Hi, I'm Shiva.

I’m Shivaramakrishna Srinivasan, a computational biologist in the Subramaniam Lab and M.S. candidate in Bioengineering at UC San Diego.

My research focuses on building scalable and interpretable machine learning models for single-cell data, particularly using large language models to uncover immune cell states across infectious diseases.

Previously, I’ve worked on molecular modeling at Adaptyv Biosystems, RNA switch prediction using graph neural networks at TCS Research, and bioinformatics workflow development at LatchBio.

I am interested in biology, open science, programming, and design.

Feel free to explore my corner of the internet.


Now

I am also a Teaching Assistant to Prof. Terry Sejnowski in his Computational Systems Neurobiology Course.


Projects

SyBodies @ Adaptyv

Sybodies are tiny, synthetic versions of antibodies designed to latch onto specific proteins—especially ones found on viruses or cancer cells. Unlike regular antibodies made by our immune systems, sybodies are created entirely in the lab, without needing an animal or human immune response. Think of them like precision-engineered tools, custom-built to stick to a specific molecular target.

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Virtual drug screening for HIV using DeepChem

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Palisades in Glioblastoma

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hlca-single-cell-spatial

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Indian Biopolicy Guide

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Workflows for Latch

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Neuron Infographics

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3-gene optorepressilator model

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Writing

iGEM: A springboard for diving into synbio

A note on synthetic biology and iGEM for Tata Consultancy Services

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iGEM Wikis - A primer

How to build your team wiki and other useful resources

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