Zander W. Blasingame
I am a postdoctoral fellow at Aithyra in Vienna, working with Alex Tong on generative modelling, stochatic processes, and sampling to solve fundamental problems in natural sciences, e.g., sampling from Boltzmann distributions. Aithyra is a new research institute led by Michael Bronstein working at the interesection of machine learning and life sciences.
Previously, I received my Ph.D. in Electrical and Computer Engineering from Clarkson University in 2025, supervised by Chen Liu, focused on controllable generation with flow/diffusion models and downstream applications in biometrics.
Χριστὸς ὁ βασιλεὺς
Christ the King
In my free time I am an amateur athlete and theologian, actively involved with local ministry. During grad school I played club volleyball (MB/Oppo) at Clarkson and reached a 1145 lb (520 kg) powerlifting total. These days I have gotten back into olympic weightlifting at Das Gym and having been doing more beach volleyball on the Danube.
Open to new collaborations — if you'd like to work together, please don't hesitate to reach out.
Recent highlights all →
- 2026 Apr 30Rex accepted as a Spotlight at ICML 2026.
- 2026 Jan 12Moved to Vienna and joined Aithyra as a Postdoctoral Fellow with Alex Tong.
- 2025 Oct 17Selected as a Top Reviewer at NeurIPS 2025.
- 2025 Sep 18Greed is Good accepted at NeurIPS 2025.
- 2024 Sep 25AdjointDEIS: Efficient Gradients for Diffusion Models accepted in the main track at NeurIPS 2024.
Selected publications all →
bib
@inproceedings{blasingame2026rex,
title = {Rex: A Family of Reversible Exponential (Stochastic) Runge--Kutta Solvers},
author = {Blasingame, Zander W. and Liu, Chen},
booktitle = {Forty-third International Conference on Machine Learning},
year = {2026},
}
bib
@inproceedings{passaro2026stochastic,
title = {Stochastic Few-step Models},
author = {Passaro, Romeo and Blasingame, Zander W. and Bronstein, Michael M. and Tong, Alexander},
booktitle = {ICLR 2026 DeLTa and ReALM-GEN workshops},
year = {2026},
}
bib
@inproceedings{blasingame2025greed,
title = {Greed is Good: A Unifying Perspective on Guided Generation},
author = {Blasingame, Zander W. and Liu, Chen},
booktitle = {The Thirty-ninth Annual Conference on Neural Information Processing Systems},
year = {2025},
}
bib
@inproceedings{blasingame2024adjointdeis,
title = {Adjoint{DEIS}: Efficient Gradients for Diffusion Models},
author = {Blasingame, Zander W. and Liu, Chen},
booktitle = {The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year = {2024},
}
Recent writings all →
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2025 May 23
Deriving the Drift and Diffusion Coefficients for Diffusion Models Where do the popular variance-preserving SDE coefficients actually come from? A derivation, working backwards from the desired transition kernel.
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2024 Dec 03
Gradients for Time-Scheduled Conditional Variables in Neural Differential Equations A càdlàg extension of the continuous adjoint equations for piecewise-continuous conditional inputs.
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2024 Nov 20
The Continuous Adjoint Equations for Diffusion Models A guided tour through AdjointDEIS — exponential integrators for the adjoint ODE/SDE of diffusion models.