Background/Experience

Education

  • 2019-present: 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.”

Work Experience

  • 2022: “PhD Intern” at Twitter Cortex
    Developing new deep reinforcement learning framework using hyperbolic geometry to attain better generalization and sample-efficiency (paper to be presented at ICLR 2023).
  • 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.

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.
  • “Highlighted Reviewer” of ICLR 2022.