Group
Principal Investigator
Lecturer in Computing
Postdoc, Computing, Imperial College London
PhD, Chemical Engineering, University of Texas at Austin
BS, Chemical Engineering, Rice University
Email: c.tsay [at] imperial.ac.uk
Links: [webpage] [google scholar]
Postdoctoral Researchers
Postdoctoral Research Associate [Sept 2024]
PhD, Chemical Engineering, University of Waterloo
MSc, Adv Chemical Engineering w/ PSE, Imperial College London
BASc, Chemical Engineering, University of Toronto
Project: Stochastic optimisation for energy systems
Email: gabriel.patron17 [at] imperial.ac.uk
Links: [webpage] [linkedin]
Postdoctoral Research Associate [March 2025]
PhD, Energy and Nuclear Science and Technology, Politecnico di Milano
MSc, Energy Engineering, Politecnico di Milano
BSc, Building Engineering, Politecnico di Milano
Project: Chemical value chain optimisation
Email: l.ghilardi [at] imperial.ac.uk
Links: [linkedin]
PhD Students
PhD Student, Modern Statistics and Machine Learning
[Oct 2023; co-supervised with Mark van der Wilk]
MS, Computational Sci, Eng, and Maths, University of Texas at Austin
MSci, Physical Natural Sciences, University of Cambridge
Project: Bayesian optimisation for experimental design
Email: b.langdon23 [at] imperial.ac.uk
Links: [linkedin]
PhD Student, Computing [Oct 2023]
MEng, Engineering, University of Cambridge
Project: Optimisation for machine learning models
Email: p.sosnin23 [at] imperial.ac.uk
Links: [linkedin]
PhD Student, Chemical Engineering
[Oct 2023; co-supervised with Antonio del Rio Chanona]
MSc, Adv Chemical Engineering w/ PSE, Imperial College London
BEng, Chemical Engineering, University of Edinburgh
Project: Data-driven optimisation and process control
Email: max.bloor22 [at] imperial.ac.uk
Links: [linkedin]
PhD Student, Computing [Jan 2024]
MSc, Artificial Intelligence, Imperial College London
BSc, Mathematics, University College London
Project: Mixed-integer programming and Bayesian optimisation
Email: yilin.xie22 [at] imperial.ac.uk
Links: [linkedin]
Visiting Researchers
Visiting Student, KTH Royal Institute of Technology
MSc, Optimization and Systems Theory, KTH
MEng, Industrial Management, KTH
Email: nora.moro25 [at] imperial.ac.uk
Available Positions
Funded PhD Position in Optimisation and Machine Learning
Funded PhD Position with BASF/Modern Statistics and Statistical Machine Learning CDT
(details tbc; see post for similar position from previous year)
I encourage prospective postdoctoral researchers, PhD candidates, MEng/MSc students, and undergraduate students interested in our research to contact me. Please include a CV and a brief statement of your research interests. For current Imperial students, I regularly post opportunities for independent projects in the Department of Computing Project Portal. I am also open to student-proposed projects–please reach out to discuss.
Alumni and Completed Research Projects
- Visiting Researchers
- Mujin Cheon, 2023-24, Visiting PhD Student, Korea Advanced Institute of Science and Technology (KAIST); Project: Reinforcement learning for Bayesian optimization.
- Antonio Alcántara Mata, 2023, Visiting PhD Student, Universidad Carlos III de Madrid (UC3M); Project: Optimization over quantile neural networks.
- Computing MEng/MSc Project Students
- Mariia Shapovalova, 2024, Optimization of neural ordinary differential equations.
- Karla Dedeler, 2024, Global training of neural networks.
- Christopher Roberts, 2024, Adversarial examples for logistic regression.
- Alex Morton, 2024 (Multus Biotech), Multi-objective batch Bayesian optimization.
- Yilin Xie, 2023, Global optimization of trained Gaussian Process models. link
- Radu-Alexandru Burtea, 2022, Constrained reinforcement learning for process optimization. link
- Christopher Salvador Marquez Alvarez, 2022, Behavioural patterns of neural surrogate models.
- Jaime Sabal Bermúdez, 2022, Constrained reinforcement learning for process optimisation. link
- Bo Peng, 2021, Data-driven uncertainty sets for robust optimization.
- Jiongjian Cai, 2021, Global optimization of trained Gaussian Process models.
- Charlotte Cronjaeger, 2021, Tensor-based autoencoder models for hyperspectral images. link