Scholar
Amine Natik
Google Scholar ID: WbzZ0IwAAAAJ
PhD Student of Applied Mathematics, Mila
Citations & Impact
Citations
136
H-index
5
i10-index
4
Publications
9
Co-authors
4
list available
Publications
Resume (English only)
Academic Achievements
- - IVADO PhD Excellence Scholarship (2020 - 2024)
- - Doctoral Research Microsoft Diversity Award (2021-2022)
- - Académie Hassan II Des Sciences Et Techniques Scholarship (2014-2023)
- - International Competition for University Students, Third Prize - Bronze medal (2016)
- - International Mathematical Olympiad, Honorable mention (2014)
- - Publications: Consistency of spectral seriation (2021), Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance (2021), Diffusion Earth Mover's Distance and Distribution Embeddings (2021), Neural Networks Manifold Activations Alignment via Probing (2021), Consistency of the spectral seriation algorithm (2019)
Research Experience
- - Lecturer, UdeM: Winter 2022 - MAT1919, Fall 2021 - MAT1680, MAT1681, Winter 2021 - MAT1681
- - Teaching Assistant, UdeM: Summer 2021 - MAT1000, Fall 2020 - STT1903, Winter 2020 - STT3795, Fall 2019 - MAT1400
- - Teaching Assistant, uOttawa: (2017 - 2019) TA for: MAT1700, MAT1702, MAT1720, MAT1722, MAT1730, MAT1732, MAT1741, MAT1318, MAT2775; employed at Mathematics and Statistics Help Center
- - Instructor, Mathematical Olympiad: President of Math&Maroc Association (2019 - 2021) — Coaching the Moroccan olympiad team in Algebra, Number theory, Combinatorics, and Geometry
Education
- - PhD in Applied Mathematics, University of Montreal — MILA (2019 — Present), Supervisors: Guillaume Lajoie and Guy Wolf
- - MSc in Mathematics, University of Ottawa (2017 — 2019), Supervisor: Aaron Smith
- - BSc in Mathematics, Faculté des Sciences de Rabat (2015 — 2017)
Background
- PhD student at the DMS (Département de Mathématiques et de Statistique) at the University of Montreal, a core member at MILA (Montreal Institute of Learning Algorithms), and a PhD fellow of IVADO (Institut de valorisation des données). Co-supervised by Guillaume Lajoie and Guy Wolf. Research interests include understanding the information encoded in the hidden layers of trained deep neural networks, using tools from manifold learning, graph signal processing, representation learning, and dynamical systems. Also interested in research at the intersection of AI and Neuroscience.
Miscellany
- LinkedIn: linkedin.com/in/amine-natik
- Email: amine.natik@umontreal.ca
- GitHub: github/amine-natik
- Google Scholar: scholar.google.com/amine-natik
