Avinash Madasu
Santa Clara, CA

I am a staff research scientist at Intel AI Labs working on multi-modal AI. I graduated from University of North Carolina, Chapel Hill with a Master in Computer Science advised by Prof. Gedas Bertasius. While at UNC, my research focused on multi-modal AI.

I was a senior engineer at Samsung R & D Institute India - Bangalore, for 3 years where I worked on Bixby (Samsung's voice assistant). My job was to design NLU models to help improve Bixby. I had the opportunity to work under Prof. Asif Eqbal on multi-modal dialog systems. I graduated from National Institute of Technology Tiruchirappalli with Bachelors in Computer Science. While pursuing UG studies, I worked closely with Prof. Sivasankar on statistical feature extraction techniques for sentiment analysis.

I am interested in contributing to open source frameworks that empower neural networks. I am also a member of Distributed Deep Machine Learning Community and reviewer of gluonnlp, Amazon's NLP library.

E-mail  |  Curriculum Vitae  |  Publications  |  LinkedIn  |  Github  | 


Research Interests

My area of interests lie in Multi-modal AI especially in the intersection of Natural Language Processing, Computer Vision and Robotics. I had worked in the areas of multi-modal dialog systems, domain adaptation, text classification etc.


Press
Awards
Service
  • Conference Reviewer: AMLC 2023, NeurIPS 2023, BMVC 2023, CoLLA 2023, ACL 2023, CVPR 2023, EACL 2023, ACL 2022, ACL 2021, ICON 2020.
  • Journal Reviewer: Machine Learning, TMLR, Computer Speech & Language, ACL ARR.
  • Workshop Reviewer: ICLR - MoFo 2023, ICLR - MRL 2023, SocialNLP
Peer Reviewed Publications
3DSP A Unified Framework for Slot based Response Generation in a Multimodal Dialogue System
Mauajama Firdaus*, Avinash Madasu*, Asif Ekbal
Journal of Multimedia Tools and Applications
[Paper] [Code]
3DSP Is Multimodal Vision Supervision Beneficial to Language?
Avinash Madasu, Vasudev Lal
CVPR 2023 (NFVLR Workshop)
[Paper] [Code]
3DSP A Unified Framework for Emotion Identification and Generation in Dialogues
Avinash Madasu*, Mauajama Firdaus*, Asif Ekbal
EACL 2023 (SRW Workshop)
[Paper]
3DSP Improving video retrieval using multilingual knowledge transfer
Avinash Madasu, Estelle Aflalo, Gabriela Ben Melech Stan, Shao-Yen Tseng, Gedas Bertasius, Vasudev Lal
ECIR 2023
[Paper]
3DSP What do Large Language Models Learn beyond Language?
Avinash Madasu, Shashank Srivastava
EMNLP 2022 (Findings)
[Paper] [Code]
3DSP Learning to Retrieve Videos by Asking Questions
Avinash Madasu, Junier Oliva, Gedas Bertasius
ACM Multimedia 2022
[Paper] [Code] [Poster]
3DSP Sequential Domain Adaptation through Elastic Weight Consolidation for Sentiment Analysis
Avinash Madasu, Vijjini Anvesh Rao
ICPR 2020
[Paper]
3DSP A Position Aware Decay Weighted Network for Aspect based Sentiment Analysis
Avinash Madasu, Vijjini Anvesh Rao
NLDB 2020
[Paper]
3DSP Sequential Learning of Convolutional Features for Effective Text Classification
Avinash Madasu, Vijjini Anvesh Rao
EMNLP 2019
[Paper]
3DSP Efficient Feature Selection techniques for Sentiment Analysis
Avinash Madasu, Sivasankar E
Journal of Multimedia Tools and Applications
[Paper]
3DSP Gated Convolutional Neural Networks for Domain Adaptation
Avinash Madasu, Vijjini Anvesh Rao
NLDB 2019
[Paper]
3DSP Effectiveness of Self Normalizing Neural Networks for Text Classification
Avinash Madasu, Vijjini Anvesh Rao
CICLing 2019
[Paper]
3DSP A Study of Feature Extraction techniques for Sentiment Analysis
Avinash Madasu, Sivasankar E
IEMIS 2018
[Paper]



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