Anbil Parthipan, Sarath Chandar

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Sarath Chandar Anbil Parthipan

B.Eng (Anna University, Chennai, India), M.S.(Indian Institute of Technology Madras), Ph.D. (University of Montreal)

Publications

Link(s)

Assistant Professor
Department of Computer Engineering and Software Engineering

Phone: (514) 340-4711 Ext. 3245 Fax: (514) 340-5139 Room: M-3406

sarath-chandar.anbil-parthipan@polymtl.ca

Research interests and affiliations

Research interests

Recurrent Neural Networks
Lifelong Learning
Reinforcement Learning
Deep Learning
Natural Language Processing
Machine Learning
Artificial Intelligence

Affiliation(s)

CIFAR Chair in Artificial Intelligence, Chairholder
LAMA-WeST (Web, Semantics and Text), Collaborating member

Publications

Recent publications

Madsen, A., Reddy, S., & Anbil Parthipan, S. C. (2023). Post-hoc Interpretability for Neural NLP: A Survey. ACM Computing Surveys, 55(8), 155 (42 pages).

Lafleur, D., Anbil Parthipan, S. C., & Pesant, G. (2022, July). Combining reinforcement learning and constraint programming for sequence-generation tasks with hard constraints [Paper]. 28th International Conference on Principles and Practice of Constraint Programming (CP 2022), Haifa, Israel.

Clouatre, L., Parthasarathi, P., Zouaq, A., & Anbil Parthipan, S. C. (2022, May). Local Structure Matters Most: Perturbation Study in NLU [Paper]. 60th Annual Meeting of the Association-for-Computational-Linguistics (ACL 2022), Dublin, IRELAND.

McRae, P.-A., Parthasarathi, P., Assran, M., & Anbil Parthipan, S. C. (2022, April). Memory augmented optimizers for deep learning [Poster]. 10th International Conference on Learning Representations (ICLR 2022).

See all publications (30)

Biography

Sarath Chandar est professeur adjoint à Polytechnique Montréal, où il dirige le laboratoire de recherche Chandar. Il est aussi membre académique principal de Mila, institut québécois d’IA, et il est titulaire d’une chaire en IA Canada-CIFAR. Il possède un Ph.D. de l’Université de Montréal. Les intérêts de recherche de M. Chandar incluent l’apprentissage continu, l’apprentissage profond, l’apprentissage par renforcement et le traitement du langage naturel. Il a agi comme membre du comité de programme des événements suivants : ICML, NeurIPS, ICLR et AAAI. M. Chandar est également président sectoriel pour l’ICLR 2020 et pour la conférence 2020 de l’AAAI. Depuis 2016, il organise l’atelier sur l’apprentissage continu de l’ICML, et il a présenté des tutoriels dans le cadre de la conférence du NAACL 2016 et de celle sur l’EMNLP 2017.

Link(s) of interest

Teaching

INF8953CE - Machine Learning (Fall 2020)

INF6900/7900A - Scientific and Technical Communication I and II (Fall 2020)

Education

Bachelors in Engineering, Computer Science and Engineering (Anna University, Chennai, India)
Master in Science. - Research in Computer Science and Engineering (Indian Institute of Technology Madras)
Doctorate in Computer Science (University of Montreal)

Supervision at Polytechnique

COMPLETED

Master's Thesis (1)
- Lafleur, D. (2022). Combining Reinforcement Learning and Constraint Programming for Sequence-Generation Tasks with Hard Constraints [Master's thesis, Polytechnique Montréal].

News about Sarath Chandar Anbil Parthipan

NEWS | August 29, 2023

Canada Research Chairs awarded to professors Boulay, Karabulut Kurt and Anbil Parthipan; funding renewed for Professor Rousseau’s Chair | Read

Press review about Sarath Chandar Anbil Parthipan

April 20, 2021, La Presse, L'IA s'intègre de plus en plus partout Dans cet article, Sarath Chandar Anbil Parthipan, professeur adjoint au Département de génie informatique et génie logiciel de Polytechnique Montréal et membre du MILA (Institut québécois d'intelligence artificielle), discute du développement de solutions en intelligence artificielle.

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