STUDENT RESEARCHER  ·  AI × BIOLOGY

Decoding the undruggable.
Building the tools that find what others miss.

Hi, I'm Nimit Akhawat — a student researcher working at the intersection of AI in drug discovery, neuroscience, and biochemistry. I build computational tools and run experiments aimed at turning hard biological questions into tractable, data-driven ones.

MISSION

To make the next generation of medicines reachable — by using artificial intelligence to illuminate the dynamic, "invisible" structures of disease-driving proteins, and to connect the molecular world of chemistry with the living systems of the brain.

AI in Drug Discovery Intrinsically Disordered Proteins Neuroscience Optogenetics Biochemistry Machine Learning
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Research & Projects

Computational and experimental work spanning drug discovery, neuroscience, and the chemistry that links them.

● Published Neuroscience × Chemistry

Chemical Techniques in Optogenetics

A review of how synthetic and biochemical chemistry is expanding the optogenetics toolkit — from engineered photoswitchable ligands to chemically caged neurotransmitters — and how these advances give researchers finer, light-controlled command over neural circuits. The work bridges molecular design and systems neuroscience.

Optogenetics Photopharmacology Neural Circuits
Read the published article →
● Ongoing Interest Neuroscience & ML

Modeling the Brain's Dynamics

Exploring how machine-learning methods can capture brain-wave patterns and neural signaling — and how the same representational ideas that power protein modeling might illuminate neuroscience. An evolving line of inquiry rather than a single project.

Brain Waves Representation Learning Signal Modeling
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Articles & Review Papers

Peer-reviewed publications and review articles, with summaries and links.

Advancing Neuroscience Through Chemical Techniques in Optogenetics

This review examines how chemistry is reshaping optogenetics — the technique of using light to control genetically targeted neurons. It surveys photoswitchable and photo-caged molecular tools, the design principles behind light-responsive ligands, and how these chemical strategies extend optogenetic control beyond classical opsins. The result is a clearer picture of how molecular-level innovation translates into more precise interrogation of neural circuits and, ultimately, new avenues for studying brain function and neurological disease.

Read article ↗ Download PDF ↓
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Main Research Goal

AI in drug discovery & development — my central focus.

Making the "undruggable" reachable.

A large share of the proteins that drive devastating diseases — many neurodegenerative disorders among them — are intrinsically disordered. They flicker between countless shapes instead of settling into one, so the standard drug-discovery playbook of "find the rigid pocket, fit a molecule into it" simply doesn't apply. These targets get labeled undruggable not because binding is impossible, but because our tools were built for a more static world.

My goal is to change which targets count as reachable. I'm developing AI-driven methods that treat a protein as the moving, breathing ensemble it actually is — learning the structural signatures that precede a transient pocket, and scoring where and when a drug might grab hold — turning today's "undruggable" targets into tomorrow's therapeutic starting points.

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Interest

The interface where machine learning meets structural biology — using data to model molecular motion, predict binding behavior, and reason about chemistry the way an experimentalist would.

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Goals

Build validated, benchmarked tools that surface cryptic and transient binding sites; make them open and explorable so other researchers can act on them; and ground every prediction in experimental reality.

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Vision

A future where disordered, dynamic proteins are routine drug targets — and where AI accelerates the path from a disease-linked protein to a credible therapeutic starting point.

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Blog

Notes on neuroscience, machine learning, chemistry, and the realities of building a research career.

Neuroscience

Why "undruggable" is a statement about our tools, not the disease

A short tour of intrinsically disordered proteins and why their flexibility breaks classical drug design — and what to do about it.

Coming soon
Machine Learning

Teaching a model to see a pocket that isn't there yet

The intuition behind learning structural signatures that precede pocket formation in a conformational ensemble.

Coming soon
Chemistry

Light as a reagent: the chemistry behind optogenetics

How photoswitches and caged molecules turn a beam of light into a precise chemical command for neurons.

Coming soon
Career

Doing real research as a student

Reflections on starting independent projects early, learning in public, and finding mentors.

Coming soon
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YouTube

Science explained — molecules, minds, and the methods in between.

@nimitakhawat

Nimit Akhawat on YouTube

I make videos breaking down ideas in neuroscience, biochemistry, and AI for drug discovery — translating dense research into something you can actually follow. New explainers added regularly.

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Resume

Academic achievements and a downloadable CV.

At a glance

  • Focus: AI in drug discovery, neuroscience, and biochemistry.
  • Research focus: Ensemble-based druggability prediction for intrinsically disordered proteins.
  • Publication: Review article on chemical techniques in optogenetics (IJAR).
  • Science communication: YouTube channel translating research for a wider audience.
  • Skills: Computational structural biology, machine learning, molecular dynamics, scientific writing.
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Get the full CV with detailed coursework, projects, and achievements.

Download Resume ↓ Place your PDF at assets/resume/Nimit-Akhawat-Resume.pdf
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Discussion

Ask questions, answer others, and discuss neuroscience, AI, chemistry, and drug discovery with a community of curious researchers. Vote up what's useful.

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Contact & Collaborate

Open to collaborations, mentorship, and conversations with fellow researchers. Let's build something.

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Reach me directly

hello@nimitakhawat.com

For research collaborations, speaking, or mentorship inquiries.

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