Researcher in Geometric Machine Learning
m [dot] bahri [at] imperial [dot] ac [dot] uk
I completed my PhD in Computer Science at Imperial College London with Prof. Stefanos Zafeiriou and Prof. Michael Bronstein working on Geometric Deep Learning. I am now a researcher at a Contex.AI working on automatic content moderation with multimodal AI.
18/09/2022: I have submitted my thesis and am about to graduate.
02/12/2022: I successfully passed my PhD viva with no corrections!
11/01/2022: I have officially graduated from the PhD program.
I was a Research Intern at Google AI in Machine Intelligence/Machine Perception for Fall 2018 in New York City. Before that, I interned in Quantitative Research (Systematic Trading) at JPMorgan Chase & Co in London for the Summer 2018. I also worked on EEG decoding with deep learning as a Machine Learning Engineer at Cogitat.io in 2021-2022.
I graduated with an MSc in Advanced Computing from Imperial College London, and a Diplôme d'Ingénieur in Applied Mathematics and CS from Ensimag (Grenoble), both with Distinction.
I am a Qualcomm Innovation Fellow (2019), thanks Qualcomm!
I co-organized the first edition of LOGML, an interdisciplinary summer school in geometry and machine learning in summer 2021. For more information on past and current editions, please visit https://logml.ai/.
Publications & Preprints
2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets
X. Wei, A. Faisal, M. Grosse-Wentrup, A. Gramfort, S. Chevallier, V. Jayaram, C. Jeunet, S. Bakas, S. Ludwig, K. Barmpas, M. Bahri, Y. Panagakis, N. Laskaris, D. A. Adamos, S. Zafeiriou, W. C. Duong, S. M. Gordon, V. J. Lawhern, M. Sliwowski, V. Rouanne, and P. Tempczyk
Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track , PMLR 176:205-219
Binary Graph Neural Networks
M. Bahri, G. Bahl, and S. Zafeiriou
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation
M. Bahri, E. O' Sullivan, S. Gong, F. Liu, X. Liu, M. Bronstein, and S. Zafeiriou
International Journal of Computer Vision (IJCV)
Two patent applications filed.
2017 - 2022
Imperial College London
PhD. Computer Science
Supervisors: Prof. Stefanos Zafeiriou & Prof. Michael Bronstein
Thesis: Advances in Efficient Geometric Deep Learning for Surface and Graph Modelling
2015 - 2016
Imperial College London
MSc. Advanced Computing
Graduated with Distinction
Thesis: Robust Low-Rank Modeling on Tensors: New Algorithms and Extensive Comparisons
2013 - 2016
Grenoble INP - Ensimag
Dip. Ing. Applied Mathematics and Computer Science
Graduated with High Honours
2010 - 2013: Classe Préparatoire aux Grandes Écoles PC*
Selected Awards & Funding
NeurIPS 2021 BEETL Competition: EEG Transfer Learning
First place with team Cogitat.
Amazon AWS Cloud Credits for Research
Awarded on proposal submission.
$6,000 - one year
Qualcomm Innovation Fellowship
Awarded on proposal submission and interviews.
$40,000 - one year
Department of Computing PhD Scholarship
Tuition fees and stipend.
Winton Capital Applied Computing MSc Project Prize
Awarded for the best MSc thesis in Computer Science at Imperial College London (1/188 students).
Co-Organizer - LOGML
London Geometry and Machine Learning Summer-School (LOGML.ai)
Dates: July 12-16, 2021
Week-long interdisciplinary summer school for early-career researchers in mathematics or computer science working at the intersection of geometry and machine learning. The summer school will offer talks and group projects from prominent researchers from academia and industry, as well as a company evening.
IEEE T-PAMI, IEEE T-SMC-Systems, IEEE TIP, IJCV
June 2021 - Present
Machine Learning Engineer
Research and Engineering on EEG decoding for brain-computer interfaces. Applications in healthcare and entertainment.
October 2018 - January 2019
New York, NY
June 2018 - August 2018
JPMorgan Chase & Co.
Quantitative Associate Intern
Equities Systematic Trading QR
April 2017 - July 2017
Speech Recognition Intern
Research & Development on RNN language models
September 2016 - March 2017
Graph modeling for digital marketing
June 2015 - September 2015
Technology & Data