Work Experience
- 2024-Present: “Research Scientist” at Sakana AI
Developing the next generation of AI models (e.g., recent first-authored work [1, 2, 3]). - 2024-Present: “Research Scientist Intern” at Meta (FAIR)
Developing multi-task ‘behavior foundation models’ for autonomous decision-making using large-scale unsupervised and offline RL. - 2022: “PhD Intern” at Twitter Cortex
Developing new deep reinforcement learning framework using hyperbolic geometry to attain better generalization and sample efficiency. - 2019: “Deep Learning and Computer Vision Intern” at Toyota
Building state-of-the-art few-shot learning techniques for 2D and 6D object detection for applications in robotic control and activity recognition. - 2018: “Engineering Summer Analyst Intern” at Goldman Sachs
Designing and deploying an anomaly detection systems for the launch of the Marcus consumer banking platform.
Education
- 2019-2023: King’s College London, Ph.D. Computer Science
- 2016-2019: King’s College London, BSc Computer Science with Intelligent Systems
Degree obtained with first Class Honors: Overall average: 90%
Awards
- 2018/2019: Winner of the King’s College Engineering Society Centenary Prize
“Awarded to the students who have shown most distinction at the final examination after three years study in the College in an Undergraduate programme which includes Engineering components.” - 2017/2018: Winner of the NMS Robotics Prize
“Awarded for the best performance on an undergraduate Robotics programme.”
Teaching Experience
- 2020-2023 (3 years): Guest lecturer for the course Random Variable and Stochastic Processes
Leading lectures and preparing course material regarding probabilistic modeling with Markov models. - 2019/2020: Graduate teaching assistant for the course Pattern Recognition and Machine Learning
Teaching bi-weekly tutorials on how to effectively implement machine learning algorithms in modern frameworks. - 2019/2020: Guest instructor for the AICore
Teaching about the theory and implementation details of reinforcement learning algorithms and generative adversarial networks.
Reviewing Experience
- Reviewer for NeurIPS, ICML, ICLR, IROS, ICRA, and ACMMM conferences (since 2020).
- “Highlighted Reviewer” of ICLR 2022.