Shudian Zhao

Shudian Zhao is a Research Fellow in the Optimization and Systems Theory division at KTH Royal Institute of Technology, starting her position in November 2022 under the supervision of Assistant Professor Jan Kronqvist.

Her educational background includes:

• PhD in Technical Mathematics from Alpen-Adria-Universität Klagenfurt (Austria), completed in April 2022
• MSc in Machine Learning from Imperial College London (UK), completed in 2018

Her research spans Optimization, Machine Learning, Semidefinite Programming, Power Systems, Graph Theory, and Neural Networks. Her doctoral work focused on semidefinite programming relaxations for graph partition problems and ADMM-based approaches for large-scale semidefinite programming. She recently completed a project funded by the Digital Future initiative titled "AI Techniques for Power Systems Under Cyberattacks", which applied optimization to enhance neural network robustness. Currently, she is working on strengthened SDP relaxations for maximum welfare problems in the European energy market, co-supervised by Professor Mohammad Reza Hesamzadeh.

She serves as a teaching assistant for the course Applied Optimization and Mathematical Decompositions (FEG3324) and has been involved in research funded by the Digital Future project.