Hi, I'm Srinitish Srinivasan
Junior Research Fellow (JRF) at Indian Institute of Technology, Delhi researching Geometric Deep Learning.
Junior Research Fellow (JRF) at Indian Institute of Technology, Delhi researching Geometric Deep Learning.
I am a Research Fellow at Indian Institute of Technology, Delhi, under the supervision of Dr.Tanmoy Chakraborty working on Geometric Deep Learning, Taxonomy Completion and the intersection of GNNs and LLMs. I also have a keen interest on Agent Based Systems.
My final-year undergrad research was focused on studying the discriminative bottleneck of Hyperbolic GNNs and developing an approximate solution to tackle the same. Apart from research, I watch K-dramas, listen to Korean music(I am a massive Uaena btw :p), play farming simulators like Stardew Valley(love cozy weekends fr) and love exploring different countries when I travel for conferences.
Attended ACM Sigmod in Berlin, Germany and presented my poster at GRADES NDA Workshop :).
June, 2025
Received a travel grant of USD 1500 from GRADES NDA to present my poster at ACM SIGMOD. Cant wait to meet yall in Berlin :p
June, 2025
My paper LGIN has been accepted at ACM SIGMOD 2025 GRADES NDA Workshop.
May, 2025
Joined LCS2, IIT Delhi as a Research Fellow under Dr. Tanmoy Chakraborty.
May, 2025
My paper on Joint Predictive and Bayesian Inference based Graph Self Supervised Learning is out on Arxiv.
February, 2025
Srinitish Srinivasan, Omkumar CU. ACM SIGMOD 2025 GRADES NDA Workshop (Poster)
Hyperbolic GNNs may not be as powerful as Euclidean GNNs due to non-injective aggregations. LGIN provides a theoretical framework for a Hyperbolic GNN that approximates a powerful GNN despite constraints on Hyperbolic spaces.
J. S. Walia, A. Sinha, S. Srinivasan, S. Unnikrishnan. Preprint
Designed a CausalGAN and RL-based framework to generate synthetic bond yield data. Integrated a fine-tuned LLM to provide trading signals, risk assessments, and volatility projections.
Srinitish Srinivasan, Omkumar CU. Scientific Reports
A white-box gradient-based adversarial attack which targets the contrastive latent space, demonstrating its effectiveness by reducing model performance by an average of 20-25% on tested graph classification tasks.
I'm always interested in discussing research collaborations, speaking opportunities, freelancing, or just chatting about AI/ML. Feel free to reach out!
smudge0110@icloud.com
Discord
smudge0110
Office
LCS2, Yardi School of AI, IIT Delhi
If you would like to discuss any papers or just talk about AI, you can chat with me on discord:)
Username: smudge0110