Kia Khezeli

35 papers A* 1A 1B 2Journal 28Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Few-Shot LoRA Adaptation of a Flow-Matching Foundation Model for Cross-Spectral Object Detection.
CoRR
Maxim Clouser, Kia Khezeli, John Kalantari
2025 J jnl
CausalARC: Abstract Reasoning with Causal World Models.
CoRR
Jacqueline Maasch, John Kalantari, Kia Khezeli
2025 J jnl
Inference-Time Scaling of Diffusion Models for Infrared Data Generation.
CoRR
Kai A. Horstmann, Maxim Clouser, Kia Khezeli
2024 J jnl
A multi-cohort study on prediction of acute brain dysfunction states using selective state space models.
CoRR
Brandon Silva, Miguel Contreras, Sabyasachi Bandyopadhyay, Yuanfang Ren, Ziyuan Guan, Jeremy A. Balch, Kia Khezeli, Tezcan Ozrazgat-Baslanti, Benjamin Shickel, Azra Bihorac, Parisa Rashidi
2024 J jnl
Transformers and large language models in healthcare: A review.
Artif. Intell. Medicine
Subhash Nerella, Sabyasachi Bandyopadhyay, Jiaqing Zhang, Miguel Contreras, Scott Siegel, Aysegul Bumin, Brandon Silva, Jessica Sena, Benjamin Shickel, Azra Bihorac, Kia Khezeli, Parisa Rashidi
2023 J jnl
AI-Enhanced Intensive Care Unit: Revolutionizing Patient Care with Pervasive Sensing.
CoRR
Subhash Nerella, Ziyuan Guan, Scott Siegel, Jiaqing Zhang, Kia Khezeli, Azra Bihorac, Parisa Rashidi
2023 J jnl
APRICOT: Acuity Prediction in Intensive Care Unit (ICU): Predicting Stability, Transitions, and Life-Sustaining Therapies.
CoRR
Miguel Contreras, Brandon Silva, Benjamin Shickel, Tezcan Ozrazgat-Baslanti, Yuanfang Ren, Ziyuan Guan, Sabyasachi Bandyopadhyay, Kia Khezeli, Azra Bihorac, Parisa Rashidi
2023 J jnl
Biological research and self-driving labs in deep space supported by artificial intelligence.
Nat. Mac. Intell.
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
2023 J jnl
Biomonitoring and precision health in deep space supported by artificial intelligence.
Nat. Mac. Intell.
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
2023 — conf
Dynamic Delirium Prediction in the Intensive Care Unit using Machine Learning on Electronic Health Records.
BHI
Miguel Contreras, Brandon Silva, Benjamin Shickel, Sabyasachi Bandyopadhyay, Ziyuan Guan, Yuanfang Ren, Tezcan Ozrazgat-Baslanti, Kia Khezeli, Azra Bihorac, Parisa Rashidi
2023 J jnl
Predicting risk of delirium from ambient noise and light information in the ICU.
CoRR
Sabyasachi Bandyopadhyay, Ahna Cecil, Jessica Sena, Andrea Davidson, Ziyuan Guan, Subhash Nerella, Jiaqing Zhang, Kia Khezeli, Brooke Armfield, Azra Bihorac, Parisa Rashidi
2023 J jnl
Transformer Models for Acute Brain Dysfunction Prediction.
CoRR
Brandon Silva, Miguel Contreras, Tezcan Ozrazgat-Baslanti, Yuanfang Ren, Ziyuan Guan, Kia Khezeli, Azra Bihorac, Parisa Rashidi
2023 J jnl
Transformers in Healthcare: A Survey.
CoRR
Subhash Nerella, Sabyasachi Bandyopadhyay, Jiaqing Zhang, Miguel Contreras, Scott Siegel, Aysegul Bumin, Brandon Silva, Jessica Sena, Benjamin Shickel, Azra Bihorac, Kia Khezeli, Parisa Rashidi
2022 J jnl
End-to-End Machine Learning Framework for Facial AU Detection in Intensive Care Units.
CoRR
Subhash Nerella, Kia Khezeli, Andrea Davidson, Patrick James Tighe, Azra Bihorac, Parisa Rashidi
2022 J jnl
Multi-dimensional patient acuity estimation with longitudinal EHR tokenization and flexible transformer networks.
Frontiers Digit. Health
Benjamin Shickel, Brandon Silva, Tezcan Ozrazgat-Baslanti, Yuanfang Ren, Kia Khezeli, Ziyuan Guan, Patrick James Tighe, Azra Bihorac, Parisa Rashidi
2021 J jnl
Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs.
CoRR
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
2021 J jnl
Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health.
CoRR
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
2021 J jnl
Invariant Risk Minimisation for Cross-Organism Inference: Substituting Mouse Data for Human Data in Human Risk Factor Discovery.
CoRR
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
2021 A conf
On Information Gain and Regret Bounds in Gaussian Process Bandits.
AISTATS
Sattar Vakili, Kia Khezeli, Victor Picheny
2021 J jnl
On Invariance Penalties for Risk Minimization.
CoRR
Kia Khezeli, Arno Blaas, Frank Soboczenski, Nicholas Chia, John Kalantari
2021 — conf
Prototyping CRISP: A Causal Relation and Inference Search Platform applied to Colorectal Cancer Data.
LifeTech
Samuel Budd, Arno Blaas, Adrienne Hoarfrost, Kia Khezeli, Krittika D'Silva, Frank Soboczenski, Graham Mackintosh, Nicholas Chia, John Kalantari
2021 J jnl
Universally Rank Consistent Ordinal Regression in Neural Networks.
CoRR
W. Garrett Jenkinson, Kia Khezeli, Gavin R. Oliver, John Kalantari, Eric W. Klee
2020 J jnl
On Information Gain and Regret Bounds in Gaussian Process Bandits.
CoRR
Sattar Vakili, Kia Khezeli, Victor Picheny
2020 A* conf
Safe Linear Stochastic Bandits.
AAAI
Kia Khezeli, Eilyan Bitar
2019 J jnl
Safe Linear Stochastic Bandits.
CoRR
Kia Khezeli, Eilyan Bitar
2018 J jnl
Risk-Sensitive Learning and Pricing for Demand Response.
IEEE Trans. Smart Grid
Kia Khezeli, Eilyan Bitar
2017 J jnl
An Online Learning Approach to Buying and Selling Demand Response.
CoRR
Kia Khezeli, Eilyan Bitar
2016 J jnl
A Source-Channel Separation Theorem With Application to the Source Broadcast Problem.
IEEE Trans. Inf. Theory
Kia Khezeli, Jun Chen
2016 J jnl
A Source-Channel Separation Theorem with Application to the Source Broadcast Problem.
CoRR
Kia Khezeli, Jun Chen
2016 — conf
Data-driven pricing of demand response.
SmartGridComm
Kia Khezeli, Eilyan Bitar
2016 J jnl
Risk-Sensitive Learning and Pricing for Demand Response.
CoRR
Kia Khezeli, Eilyan Bitar
2015 J jnl
Outer Bounds on the Admissible Source Region for Broadcast Channels With Correlated Sources.
IEEE Trans. Inf. Theory
Kia Khezeli, Jun Chen
2015 J jnl
Outer Bounds on the Admissible Source Region for Broadcast Channels with Correlated Sources.
CoRR
Kia Khezeli, Jun Chen
2014 B conf
A source-channel separation theorem with application to the source broadcast problem.
ISIT
Kia Khezeli, Jun Chen
2014 B conf
An improved outer bound on the admissible source region for broadcast channels with correlated sources.
ISIT
Kia Khezeli, Jun Chen