I am a second year PhD student at UNSW Sydney jointly supervised by Dr. Lina Yao and Dr. Dong Gong. Prior to my PhD, I was a research assistant at the Computer Vision Center, Barcelona where I worked with Dr. Joost van de Weijer on continual learning.

I completed my Erasmus Mundus Joint Master’s Degree in Advanced Systems Dependability from the University of St Andrews, UK, and l’Université de Lorraine, France. During my master’s, I interned with the MULTISPEECH group at Inria Nancy where I worked with Dr. Emmanuel Vincent on training domain-specific language models for Automatic Speech Recognition. Before that, I  was a machine learning engineer at FactSet Research Systems Inc. I earned my BS in Computer Science and Engineering from MNNIT Allahabad, India.


Publications

Please check my google scholar profile for an up-to-date list.

Pre-prints:
  • Jha S., Gong D., Yao L., “CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models”, 2024. Paper  Code
  • Jha S., Gong D., Wang X., Turner R., Yao L., “The Neural Process Family: Survey, Applications and Perspectives”, 2022.
Conferences:
  • Jha S., Gong D., Zhao H., Yao L., “NPCL: Neural Processes for Uncertainty-Aware Continual Learning”, NeurIPS 2023. Blog Paper
  • Li Y., Liu Z., Jha S., Cripps S., Yao L., “Distilled Reverse Attention Network for Open-world Compositional Zero-Shot Learning”, ICCV 2023.
Workshops:
  • Pelosin F.*, Jha S.*, Torsello A., Raducanu B., van de Weijer J. “Towards Exemplar-Free Continual Learning in Vision Transformers: an Account of Attention, Functional and Weight Regularization”. CVPR Workshop on Continual Learning, 2022. (* Equal Contribution) Code [Best runner-up paper]
  • Jha S., Schiemer M., Ye J. “Continual learning in human activity recognition: an empirical analysis of regularization”. ICML Workshop on Continual Learning, 2020. Code
Journals:
  • Jha S., Schiemer M., Zambonelli F., Ye J. “Continual learning in sensor-based human activity recognition: An empirical benchmark analysis”. Information Sciences, 2021. Code
  • Ye J., Nakwijit P., Schiemer M., Jha S., Zambonelli F. “Continual Activity Recognition with Generative Adversarial Networks”. ACM Transactions on Internet of Things (TIOT), 2021.
  • Jha S., Sudhakar A., Singh A.K. “Learning cross-lingual phonological and orthographic adaptations: a case study in improving neural machine translation between low-resource languages”. Journal of Language Modelling, 2019.

Academic Services

  • Reviewer for: CPVR 2023, TPAMI, ICLR 2023, NeurIPS 2023
  • PC member for Workshop Proposals, Conference on Information and Knowledge Management (CIKM 2023)

Teaching at UNSW

  • Head Tutor for Term 1 2024 postgraduate course – COMP6713 (Natural Language Processing), taught by Dr. Aditya Joshi
  • Tutor for Term 3 2022 postgraduate course – COMP9418 (Advanced Topics in Statistical Machine Learning), taught by Dr. Gustavo Batista
  • Tutor for Term 3 2022 postgraduate course – ZZEN9444 (Neural Networks and Deep Learning), taught by Dr. Dong Gong
  • Tutor for Terms 1,2,3 2023 postgraduate course – COMM5007 (Python Coding for Business), taught by Dr. Xiangyu Wang