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High level experience in the development of statistical and machine learning models for the development of better decision-making processes.
M Campi, G Peters, N Azzaoui, T Matsui
IEEE Access 9, 136831 - 136860
M Campi
UCL (University College London)
M Campi, G Peters, D Toczydlowska
PLOS One 18 (4), e0284667
S Wiener-Vacherm, M Campi, P Boizeau, H Thai-Van
Frontiers in Neurology, Section Neuro-Otology 14
M Campi, G Staerman, GW Peters, T Matsui
arXiv preprint arXiv:2403.04405
AISTAT 2025
SR Wiener-Vacher, M Campi, S Caldani, H Thai-Van
JAMA Network Open 7 (5), e2412846-e2412846
M Campi, GW Peters, KA Richards
Franklin Open, 100113
M Campi, GW Peters, P Morvan, M Buhl, H Thai-Van
M Campi, C Gaultier, G Gerenton, P Avan
P Morvan, M Campi, GW Peters, H Thai-Van
M Campi et. all
M Buhl, E Kludt, L Schell-Majoor, M Campi, P Avan
MH Sehatpour, M Campi, CS Nikitopoulos, GW Peters, KA Richards
Invited speaker for the seminar at the Department of Statistics and Applied Probability, University California Santa Barbara.
Invited speaker and chair at WCA.
Invited speaker at internal workshop for audiologists.
Poster presentation.
Internal Seminar at Télécom Paris.
International Workshop on Green Finance and UK Decarbonization Processes at the Business School of Heriot-Watt University.
International Workshop on spatio-temporal statistics methods at ISM in Tokyo.
The 10th International Conference of the ERCIM WG on Computational and Methodological Statistics.
Seminar at the Business School of Essex.
University College London (2016-2021)
Teaching Assistant in the Statistical Science and Computer Science departments,
instructing courses in Probability, Statistics, and Programming Methods.
I received recognition as the Best Tutor within the Computer Science Department (2019) and was
awarded
the UCL Faculty Education
Award. I was also shortlisted for the prestigious UCL Provost's Education Award, competing against
more
experienced faculty members.
Student Supervision
I supervise/ed graduate and doctoral students across multiple institutions:
PhD students at University of California Santa Barbara and University of Technology Sydney focusing on cross-curve interest rate stress testing and green bond yield analysis.
Master's students at the Hearing Institute from various French Schools such as Sorbonne University (Machine Learning), ECE Paris (Acoustics), and AIX-Marseille Université in different audiological applications.
Philosophy
My approach to teaching is grounded in the belief that theoretical concepts must be connected to real-world applications. I emphasize the development of both technical proficiency and critical thinking skills, encouraging students to move beyond formula memorization to deeper understanding of statistical principles.
I value creating an inclusive learning environment where students from diverse backgrounds can thrive. Drawing from my experience as a professional athlete, I incorporate collaborative problem-solving and team-based learning that prepares students for careers in both academic and industry settings.
I believe in adaptive teaching methods that respond to individual learning styles, using a combination of traditional instruction, interactive demonstrations, and hands-on project work to engage students with different strengths and interests.
I maintain active research collaborations across disciplines and institutions
worldwide.
Along my academic journey, I have had the pleasure of working on several interesting problems
with talented researchers.
Duncan Endowed Chair Actuarial & Professor of Statistics for Risk & Insurance.
Professor of physiology, University of Lyon 1.
Institute of Statistical Mathematics.
Software Engineer, NVIDIA, Warsaw.
LMBP - Laboratoire de Mathématiques Blaise Pascal.
PostDoc, (CERIAH), Institut de l'Audition, Institut Pasteur, Paris.
French National Center for Scientific Research (CNRS).
Postdoc at INRIA (Parietal).
University of Technology Sydney (UTS).
Institut Pasteur, CERIAH.
Project Manager, Institut Pasteur, CERIAH.
Associate Professor, UTS Business School.
Lecturer, UTS Sydney.
I am a Postdoctoral Researcher at Institut Pasteur's Hearing Institute, specialized in
statistical
signal processing, statistical machine learning, and time-series modelling.
My research focuses on developing sophisticated methodologies for complex structured data,
combining
statistical modeling and machine learning to create interpretable solutions across diverse
domains.
A summary of my research interests and:
With a multidisciplinary approach and experience in international collaborations, I translate advanced machine learning methodologies into impactful solutions. Drawing from my background as a professional athlete, I bring a strategic, results-driven mindset to research, emphasizing adaptability and problem-solving in complex domains.
