As of 2020, I am Associate Professor at Queen Mary University London and Principal Scientist at Samsung AI Center, Cambridge. Prior to that, I was Associate Professor at the University of Nottingham, and Senior Research Fellow in the Intelligent Behaviour Understanding Group (iBUG), at Imperial College London. I received the Diploma degree in Electrical and Computer Engineering from Aristotle University of Thessaloniki, Greece, and the M.Sc. and Ph.D. degrees in Signal Processing and Computer Vision both from Imperial College London.


My research interests are mainly in the problems of object detection and tracking, alignment and pose estimation, 3D reconstruction, super-resolution, and recognition with humans and faces being the focal point of my research. I have approached these problems mainly using tools from Mathematical Optimization and Machine Learning. My current focus is on Compute and Data Efficient Deep Learning.

In the aforementioned areas, I have co-authored more than 60 publications (h-index 34, over 6,400 citations to my work according to Google Scholar), many of which in the most authoritative journals (IEEE TPAMI, IJCV, IEEE TIP) and conferences (CVPR, ICCV, ECCV, NeurIPS, ICLR) of my field. For a full list of publications see my Google Scholar.


  • Jing Yang (PhD, UoN)
  • John McDonagh (PhD, UoN)
  • Keerthy Kusumam (PhD, UoN)
  • Dimitris Mallis (PhD, UoN)
  • Ioanna Ntinou (PhD, QMUL)
  • Zhonglin Sun (PhD, QMUL)
  • Yeming Meng (PhD, QMUL)
  • Adrian Bulat (Samsung AI Center)
  • Enrique Sanchez-Lozano (Samsung AI Center)
  • Shiyang Cheng (Samsung AI Center)
  • Stavros Petridis (Samsung AI Center)

Past Supervision

  • Adrian Bulat (PhD)
  • Enrique Sanchez-Lozano (PhD & Post-Doc)
  • Aaron Jackson (PhD; now with UoN)
  • Themos Stafylakis (Marie Curie Research Fellow; now with Omilia)
  • Haris Khan (Post-Doc; now with MBZUAI - UAE)
  • Farhad Bazyari (Post-Doc)


  • H2020 TalkingHeads (Supervisor)
  • EPSRC Facial Deformable Models of Animals (PI)
  • Visible Signs of Feline Pain (PI for Computer Science)
  • TSB Novel computer vision techniques for food quality analysis (PI)


  • Artificial Intelligence (ECS629U)