Kia Khezeli

According to our database, Kia Khezeli authored at least 27 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A multi-cohort study on prediction of acute brain dysfunction states using selective state space models.

Brandon Silva, Miguel Contreras, Sabyasachi Bandyopadhyay, Yuanfang Ren, Ziyuan Guan, Jeremy A. Balch, Kia Khezeli, Tezcan Ozrazgat-Baslanti, Benjamin Shickel, Azra Bihorac, Parisa Rashidi

CoRR, 2024

2023

Biomonitoring and precision health in deep space supported by artificial intelligence.

Ryan T. Scott, Lauren M. Sanders, Erik L. Antonsen, Jaden J. A. Hastings, Seung-Min Park, Graham Mackintosh, Robert J. Reynolds, Adrienne L. Hoarfrost, Aenor Sawyer, Casey S. Greene, Benjamin S. Glicksberg, Corey A. Theriot, Daniel C. Berrios, Jack Miller, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Stuart J. Chalk, Guillermo M. Delgado-Aparicio, Melissa A. Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, John Kalantari, Kia Khezeli, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Héctor García Martín, Christopher E. Mason, Mona Matar, George I. Mias, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Patricia Parsons-Wingerter, R. K. Prabhu, Amina Ann Qutub, Jon Rask, Amanda Saravia-Butler, Suchi Saria, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Jason H. Yang, Marinka Zitnik, Sylvain V. Costes

Nat. Mac. Intell., March, 2023

Biological research and self-driving labs in deep space supported by artificial intelligence.

Lauren M. Sanders, Ryan T. Scott, Jason H. Yang, Amina Ann Qutub, Héctor García Martín, Daniel C. Berrios, Jaden J. A. Hastings, Jon Rask, Graham Mackintosh, Adrienne L. Hoarfrost, Stuart J. Chalk, John Kalantari, Kia Khezeli, Erik L. Antonsen, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Guillermo M. Delgado-Aparicio, Benjamin S. Glicksberg, Casey S. Greene, Melissa A. Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E. Mason, Mona Matar, George I. Mias, Jack Miller, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Seung-Min Park, Patricia Parsons-Wingerter, R. K. Prabhu, Robert J. Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, Corey A. Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, Sylvain V. Costes

Nat. Mac. Intell., March, 2023

APRICOT: Acuity Prediction in Intensive Care Unit (ICU): Predicting Stability, Transitions, and Life-Sustaining Therapies.

Miguel Contreras, Brandon Silva, Benjamin Shickel, Tezcan Ozrazgat-Baslanti, Yuanfang Ren, Ziyuan Guan, Sabyasachi Bandyopadhyay, Kia Khezeli, Azra Bihorac, Parisa Rashidi

CoRR, 2023

Transformers in Healthcare: A Survey.

Subhash Nerella, Sabyasachi Bandyopadhyay, Jiaqing Zhang, Miguel Contreras, Scott Siegel, Aysegul Bumin, Brandon Silva, Jessica Sena, Benjamin Shickel, Azra Bihorac, Kia Khezeli, Parisa Rashidi

CoRR, 2023

Transformer Models for Acute Brain Dysfunction Prediction.

Brandon Silva, Miguel Contreras, Tezcan Ozrazgat-Baslanti, Yuanfang Ren, Ziyuan Guan, Kia Khezeli, Azra Bihorac, Parisa Rashidi

CoRR, 2023

Predicting risk of delirium from ambient noise and light information in the ICU.

Sabyasachi Bandyopadhyay, Ahna Cecil, Jessica Sena, Andrea Davidson, Ziyuan Guan, Subhash Nerella, Jiaqing Zhang, Kia Khezeli, Brooke Armfield, Azra Bihorac, Parisa Rashidi

CoRR, 2023

AI-Enhanced Intensive Care Unit: Revolutionizing Patient Care with Pervasive Sensing.

Subhash Nerella, Ziyuan Guan, Scott Siegel, Jiaqing Zhang, Kia Khezeli, Azra Bihorac, Parisa Rashidi

CoRR, 2023

Dynamic Delirium Prediction in the Intensive Care Unit using Machine Learning on Electronic Health Records.

Miguel Contreras, Brandon Silva, Benjamin Shickel, Sabyasachi Bandyopadhyay, Ziyuan Guan, Yuanfang Ren, Tezcan Ozrazgat-Baslanti, Kia Khezeli, Azra Bihorac, Parisa Rashidi

Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2023

2022

Multi-dimensional patient acuity estimation with longitudinal EHR tokenization and flexible transformer networks.

Benjamin Shickel, Brandon Silva, Tezcan Ozrazgat-Baslanti, Yuanfang Ren, Kia Khezeli, Ziyuan Guan, Patrick James Tighe, Azra Bihorac, Parisa Rashidi

Frontiers Digit. Health, 2022

End-to-End Machine Learning Framework for Facial AU Detection in Intensive Care Units.

Subhash Nerella, Kia Khezeli, Andrea Davidson, Patrick James Tighe, Azra Bihorac, Parisa Rashidi

CoRR, 2022

2021

Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs.

Lauren M. Sanders, Jason H. Yang, Ryan T. Scott, Amina Ann Qutub, Héctor García Martín, Daniel C. Berrios, Jaden J. A. Hastings, Jon Rask, Graham Mackintosh, Adrienne L. Hoarfrost, Stuart J. Chalk, John Kalantari, Kia Khezeli, Erik L. Antonsen, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Guillermo M. Delgado-Aparicio, Benjamin S. Glicksberg, Casey S. Greene, Melissa A. Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E. Mason, Mona Matar, George I. Mias, Jack Miller, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Seung-Min Park, Patricia Parsons-Wingerter, R. K. Prabhu, Robert J. Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Frank Soboczenski, Michael Snyder, Karthik Soman, Corey A. Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, Sylvain V. Costes

CoRR, 2021

Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health.

Ryan T. Scott, Erik L. Antonsen, Lauren M. Sanders, Jaden J. A. Hastings, Seung-Min Park, Graham Mackintosh, Robert J. Reynolds, Adrienne L. Hoarfrost, Aenor Sawyer, Casey S. Greene, Benjamin S. Glicksberg, Corey A. Theriot, Daniel C. Berrios, Jack Miller, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Stuart J. Chalk, Guillermo M. Delgado-Aparicio, Melissa A. Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, John Kalantari, Kia Khezeli, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Héctor García Martín, Christopher E. Mason, Mona Matar, George I. Mias, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Patricia Parsons-Wingerter, R. K. Prabhu, Amina Ann Qutub, Jon Rask, Amanda Saravia-Butler, Suchi Saria, Nitin Kumar Singh, Frank Soboczenski, Michael Snyder, Karthik Soman, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Jason H. Yang, Marinka Zitnik, Sylvain V. Costes

CoRR, 2021

Invariant Risk Minimisation for Cross-Organism Inference: Substituting Mouse Data for Human Data in Human Risk Factor Discovery.

Odhran O'Donoghue, Paul Duckworth, Giuseppe Ughi, Linus Scheibenreif, Kia Khezeli, Adrienne Hoarfrost, Samuel Budd, Patrick Foley, Nicholas Chia, John Kalantari, Graham Mackintosh, Frank Soboczenski, Lauren M. Sanders

CoRR, 2021

Universally Rank Consistent Ordinal Regression in Neural Networks.

W. Garrett Jenkinson, Kia Khezeli, Gavin R. Oliver, John Kalantari, Eric W. Klee

CoRR, 2021

On Invariance Penalties for Risk Minimization.

Kia Khezeli, Arno Blaas, Frank Soboczenski, Nicholas Chia, John Kalantari

CoRR, 2021

Prototyping CRISP: A Causal Relation and Inference Search Platform applied to Colorectal Cancer Data.

Samuel Budd, Arno Blaas, Adrienne Hoarfrost, Kia Khezeli, Krittika D'Silva, Frank Soboczenski, Graham Mackintosh, Nicholas Chia, John Kalantari

Proceedings of the 3rd IEEE Global Conference on Life Sciences and Technologies, 2021

On Information Gain and Regret Bounds in Gaussian Process Bandits.

Sattar Vakili, Kia Khezeli, Victor Picheny

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Safe Linear Stochastic Bandits.

Kia Khezeli, Eilyan Bitar

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2018

Risk-Sensitive Learning and Pricing for Demand Response.

Kia Khezeli, Eilyan Bitar

IEEE Trans. Smart Grid, 2018

2017

An Online Learning Approach to Buying and Selling Demand Response.

Kia Khezeli, Eilyan Bitar

CoRR, 2017

2016

A Source-Channel Separation Theorem With Application to the Source Broadcast Problem.

Kia Khezeli, Jun Chen

IEEE Trans. Inf. Theory, 2016

A Source-Channel Separation Theorem with Application to the Source Broadcast Problem.

Kia Khezeli, Jun Chen

CoRR, 2016

Data-driven pricing of demand response.

Kia Khezeli, Eilyan Bitar

Proceedings of the 2016 IEEE International Conference on Smart Grid Communications, 2016

2015

Outer Bounds on the Admissible Source Region for Broadcast Channels With Correlated Sources.

Kia Khezeli, Jun Chen

IEEE Trans. Inf. Theory, 2015

Outer Bounds on the Admissible Source Region for Broadcast Channels with Correlated Sources.

Kia Khezeli, Jun Chen

CoRR, 2015

2014

An improved outer bound on the admissible source region for broadcast channels with correlated sources.

Kia Khezeli, Jun Chen

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014