Natural Sciences and Engineering; Engineering
Sarath Chandar Anbil Parthipan
- Professeur associé
-
Faculté des arts et des sciences - Département d'informatique et de recherche opérationnelle
Secondary number:
514 340-4711 #3245
(Travail 1)
Secondary email:
sarath-chandar.anbil-parthipan@polymtl.ca
(Travail)
Profile
Research expertise
Intérêts de recherche
- Réseaux de neurones récurrents
- Apprentissage continu
- Apprentissage par renforcement
- Apprentissage profond
- Traitement du langage naturel
- Apprentissage machine
- Intelligence artificielle
For more information…
Affiliations and responsabilities
Teaching and supervision
Student supervision
Theses and dissertation supervision (Papyrus Institutional Repository)
2024
The role of continual learning and adaptive computation in improving computational efficiency of deep learning
Graduate : Gupta, Kshitij
Cycle : Master's
Grade : M. Sc.
Cycle : Master's
Grade : M. Sc.
2023
Towards adaptive deep model-based reinforcement learning
Graduate : Rahimi-Kalahroudi, Ali
Cycle : Master's
Grade : M. Sc.
Cycle : Master's
Grade : M. Sc.
2022
Benchmarking bias mitigation algorithms in representation learning through fairness metrics
Graduate : Reddy, Charan
Cycle : Master's
Grade : M. Sc.
Cycle : Master's
Grade : M. Sc.
2021
IIRC : Incremental Implicitly-Refined Classification
Graduate : Abdelsalam, Mohamed
Cycle : Master's
Grade : M. Sc.
Cycle : Master's
Grade : M. Sc.
2021
Continuous coordination as a realistic scenario for lifelong learning
Graduate : Badrinaaraayanan, Akilesh
Cycle : Master's
Grade : M. Sc.
Cycle : Master's
Grade : M. Sc.
2021
PatchUp : a feature-space block-level regularization technique for convolutional neural networks
Graduate : Faramarzi, Mojtaba
Cycle : Master's
Grade : M. Sc.
Cycle : Master's
Grade : M. Sc.
Projects
Research projects
2024
- 2025
Reinforcement Learning for Micro-Grid Control and Optimization
Funding sources:
MITACS Inc.
Grant programs:
PVXXXXXX-Stage Accélération Québec - MITACS
Outreach
Publications and presentations
Disciplines
- Computer Science
- Computer Engineering and Software Engineering
Areas of expertise
- Neural Networks
- Deep learning
- Natural-language processing (NLP)
- Artificial intelligence