I'm Abhijith Sharma. I audit tool-using LLM agents.

I'm a PhD student in Machine Learning at MBZUAI in Abu Dhabi, advised by Salem Lahlou and Nils Lukas. I work on auditing, testing and verification of AI agents: training auditors that interrogate tool-using LLM agents the way real users would, and fuzzing multi-agent systems for the failures that only appear when agents, tools and memories interact.

Previously, I was a research associate at the University of Waterloo with AVL, where I built a real-time adversarial testing framework for autonomous vehicles under Sebastian Fischmeister and Nasser Azad. Before that I was a MITACS Accelerate intern at TrojAI, working on physical adversarial attacks and defenses for vision models under Apurva Narayan, which became my master's thesis at UBC.

I did my bachelor's at the College of Engineering, Pune, graduating with the gold medal, and spent three of those years on the control subsystem of COEP-SAT-2, a student satellite. There was also a short stint in decision analytics at ZS Associates.

Outside of work I play squash, swim, and read history.

recent venues NeurIPS 2026AAAI 2026UAI 2025IEEE T-IV 2024
Cut-out portrait of Abhijith Sharma
Education

Degrees

Research threads

What I'm working on

  1. 01
    Learning to audit

    Auditors that probe deployed agents like real users would, and surface policy violations hidden across turns and tool calls.

  2. 02
    Fuzz verification of multi-agent systems

    Fuzzing for the failures that only appear when several agents, tools and memories interact.

  3. 03
    Diversity-seeking exploration

    GFlowNets and RL objectives that find many distinct failure modes, not one worst case.

  4. 04
    Robustness & privacy

    Physical adversarial patches, real-time AV testing (AVATAR), membership inference on spiking networks.

Read the research page

Now

Second year of the PhD at MBZUAI, Abu Dhabi. Presenting PROBE at NeurIPS 2026 and building the next auditor.

Abu Dhabi
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GST · UTC+4
where you are--:--
Selected work

Papers I'd show you first

All publications
Toolbox

Things I reach for

Methods
RL fine-tuning · GRPO / DPOGFlowNetsadversarial MLmembership inferencefuzzingverifiers & LLM judges
Agents
tool-using LLM agentsmulti-turn simulationMCPpolicy specsQLoRA
Code
PythonPyTorchtorchgfnCARLADockerLaTeXC

Let's audit something together.

Email
Based in
Abu Dhabi, UAE
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Changelog

Recent updates

    Experience

    Pune → Vancouver → Waterloo → Abu Dhabi

    1. 2020 – 2021ZS AssociatesDecision analytics associate. Pricing models for a US medical-device launch.
    2. 2021 – 2023TrojAI · UBCMITACS Accelerate intern. Physical adversarial attacks and defenses for vision models.
    3. 2023 – 2024University of WaterlooResearch associate with AVL. Real-time adversarial testing for autonomous vehicles.
    4. 2024 – nowMBZUAIResearch associate, then PhD. Auditing and verifying AI agents.
    Open source

    Code

    Off the clock

    When not auditing

    Squash courts, long swims, and history books. I read about empires the way I read agent traces: looking for the turn where the rules stopped being followed.

    speaks english · hindi · marathi