👨🏻‍💻 I am a Research Engineer at the CNRS, based at the CerCo in Toulouse, France.

🔬 I am passionate about Multimodal Representation Learning, NeuroAI, and AI/ML for healthcare. Committed to developing technologies that enhance lives.

📚 I’ve completed my Master’s Thesis from IIT Bombay at the junction of natural language processing (NLP), machine learning (ML), and computational social science.

Research Experience

Deep‑learning Implementations of the Global Workspace Theory

Guide: Prof. Rufin VanRullen, VanRullen Lab

• Working on a transformer‑based semi‑supervised approach for multimodal learning through Global Workspace Theory
• Exploring efficient fine‑tuning methods for multimodal large language models (MLLMs) to integrate Global Workspace

Multimodal Mixup Contrastive Learning for Multimodal Classification | Research Project, Monash University & IIT Bombay

Guide: Prof. Kshitij Jadhav & Dr. Deval Mehta

• Developed a novel multimodal contrastive loss incorporating mixup training to improve representation learning for complex real‑world multimodal data relations, beating SOTA on four diverse public multimodal classification benchmarks
• Designed and implemented a multimodal learningframework incorporating unimodal prediction modules, afusion module, and a new Mixup‑based contrastive loss for continuous representation updating

Mental Disorder Identification through Linguistic Markers | Master’s Thesis, IIT Bombay

Guide: Prof. Pushpak Bhattacharyya, CFILT Lab

• Proposed a unique method to convert social media text into time series data for post‑level analysis of mental disorders
• Developed a novel framework for mental disorder identification via foundational deep learning models which surpasses the performance of BERT‑based approaches by 5% in the F1 score on mental conditions: Depression, Self‑harm, and Anorexia
• Explored semantic overlaps among these disorders, underscoring the value of cross‑domain data in mental health research

Cognitively Inspired Hallucination Detection | Research Project, UT Austin & IIT Bombay

Guide: Prof. Abhijit Mishra & Prof. Pushpak Bhattacharyya

• Curated eye‑tracking data with 500 instances for the task of hallucination detection and developed a BERT‑based framework
• Proposed a novel attention bias framework inspired by human behavior for detecting hallucinated texts

Professional Experience

I have professional experience working as an AI Student Researcher at Assert AI.
There, I deployed customized YOLOv4 models for surveillance tasks leveraging the Nvidia Jetson series GPU accelerators, generated tailored datasets and trained YOLOv4 models for diverse object detection and classification scenarios.