publications

publications by categories in reversed chronological order. generated by jekyll-scholar.

2026

  1. arXiv
    Multimodal Alignment Improves Generalizability of Genomic Biomarker Prediction in Computational Pathology
    Ekaterina Redekop, Eric Zimmermann, Ava P. Amini, Alex X. Lu, Neil Tenenholtz, James B. Hall, and 2 more authors
    arXiv preprint arXiv:2603.00193, 2026
    Paper
  2. arXiv
    Mixed Magnification Aggregation for Generalizable Region-Level Representations in Computational Pathology
    Eric Zimmermann, Julien Viret, Michal Zelechowski, James B. Hall, Neil Tenenholtz, Adam Casson, and 4 more authors
    arXiv preprint arXiv:2602.22176, 2026
    Paper

2025

  1. Matter
    Closed-loop optimization using machine learning for the accelerated design of sustainable cements incorporating algal biomatter
    Meng-Yen Lin, Kristen Severson, Paul Grandgeorge, and Eleftheria Roumeli
    Matter, 2025
    Paper Code
  2. arXiv
    Prism2: Unlocking Multi-modal General Pathology AI with Clinical Dialogue
    Eugene Vorontsov, George Shaikovski, Adam Casson, Julien Viret, Eric Zimmermann, Neil Tenenholtz, and 13 more authors
    arXiv preprint arXiv:2506.13063, 2025
    Paper

2024

  1. Nat. Med.
    A Foundation Model for Clinical-Grade Computational Pathology and Rare Cancers Detection
    Eugene Vorontsov, Alican Bozkurt, Adam Casson, George Shaikovski, Michal Zelechowski, Kristen Severson, and 27 more authors
    Nature Medicine, 2024
    Paper Model
  2. arXiv
    Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology
    Eric Zimmermann, Eugene Vorontsov, Julien Viret, Adam Casson, Michal Zelechowski, George Shaikovski, and 8 more authors
    arXiv preprint arXiv:2408.00738, 2024
    Paper Model
  3. arXiv
    Prism: A Multi-Modal Generative Foundation Model for Slide-Level Histopathology
    George Shaikovski, Adam Casson, Kristen Severson, Eric Zimmermann, Yi Kan Wang, Joseph D. Kunz, and 16 more authors
    arXiv preprint arXiv:2405.10254, 2024
    Paper Model
  4. ISBI
    Improving Mitosis Detection on Histopathology Images Using Large Vision-Language Models
    Ruiwen Ding, James Hall, Neil Tenenholtz, and Kristen Severson
    In 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 2024
    Paper
  5. arXiv
    Adapting Self-Supervised Learning for Computational Pathology
    Eric Zimmermann, Neil Tenenholtz, James Hall, George Shaikovski, Michal Zelechowski, Adam Casson, and 5 more authors
    arXiv preprint arXiv:2405.01688, 2024
    Paper
  6. Cem. Concr. Res.
    Bayesian Design of Concrete with Amortized Gaussian Processes and Multi-Objective Optimization
    Olivia P. Pfeiffer, Kai Gong, Kristen A. Severson, Jie Chen, Jeremy R. Gregory, Soumya Ghosh, and 2 more authors
    Cement and Concrete Research, 2024
    Paper
  7. MIDL
    Considerations for Data Acquisition and Modeling Strategies: Mitosis Detection in Computational Pathology
    Zongliang Ji, Phillip Rosenfield, Christina Eng, Sarah Bettigole, Danielle C. Gibson, Hamid Masoudi, and 3 more authors
    In Medical Imaging with Deep Learning, 2024
    Paper
  8. AAAI Wksp.
    Explainable Concrete Strength Prediction with Amortized Gaussian Process
    Yifei Duan, Kai Gong, Kristen A. Severson, Jie Chen, Jeremy Gregory, and Elsa Olivetti
    In AAAI 2024 Workshop: XAI4Sci, 2024
    Paper

2022

  1. Nat. Comput. Sci.
    Identifying Patterns in Amyotrophic Lateral Sclerosis Progression from Sparse Longitudinal Data
    Divya Ramamoorthy, Kristen Severson, Soumya Ghosh, Karen Sachs, Jonathan D. Glass, Christina N. Fournier, and 1 more author
    Nature Computational Science, 2022
    Paper

2021

  1. J. Electrochem. Soc.
    Statistical Learning for Accurate and Interpretable Battery Lifetime Prediction
    Peter M. Attia, Kristen A. Severson, and Jeremy D. Witmer
    Journal of The Electrochemical Society, 2021
    Paper
  2. Lancet Digit. Health
    Discovery of Parkinson’s Disease States and Disease Progression Modelling: A Longitudinal Data Study Using Machine Learning
    Kristen A. Severson, Lana M. Chahine, Luba A. Smolensky, Murtaza Dhuliawala, Mark Frasier, Kenney Ng, and 2 more authors
    The Lancet Digital Health, 2021
    Paper

2020

  1. MLHC
    Personalized Input-Output Hidden Markov Models for Disease Progression Modeling
    Kristen A. Severson, Lana M. Chahine, Luba Smolensky, Kenney Ng, Jianying Hu, and Soumya Ghosh
    In Machine Learning for Healthcare Conference, 2020
    Paper
  2. SoftwareX
    BEEP: A Python Library for Battery Evaluation and Early Prediction
    Patrick Herring, Chirranjeevi B. Gopal, Muratahan Aykol, Joseph H. Montoya, Abraham Anapolsky, Peter M. Attia, and 11 more authors
    SoftwareX, 2020
    Paper
  3. IEEE TVCG
    DPVis: Visual Analytics with Hidden Markov Models for Disease Progression Pathways
    Bum Chul Kwon, Vibha Anand, Kristen A. Severson, Soumya Ghosh, Zhaonan Sun, Brigitte I. Frohnert, and 2 more authors
    IEEE Transactions on Visualization and Computer Graphics, 2020
    Paper
  4. Nature
    Closed-Loop Optimization of Fast-Charging Protocols for Batteries with Machine Learning
    Peter M. Attia, Aditya Grover, Norman Jin, Kristen A. Severson, Todor M. Markov, Yi-Hao Liao, and 10 more authors
    Nature, 2020
    Paper
  5. npj Digit. Med.
    Identifying Unreliable Predictions in Clinical Risk Models
    Patrick D. Myers, Kenney Ng, Kristen A. Severson, Uri Kartoun, Wangzhi Dai, Wenting Huang, and 2 more authors
    npj Digital Medicine, 2020
    Paper

2019

  1. Nat. Energy
    Data-Driven Prediction of Battery Cycle Life Before Capacity Degradation
    Kristen A. Severson, Peter M. Attia, Norman Jin, Nicholas Perkins, Benben Jiang, Zi Yang, and 8 more authors
    Nature Energy, 2019
    Paper
  2. AAAI
    Unsupervised Learning with Contrastive Latent Variable Models
    Kristen A. Severson, Soumya Ghosh, and Kenney Ng
    In Proceedings of the AAAI Conference on Artificial Intelligence, 2019
    Paper
  3. ICDM
    Generative Oversampling with a Contrastive Variational Autoencoder
    Wangzhi Dai, Kenney Ng, Kristen A. Severson, Wenting Huang, Frederick Anderson, and Collin Stultz
    In IEEE International Conference on Data Mining (ICDM), 2019

2018

  1. J. Intensive Care Med.
    Vasopressin Administration is Associated with Rising Serum Lactate Levels in Patients with Sepsis
    Kristen A. Severson, Laura Ritter-Cox, Jesse D. Raffa, Leo A. Celi, and William J. Gordon
    Journal of Intensive Care Medicine, 2018
    Paper
  2. Comput. Chem. Eng.
    Challenges and Opportunities in Biopharmaceutical Manufacturing Control
    Moo Sun Hong, Kristen A. Severson, Mo Jiang, Amanda E. Lu, J. Christopher Love, and Richard D. Braatz
    Computers & Chemical Engineering, 2018
    Paper

2017

  1. Biotechnol. Bioeng.
    Opportunities and Challenges of Real-Time Release Testing in Biopharmaceutical Manufacturing
    Mo Jiang, Kristen A. Severson, J. Christopher Love, Helen Madden, Patrick Swann, Li Zang, and 1 more author
    Biotechnology and Bioengineering, 2017
    Paper
  2. Processes
    Principal Component Analysis of Process Datasets with Missing Values
    Kristen A. Severson, Mark C. Molaro, and Richard D. Braatz
    Processes, 2017
    Paper
  3. Bioinformatics
    A Method for Learning a Sparse Classifier in the Presence of Missing Data for High-Dimensional Biological Datasets
    Kristen A. Severson, Brinda Monian, J. Christopher Love, and Richard D. Braatz
    Bioinformatics, 2017
    Paper

2016

  1. Annu. Rev. Control
    Perspectives on Process Monitoring of Industrial Systems
    Kristen Severson, Patcharapol Chaiwatanodom, and Richard D. Braatz
    Annual Reviews in Control, 2016
    Paper

2015

  1. Comput. Chem. Eng.
    Elastic Net with Monte Carlo Sampling for Data-Based Modeling in Biopharmaceutical Manufacturing Facilities
    Kristen Severson, Jeremy G. Van Antwerp, Venkatesh Natarajan, Chris Antonio, Jorg Thommes, and Richard D. Braatz
    Computers & Chemical Engineering, 2015
    Paper

2013

  1. AIChE J.
    Optimal Integration for Biodiesel Production Using Bioethanol
    Kristen Severson, Mariano Martı́n, and Ignacio E. Grossmann
    AIChE Journal, 2013
    Paper