About Me
Dr. Dmitry Kazhdan
AI Researcher & Builder
👋About Me
Current: My current passion is in Multi-Agent Systems - figuring out how mixed-species teams of Human and AI agents (such as LLMs / MLLMs) can reach optimal outcomes without doing too much evil in the process. As a film enthusiast, I'm also paying close attention to AI video generation efforts (e.g. Veo). Expect experiments in the Projects section soon...
Past: Ex-Co-founder & CPTO of Tenyks (YC S21), where I helped build Visual Intelligence AI products for real-time camera analytics in the Hospitality Industry. Yes, I've seen things. I've led teams through startup hellfire, built LLM/VLM products from scratch, and lived to tell the tale. Academically, I hold a PhD from The University of Cambridge in Explainable AI, where I happily wrestled with Concept-based Explanations across multiple modalities (expertly supervised by Prof. Mateja Jamnik & Prof. Pietro Lio). Spoiler: XAI doesn't solve the Evil AI problem - turns out, you need Explainable Humans for that too.
Outside of AI: I used to play classical guitar (Grade 8 Distinction) and will happily nerd out over cinematography, sci-fi plots, and existential humour.
🎓Education
PhD in Artificial Intelligence
The University of Cambridge
Enhancing Interpretability: The Role of Concept-based Explanations Across Data Types • Grade: Passed with Minor Corrections Only
MEng in Computer Science
The University of Cambridge
MARLeME: A Multi-Agent Reinforcement Learning Model Extraction Library • Grade: Distinction
High-School
The Heritage Private School, Cyprus
A-levels: 4A*, 1A; AS-levels: 1A; IGCSEs: 9A*, 1A • Grade: 4A*, 1A (A-levels)
💼Work Experience
Co-Founder and CTO
Tenyks
2021 - 2025
Lead R&D of a cutting-edge camera stream analytics platform for the Hospitality Industry
Research Intern
Nokia Bell Labs
2019
Explored Variational Continual Learning for personalised ML systems using sparse user data
Software Engineer Intern in Machine Learning
Arm
2018
Built a face recognition pipeline for Arm platforms using SVMs, CNNs, and CV pre-processing techniques
📚Recent Publications
Now You See Me (CME): Concept-based Model Extraction
Conference on Information and Knowledge Management (CIKM), AIMLAI Workshop
MEME: Generating RNN Model Explanations via Model Extraction
Advances in Neural Information Processing Systems (NeurIPS), HAMLETS Workshop
MARLeME: A Multi-Agent Reinforcement Learning Model Extraction Library
International Joint Conference on Neural Networks (IJCNN)