I specialize in neuroplastic Adaptive Neural Controllers, Reinforcement Learning, and Neuroevolution. With over a decade of experience across fusion energy and industrial automation, I design tiny, robust AI systems for embedded deployment and edge computing.
A strategic mobile game featuring a custom-built minimax AI engine. I engineered the opponent AI from scratch, optimizing alpha-beta pruning and heuristic evaluation to run smoothly on constrained mobile devices without native system crashes.
Read MoreDeep reinforcement learning agent for learning trading strategies based on MuZero for a pre-startup mini hedge-fund in the US. Huge potential for automated trading.
Developed a solution using Temporal Fusion Transformers (TFT) for predicting future volatility of stock options, achieving a 64% win rate on validation datasets.
Parametric and generative design of long reach manipulators at UKAEA, including custom physics engine implementation and topology/dimension synthesis.
Managed and delivered the full project lifecycle for the control system of the ITER Vacuum Vessel Pressure Suppression System tooling.
Developed an OS-agnostic OPC-UA client library and integrated EtherCAT drivers into the CorteX framework for the European Spallation Source.
Freelance project integrating a Yaskawa robot and Allen Bradley PLC to create a fully automated bartending machine for night clubs.
R&D at Nebb on a subsea Variable Speed Drive (VSD) for Brushless DC Motors designed to operate at 3000m depths.
Designed and commissioned Wonderware and Citect SCADA systems across plants in Sweden and the USA, integrating with Nebb's Process Pilot MES.
Created an interface at Johnson Matthey for 16 Yaskawa robots to receive recipe parameters directly from the PLC/SCADA, drastically cutting setup time.
Research and development of novel Unsupervised Machine Learning techniques for Machine Health Estimation and Prognostics applied on the DEMO future fusion power plant.
Thesis: Sensor fusion of Inertial sensors and Global Positioning System using an Extended Kalman Filter on a custom mobile platform (Arduino + BeagleBone Black, Ubuntu).
Graduation project: Algorithm for 2D terrain mapping using a single smartphone camera on a mobile robotic vehicle, combining frame-to-frame triangulation and encoder odometry.
Building neuroplastic, neuroevolution-based Adaptive Neural Controllers (ANC). Crafting tiny AI fibres for embedded control, digital twins, and real-time domain randomisation.
Deep learning for anomaly detection and prognostics using CNN, LSTM, ResNet, and Transformers. Specialized in unsupervised and self-supervised learning methods.
Developing reinforcement learning agents and search-based planning algorithms for robotics and quantitative trading applications.
Long-reach manipulator concept design, kinematics, and constrained workspaces for fusion reactors. Deep industrial automation experience.
N. Petkov, O. Tokatli, K. Zhang, H. Wu and R. Skilton
2025 IEEE International Conference on Robotics and Automation (ICRA), Atlanta, GA, USA
Keelan Keogh, Chang-Hwan Choi, David Cooper, Steven Craig, David Hamilton, Stewart Hockley, James Kent, Chris Lamb, Nikola Petkov, Andrew Robbins, Paul Talbot
Fusion Engineering and Design, Volume 153, 111485
Abstract: As part of the development work performed under the ITER Robotic Test Facility (IRTF) program, development and substantiation of the maintenance strategy for the Vacuum Vessel Pressure Suppression System (VVPSS) must be investigated... During removal the confinement function of vessel must be retained. The remote handling of these components while maintaining the first confinement boundary is challenging due to the access restrictions. To understand and develop the strategy, prototype tooling in a mock-up environment has been created.
Poster J-588 at SOFE 2023
View Poster ListingUKAEA preprint UKAEA-RACE-PR(23)03, submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence
UKAEA Scientific PublicationsFusion Engineering and Design 160
Read Publication