Tara Akhound-Sadegh

I’m a fourth-year PhD student at McGill University and Mila, supervised by Siamak Ravanbakhsh and Laurence Perreault-Levasseur. I work on generative models, sampling, and geometric deep learning, with applications to biology.

Select Publications

Tara Akhound-Sadegh*, Jungyoon Lee*, Avishek Joey Bose, Valentin De Bortoli, Arnaud Doucet, Michael M. Bronstein, Dominique Beaini, Siamak Ravanbakhsh, Kirill Neklyudov^, Alexander Tong^
(NeurIPS 2025, Spotlight)

Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities

Marta Skreta*, Tara Akhound-Sadegh*, Viktor Ohanesian*, Roberto Bondesan, Alán Aspuru-Guzik, Arnaud Doucet, Rob Brekelmans, Alexander Tong^, Kirill Neklyudov^
(ICML 2025)

Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts

Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael Bronstein, Alexander Tong, Avishek Joey Bose
(Neurips 2024)

Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generationation

Tara Akhound-Sadegh*, Jarrid Rector-Brooks*, Avishek Joey Bose*, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong
(ICML 2024)

Iterated Denoising Energy Matching for Sampling from Boltzmann Densities

Avishek Joey Bose*, Tara Akhound-Sadegh*, Kilian Fatras, Guillaume Huguet, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael Bronstein, Alexander Tong
(ICLR 2024, Spotlight)

SE(3)-Stochastic Flow Matching for Protein Backbone Generation

Tara Akhound-Sadegh, Laurence Perreault-Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh
(Neurips 2023)

Lie Point Symmetry and Physics-Informed Networks

Education

PhD (in progress) - McGill University & Mila
Computer Science
January 2022 - present
GPA: 4.0/4.0
MSc - McGill University & Mila
Computer Science
September 2020 - January 2022 (fast-tracked to PhD)
GPA: 4.0/4.0
Master 1 - L’Université Paris Diderot
Mathématiques Fondamentales et Appliquées
Sept 2019 - June 2020
BSc - University of British Columbia
Engineering Physics, Minor in Honours Mathematics
September 2014 - May 2019

Internships

Visiting Researcher @ Oxford University, Michael Bronstein's group
October 2024 - March 2025
ML Scientist in Residence @ Dreamfold
August 2023 - October 2024

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