Jeffrey Alido

I am a member of the technical staff at Conquest Labs, where I work on large-scale model training, generative modeling, and inverse problems for biological discovery.

Previously, I received my Ph.D. in Electrical and Computer Engineering from Boston University, where I was advised by Professor Lei Tian in the Computational Imaging Systems Lab and supported by the NSF Graduate Research Fellowship. My doctoral research sat at the intersection of computational imaging, signal processing, and diffusion models. Along the way, I held research internships at insitro and Google. I received my B.S. in Chemical Engineering from UC San Diego.

Outside of work, I play jazz, sing, hoop, and bike.

Email / Google Scholar / GitHub

Jeffrey Alido - Member of Technical Staff at Conquest Labs

Research

	Whitened Score Diffusion: A Structured Prior for Imaging Inverse Problems Jeffrey Alido, Tongyu Li, Yu Sun, Lei Tian NeurIPS 2025 arXiv / code / openreview / model weights We propose Whitened Score diffusion models that learn the Whitened Score function instead of the standard score, enabling stable training on arbitrary Gaussian forward noising processes and providing strong Bayesian priors for imaging inverse problems with structured noise.
	Behind the Blurry Background: Practical Synthetic Features To Enable Robust Imaging Through Scattering Jeffrey Alido, J. Greene, Y. Xue, G. Hu, Y. Li, M. Gilmore, Lei Tian CVPR 2024: Computational Cameras and Displays Workshop, 2024 Practical synthetic features enable robust imaging through scattering media by addressing the blurry background problem in computational imaging applications.
	Robust single-shot 3D fluorescence imaging in scattering media with a simulator-trained neural network Jeffrey Alido, J. Greene, Y. Xue, G. Hu, Y. Li, M. Gilmore, K. J. Monk, B. T. DiBenedictis, I. G. Davison, Lei Tian Optics Express, 2024 paper / supplementary / code A simulator-trained neural network enables robust single-shot 3D fluorescence imaging in scattering media.
	HiLo Microscopy with Caustic Illumination G. Hu, J. Greene, J. Zhu, Q. Yang, Y. Li, Jeffrey Alido, R. Guo, Lei Tian Biomedical Optics Express, 2024 paper / supplementary HiLo microscopy enhanced with caustic illumination for improved optical sectioning.
	EDoF-Miniscope: pupil engineering for extended depth-of-field imaging in a fluorescence Miniscope J. Greene, Y. Xue, Jeffrey Alido, G. Hu, Y. Li, Lei Tian Neurophotonics, 2023 paper Pupil engineering enables extended depth-of-field imaging in fluorescence miniscopes for improved neural imaging.
	Compensating the cell-induced light scattering effect in light-based bioprinting using deep learning J. Guan, S. You, Y. Xiang, J. Schimelman, Jeffrey Alido, X. Ma, M. Tang, S. Chen Biofabrication, 2021 paper Deep learning compensates for cell-induced light scattering effects in light-based bioprinting applications.
	Mitigating Scattering Effects in Light-Based Three-Dimensional Printing Using Machine Learning S. You, J. Guan, Jeffrey Alido, H. H. Hwang, R. Yu, L. Kwe, H. Su, S. Chen ASME Journal of Manufacturing Science and Engineering, 2020 paper Machine learning techniques mitigate scattering effects in light-based three-dimensional printing processes.

Projects

likely.chat

An LLM chat app built around branching conversations, with full transparency and control over your context. I made it for going deep on topics without the context rot of a long linear chat.

Service & Teaching

Peer Reviewer: NeurIPS (2024), Optics Letters (2022-present), Optics Express (2022-present)
Teaching Assistant: Computational Linear Algebra (2023, undergrad), Computational Imaging (2022, grad), Stochastic Processes (2021, grad)

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