissions Committee, EECS, UC Berkeley

Panel Member: National Science Foundation (NSF) Review Panels

Software and Datasets: Available as links with corresponding paper in Publications/Code/Data.
Resources released recently: