Curriculum Vitae

Education

• 2011 - 2016

  Ph.D. in Computational Biology

  Systems Biology & Machine Learning

  Carnegie Mellon University & University of Pittsburgh

  Pittsburgh, PA

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• 2004 - 2005

  M.S. in Physics

  University of Washington

  Seattle, WA

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• 2000 - 2004

  B.A. in Physics

  Reed College

  Portland, OR

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Experiences

• 2025 - present

  Research Scientist

  AI for biology and human health.

  Allen Institute for Artificial Intelligence

  Seattle, WA

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• 2021 - 2025

  Senior Scientist, Machine Intelligence

  ML / GenAI driven multimodal data analysis and modeling applied to drug discovery and target identification.

  Novo Nordisk

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• 2017 - 2021

  Research Scientist / Senior Scientist

  Computational biology and machine learning – integrative methods for single cell modeling

  Allen Institute for Cell Science

  Seattle, WA

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• 2016 - 2017

  Postdoctoral Fellow

  Hood-Price Lab – personalized medicine & wellness, mouse and human genomics, causal learning

  Institute for Systems Biology

  Seattle, WA

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Last publications

• Enhancing generative perturbation models with LLM-informed gene embeddings

  Authors: Kaspar Märtens, Rory Donovan-Maiye, and Jesper Ferkinghoff-Borg

  ICLR 2024 Workshop on Machine Learning for Genomics Explorations • 2024

• Integrated intracellular organization and its variations in human ips cells

  Authors: Matheus P Viana, Jianxu Chen, Theo A Knijnenburg, Ritvik Vasan, Calysta Yan, Joy E Arakaki, Matte Bailey, Ben Berry, Antoine Borensztejn, Eva M Brown, et al. (including Rory Donovan-Maiye)

  Nature • 2023

  Nature, 613(7943):345–354, 2023.

• A deep generative model of 3d single-cell organization

  Authors: Rory M Donovan-Maiye, Jackson M Brown, Caleb K Chan, Liya Ding, Calysta Yan, Nathalie Gaudreault, Julie A Theriot, Mary M Maleckar, Theo A Knijnenburg, and Gregory R Johnson

  PLOS Computational Biology • 2022

  PLOS Computational Biology, 18(1):e1009155, 2022.

• Cell states beyond transcriptomics: Integrating structural organization and gene expression in hipsc-derived cardiomyocytes

  Authors: Kaytlyn A Gerbin, Tanya Grancharova, Rory M Donovan-Maiye, Melissa C Hendershott, Helen G Anderson, Jackson M Brown, Jianxu Chen, Stephanie Q Dinh, Jamie L Gehring, Gregory R Johnson, et al.

  Cell Systems • 2021

  Cell Systems, 12(6):670–687, 2021.

• Atlas of transcription factor binding sites from encode dnase hypersensitivity data across 27 tissue types

  Authors: Cory C Funk, Alex M Casella, Segun Jung, Matthew A Richards, Alex Rodriguez, Paul Shannon, Rory Donovan-Maiye, Ben Heavner, Kyle Chard, Yukai Xiao, et al.

  Cell Reports • 2020

  Cell Reports, 32(7), 2020.

• Systematic testing of belief-propagation estimates for absolute free energies in atomistic peptides and proteins

  Authors: Rory M Donovan-Maiye, Christopher J Langmead, and Daniel Zuckerman

  Journal of Chemical Theory and Computation • 2017

• Biophysical comparison of atp synthesis mechanisms shows a kinetic advantage for the rotary process

  Authors: Ramu Anandakrishnan, Zining Zhang, Rory Donovan-Maiye, and Daniel M Zuckerman

  Proceedings of the National Academy of Sciences • 2016

  PNAS, 113(40):11220–11225, 2016.

• Unbiased rare event sampling in spatial stochastic systems biology models using a weighted ensemble of trajectories

  Authors: Rory M Donovan, Jose-Juan Tapia, Devin P Sullivan, James R Faeder, Robert F Murphy, Markus Dittrich, and Daniel M Zuckerman

  PLoS Computational Biology • 2016

• Learning mixed graphical models with separate sparsity parameters and stability-based model selection

  Authors: Andrew J Sedgewick, Ivy Shi, Rory M Donovan, and Panatiotis V Benos

  BMC Genomics • 2014

• Efficient stochastic simulation of chemical kinetics networks using a weighted ensemble of trajectories

  Authors: Rory M Donovan, Andrew J Sedgewick, James R Faeder, and Daniel M Zuckerman

  The Journal of Chemical Physics • 2013

  The Journal of Chemical Physics, 139(11):115105, 2013.

Skills