I'm Sid — a researcher working across cancer immunology, T cells, synthetic receptors, gene editing, and AI for biology. This is a place for the science I care about, the things I'm building, and the questions I keep nearby.
Photo of Sid
Photo of Sid
Photo of Sid
scroll— a cell, a strand, a route
fig. 01 — from editing to recognition
Editing a cell changes its instructions. That's the first layer, not the last.
The harder question is what a cell can sense — and how it decides to act.
I want to design the receptors and circuits that let T cells recognize cancer with more specificity and context.
Recognition is the hard part. Cancer is, in part, a failure of it.
So the goal isn't only better edits — it's better ways to sense, interpret, and decide.
history — fig. 02 movement
A path through labs and questions — biking is where a lot of it metabolizes.
Cancer biology and DNA damage. Where research stopped being an idea and became something I actually did with my hands.
Memory T cells, immunology, and cancer prevention — work that became a first-author paper in the Journal of Immunology on memory T cells in cancer immunoprevention.
CRISPR, T cell engineering, and programmable biology — and the receptor and circuit logic that decides what an engineered cell can sense and do. Still involved.
T cell biology and cancer immunology, leaning into immune dysfunction, exhaustion, and cell state (including noncoding RNA / lincRNAs): why cancer recognition holds or breaks down inside tumors.
Working at the interface of recognition and editing — synthetic receptors, CRISPR, cell state, and AI — to make how T cells recognize cancer more precise, more legible, and more editable.
about
I'm Sid. Most of my work circles around cancer immunology, T cells, gene editing, and the problem of making biology more understandable and more editable.
I'm drawn to systems that recognize, remember, fail, repair, and adapt: immune systems, cells, institutions, people, and sometimes software.
work
Designing logic-gated receptor systems for T cells that can recognize cancer cells with greater precision and context-awareness.
A tool for designing modular genetic perturbations in T cells — the editing layer of cell engineering.
How T cells recognize cancer — and how sensitivity, specificity, and cell state (including the role of noncoding RNA and lincRNAs) shape whether recognition holds or breaks down.
Research and writing on how memory T cells may shape cancer immunoprevention.
Using computational tools to reason about perturbations, receptor designs, cell states, and experimental design.
Making immunology and cancer biology easier to see, explain, and care about.
papers
src/lib/publications.ts.Siddhesh Mittra, Shane M. Harding, Susan M. Kaech
First-author review on how memory T cell subsets, especially tissue-resident memory and stem memory T cells, may contribute to cancer immunoprevention.
read →Work on CRISPR-All, a unified genetic perturbation language for designing and combining genetic programs in primary human cells, including T cell engineering contexts.
read →press
src/lib/press.ts.Kerry Howley's feature on the young founders and researchers reshaping San Francisco's AI scene — I was one of the people profiled.
read →A profile on becoming one of the youngest authors published in The Journal of Immunology — a memory T cell review that grew out of teaching myself immunology during the 2020 COVID lockdown.
read →video
How unconventional T cells fit into the picture — and what EVO 2 adds to the story.
A walk through the people, labs, and ideas that shaped immunology in San Diego.
What in vivo CAR T-cell therapy is, how it differs from ex vivo approaches, and why it matters.
contact