Statistics, Machine Learning and Simulation (SMLS) Group at EURECOM
Objective: Simulation is a fundamental methodology for understanding complex systems. Examples of such systems appear in a variety of fields, such as geophysical and environmental sciences (e.g., climate, weather, and natural disasters), social sciences (e.g., economics, finance, and insurance), and engineering (e.g., aviation engineering, traffic engineering, and architectural engineering), where simulation has been widely used. However, the reliability of a simulation depends on several factors, such as how accurately the underlying model (e.g., differential equations) can approximate the system of interest, and how accurately the execution of the simulation (e.g., a numerical solution to the differential equations) can approximate the model. For a simulation to be reliable, these factors must be systematically and objectively validated, but doing so manually is challenging.
Our objective is to develop statistical and machine learning methodologies for enhancing the reliability of simulation. As such methodologies themselves must also be reliable, we study mathematical theories to back the methodologies. Moreover, by cooperating with researchers and engineers from applied fields, we identify the needs in practice and develop tools that practitioners can easily use.
Ph.D. students:
Kensuke Mitsuzawa (2021 - Present; co-supervised by Prof Paolo Papotti; funded by Huawei Munich)
Parastoo Pashmchi (2023 - Present; CIFRE with SAP)
Nugzar Gognadze (2023 - Present; funded by National Institute for Environmental Studies, Japan)
Research Engineers:
Mobina Talebinamvar (2023 - Present; funded by the Monaco Government)
Past Postdocs and Research Engineers:
Fangyuan Zhang (2022- 2023; co-supervised by Prof Maurizio Filippone; now a Senior Research Engineer at EDHEC Business School)
Wilfredo-Joshua Robinson-Moore (Oct 2021 - Nov 2022)
Past interns:
Vincent Labarre (2021); ML for traffic simulations; co-supervised by Prof Paolo Papotti)
Thu-Ha Phi (March - Aug 2021; tsunami simulation; co-supervised by Prof Pietro Michiardi)
Mohamed-Zineddine Chedadi (Summer 2020): Theoretical analysis of a simulator calibration method with kernels (supported by NEC).
Hassan El-Mansouri Khoudari (Summer 2020): Theoretical analysis of a simulator calibration method with kernels (supported by NEC).