Dynamic Positioning Based on Voronoi Cells (DPVC). - HesamAddin Dashti; Nima Aghaeepour; Sahar Asadi; Meysam Bastani; Zahra Delafkar; Fatemeh Miri Disfani; Serveh Ghaderi; Shahin Kamali; Sepideh Pashami; Alireza Siahpirani (RoboCup, 2005)

Support Vector Clustering: From Local Constraint to Global Stability. - Bahman Yari Saeed Khanloo; Daryanaz Dargahi; Nima Aghaeepour; Ali Masoudi-Nejad (Foundations of Computational Intelligence (6), 2009)

Early immunologic correlates of HIV protection can be identified from computational analysis of complex multivariate T-cell flow cytometry assays. - Nima Aghaeepour; Pratip K. Chattopadhyay; Anuradha Ganesan; Kieran O'Neill; Habil Zare; Adrin Jalali; Holger H. Hoos; Mario Roederer; Ryan Remy Brinkman (Bioinform., 2012)

Ensemble-based prediction of RNA secondary structures. - Nima Aghaeepour; Holger H. Hoos (BMC Bioinform., 2013)

Flow Cytometry Bioinformatics. - Kieran O'Neill; Nima Aghaeepour; Josef Spidlen; Ryan Remy Brinkman (PLoS Comput. Biol., 2013)

Enhanced flowType/RchyOptimyx: a Bioconductor pipeline for discovery in high-dimensional cytometry data. - Kieran O'Neill; Adrin Jalali; Nima Aghaeepour; Holger H. Hoos; Ryan Remy Brinkman (Bioinform., 2014)

Deep profiling of multitube flow cytometry data. - Kieran O'Neill; Nima Aghaeepour; Jeremy Parker; Donna Hogge; Aly Karsan; Bakul Dalal; Ryan Remy Brinkman (Bioinform., 2015)

Session Introduction. - Nikolay Samusik; Nima Aghaeepour; Sean Bendall (PSB, 2017)

GateFinder: projection-based gating strategy optimization for flow and mass cytometry. - Nima Aghaeepour; Erin F. Simonds; David J. H. F. Knapp; Robert V. Bruggner; Karen Sachs; Anthony Culos; Pier Federico Gherardini; Nikolay Samusik; Gabriela K. Fragiadakis; Sean Bendall; Brice Gaudilliere; Martin S. Angst; et al. (Bioinform., 2018)

Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy. - Mohammad Sajjad Ghaemi; Daniel B. DiGiulio; Kévin Contrepois; Benjamin J. Callahan; Thuy T. M. Ngo; Brittany Lee-McMullen; Benoit Lehallier; Anna Robaczewska; David Mcilwain; Yael Rosenberg-Hasson; Ronald J. Wong; Cecele Quaintance; et al. (Bioinform., 2019)

Feature-weighted elastic net: using "features of features" for better prediction. - J. Kenneth Tay; Nima Aghaeepour; Trevor Hastie; Robert Tibshirani (CoRR, 2020)

Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions. - Anthony Culos; Amy Tsai; Natalie Stanley; Martin Becker 003; Mohammad Sajjad Ghaemi; David Mcilwain; Ramin Fallahzadeh; Athena Tanada; Huda Nassar; Camilo Espinosa; Maria Xenochristou; Edward Ganio; et al. (Nat. Mach. Intell., 2020)

Heart Rate and CGM Feature Representation Diabetes Detection From Heart Rate: Learning Joint Features of Heart Rate and Continuous Glucose Monitors Yields Better Representations. - Hootan Rashtian; Solmaz Shariat Torbaghan; Salar Rahili; Michael P. Snyder; Nima Aghaeepour (IEEE Access, 2021)

Early prediction and longitudinal modeling of preeclampsia from multiomics. - Ivana Maric; Kévin Contrepois; Mira N. Moufarrej; Ina A. Stelzer; Dorien Feyaerts; Xiaoyuan Han; Andy Tang; Natalie Stanley; Ronald J. Wong; Gavin M. Traber; Mathew Ellenberger; Alan L. Chang; et al. (Patterns, 2022)

Large-scale correlation network construction for unraveling the coordination of complex biological systems. - Martin Becker 003; Huda Nassar; Camilo Espinosa; Ina A. Stelzer; Dorien Feyaerts; Eloïse Berson; Neda Hajiakhoond Bidoki; Alan L. Chang; Geetha Saarunya; Anthony Culos; Davide De Francesco; Ramin Fallahzadeh; et al. (Nat. Comput. Sci., 2023)

Deep representation learning identifies associations between physical activity and sleep patterns during pregnancy and prematurity. - Neal G. Ravindra; Camilo Espinosa; Eloïse Berson; Thanaphong Phongpreecha; Peinan Zhao; Martin Becker 003; Alan L. Chang; Sayane Shome; Ivana Maric; Davide De Francesco; Samson Mataraso; Geetha Saarunya; et al. (npj Digit. Medicine, 2023)

Digital health application integrating wearable data and behavioral patterns improves metabolic health. - Ashkan Dehghani Zahedani; Arvind Veluvali; Tracey McLaughlin; Nima Aghaeepour; Amir Hosseinian; Saransh Agarwal; Jingyi Ruan; Shital Tripathi; Mark Woodward; Noosheen Hashemi; Michael Snyder 001 (npj Digit. Medicine, 2023)

MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records. - Scott L. Fleming; Alejandro Lozano; William J. Haberkorn; Jenelle A. Jindal; Eduardo Pontes Reis; Rahul Thapa; Louis Blankemeier; Julian Z. Genkins; Ethan Steinberg; Ashwin Nayak 002; Birju S. Patel; Chia-Chun Chiang; et al. (AAAI, 2024)

Generating pregnant patient biological profiles by deconvoluting clinical records with electronic health record foundation models. - David Seong; Samson Mataraso; Camilo Espinosa; Eloïse Berson; S. Momsen Reincke; Lei Xue; Chloe Kashiwagi; Yeasul Kim; Chi-Hung Shu; Philip Chung 005; Marc Ghanem; Feng Xie 004; et al. (Briefings Bioinform., 2024)

Large Language Model Capabilities in Perioperative Risk Prediction and Prognostication. - Philip Chung 005; Christine T. Fong; Andrew M. Walters; Nima Aghaeepour; Meliha Yetisgen; Vikas N. O'Reilly-Shah (CoRR, 2024)

Correction: Digital health application integrating wearable data and behavioral patterns improves metabolic health. - Ashkan Dehghani Zahedani; Tracey McLaughlin; Arvind Veluvali; Nima Aghaeepour; Amir Hosseinian; Saransh Agarwal; Jingyi Ruan; Shital Tripathi; Mark Woodward; Noosheen Hashemi; Michael Snyder 001 (npj Digit. Medicine, 2024)

Mitigation of outcome conflation in predicting patient outcomes using electronic health records. - S. Momsen Reincke; Camilo Espinosa; Philip Chung 005; Tomin James; Eloïse Berson; Nima Aghaeepour (J. Am. Medical Informatics Assoc., 2025)

A machine learning approach to leveraging electronic health records for enhanced omics analysis. - Samson Mataraso; Camilo Espinosa; David Seong; S. Momsen Reincke; Eloïse Berson; Jonathan D. Reiss; Yeasul Kim; Marc Ghanem; Chi-Hung Shu; Tomin James; Yuqi Tan; Sayane Shome; et al. (Nat. Mac. Intell., 2025)

Author Correction: A machine learning approach to leveraging electronic health records for enhanced omics analysis. - Samson Mataraso; Camilo Espinosa; David Seong; S. Momsen Reincke; Eloïse Berson; Jonathan D. Reiss; Yeasul Kim; Marc Ghanem; Chi-Hung Shu; Tomin James; Yuqi Tan; Sayane Shome; et al. (Nat. Mac. Intell., 2025)

Impact of digital health interventions on glycemic control and weight management. - Arvind Veluvali; Ashkan Dehghani Zahedani; Amir Hosseinian; Nima Aghaeepour; Tracey McLaughlin; Mark Woodward; Alex Ditullio; Noosheen Hashemi; Michael P. Snyder (npj Digit. Medicine, 2025)

VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records. - Philip Chung 005; Akshay Swaminathan; Alex J. Goodell; Yeasul Kim; S. Momsen Reincke; Lichy Han; Ben Deverett; Mohammad Amin Sadeghi; Abdel-Badih Ariss; Marc Ghanem; David Seong; Andrew A. Lee; et al. (CoRR, 2025)

MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks. - Suhana Bedi; Hejie Cui; Miguel Fuentes; Alyssa Unell; Michael Wornow; Juan M. Banda; Nikesh Kotecha; Timothy Keyes; Yifan Mai 001; Mert Oez; Hao Qiu; Shrey Jain; et al. (CoRR, 2025)