Nitish

Hi, I'm Srinitish Srinivasan

Master's Student at Indian Institute of Technology, Delhi under the supervision of Dr. Tanmoy Chakraborty.

About Me

I am a Master's Student in Electrical Engineering at Indian Institute of Technology, Delhi, under the supervision of Dr.Tanmoy Chakraborty specializing in Information Retrieval and Geometry. Over the past 1 year, I have been working on geometric representations of hierarchies such as Taxonomies. I also have a keen interest in Agentic AI.

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 enjoy cycling, running, K-dramas, Korean music (massive Uaena btw :p), farming simulators like Stardew Valley(Checkout the Stardew Theme(Attempted😔 LOL) and travelling.

Geometric Deep Learning
Graphs
Taxonomy Induction

Recent News

University

Began my Master's program at IIT Delhi under the supervision of Dr. Tanmoy Chakraborty.

January, 2026 (Spring Intake)

Conference

Attended ACM Sigmod in Berlin, Germany and presented my poster at GRADES NDA Workshop.

June, 2025

Grant Awarded

Received a travel grant of USD 1500 from GRADES NDA to present my poster at ACM SIGMOD.

June, 2025

Paper Accepted

My paper LGIN has been accepted at ACM SIGMOD 2025 GRADES NDA Workshop.

May, 2025

Recent Publications

LGIN Abstract

Can we ease the Injectivity Bottleneck on Lorentzian Manifolds for GNNs?

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.

Bond Yields Paper

Predicting Liquidity-Aware Bond Yields using Causal GANs...

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.

Joint Predictive Embedding Paper

Leveraging Joint Predictive Embedding and Bayesian Inference...

Srinitish Srinivasan, Omkumar CU. Preprint

A novel, scalable graph self-supervised technique that leverages both joint predictive embedding architecture and Bayesian inference for robust representation learning.

Get In Touch

Contact Information

I'm always interested in discussing research collaborations, speaking opportunities, freelancing, or just chatting about AI/ML. Feel free to reach out!

Email

smudge0110@icloud.com

Discord

smudge0110

Office

LCS2, Yardi School of AI, IIT Delhi

Connect Directly on Discord

Discord QR Code

If you would like to discuss any papers or just talk about AI, you can chat with me on discord:)

Username: smudge0110