Jirong Yi

Welcome to Jirong Yi's webpage.

Short bibliography

I received a PhD degree in computer engineering from University of Iowa under supervision of Prof. Weiyu Xu and Xiaodong Wu. My work at University of Iowa focused on (1) compressed sensing and deep learning theory for medical image reconstruction and (2) large-scale convex optimization for CT-guided cancer radiation therapy treatment planning optimization. During my time with the Computer-aided Diagnosis (CAD) Science team at Hologic Inc, I worked on (1) deep learning for tomosynthesis-based image classification and image object detection, and (2) their applications in breast cancer diagnostic product development and deployment. Since 2023, I have been with Prof. Piotr Slomka's team at Cedars-Sinai Medical Center, and working on (1) deep learning for cardiac perfusion SPECT/CT and PET/CT multimodality image analysis, and (2) their applications in cardiovascular disease prognosis, diagnosis, and treatment. I have long-standing and close collaboration with clinicians and industrial partners including cardiologists, radiologists, medical physicists, radiation oncologists, and medical imaging AI experts. My research has been producing publications in leading journals (e.g., Lancet Digital Health), FDA-approved products (e.g., Genius AI Detection for tomosynthesis-based breast cancer diagnosis), and patents (e.g., CT-guided cancer radiation therapy treatment planning). See ORCID, Google Scholar, and Linkedin for more.

Education

Ph.D., Computer Engineering, University of Iowa, Iowa City, Iowa, USA, 2021
M.S., Computer Engineering, University of Iowa, Iowa City, Iowa, USA, 2020
B.S., Information and Computing Science, Harbin Engineering University, Harbin, Heilongjiang, PRC, 2015

Experience

Postdoctoral Scientist, Division of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA, 10/2023-Now
Machine Learning Research Scientist, Computer-Aided Diagnosis Science, Hologic Inc, Santa Clara, California, USA, 09/2021-08/2023
Engineer, Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China, 07/2015-07/2016

Interests

My interest lies in the intersection of AI/ML, medical image analysis and informatics, and their translation into clinical practice and precision medicine, specifically in the following highly aligned topics:

Medical image analysis, informatics and reconstruction

including compressed sensing, computer vision, and deep learning methods for CT-, SPECT-, PET-, MRI-, and US-based image classification, image object detection, image segmentation, image registration, generative imaging AI, multi-modality image fusion and alignment, vision-language foundation models, agentic imaging AI systems, image reconstruction, image denoising, and image super-resolution.

Translation into clinical practice and precision medicine

including machine learning, computer vision, and deep learning techniques for CT-, SPECT-, PET-, MRI-, and US–based biomarker discovery and quantification, and disease prognosis, diagnosis, and treatment in cardiovascular disease, breast cancer, cervical cancer, prostate cancer, and so on.

Artificial intelligence and computer vision methodologies

including imbalanced learning, small-sample learning, explainable AI, domain adaptation, supervised learning, semi-supervised learning, self-supervised learning, and model calibration.

Projects

My past research projects include: (1) deep learning for PET/CT- and SPECT/CT-based multimodality image analysis for cardiovascular disease prognosis, diagnosis, and treatment; (2) deep learning for tomosynthesis-based for breast cancer diagnosis; (3) large-scale convex optimization for CT-guided cancer radiation therapy treatment planning optimization; and (4) compressed sensing and deep learning theory for medical image reconstruction.

Expertise

My expertise includes artificial intelligence/machine learning (AI/ML), medical image analysis, and their clinical translation.

Vision

My long-term goal is to accelerate innovation and clinical translation in biomedical imaging AI by strategically aligning cutting-edge technology development, advanced medical image analysis, real-world clinical value propositions, and scalable commercialization pathways.

Publications

Refereed Publications: see Google Scholar, * indicate co-first authorships

Jingchao Gao, Ziqing Lu, Raghu Mudumbai, Xiaodong Wu, Jirong Yi, Myung Cho, Catherine Xu, Hui Xie, and Weiyu Xu. Feature compression may be the root cause of adversarial fragility in neural network classifiers (Student Abstract). In Proceedings of the AAAI Conference on Artificial Intelligence 2026. pdf
Robert J.H. Miller, Jirong Yi, Aakash Shanbhag, Krishna Patel, Terrence D. Ruddy, Andrew J. Einstein, Attila Feher, Edward J. Miller, Albert J. Sinusas, Joanna X. Liang, Daniel S. Berman, Damini Dey, and Piotr J. Slomka. Deep learning-derived body composition: association with cardiorespiratory fitness. Accepted to American College of Cardiology (ACC) Annual Meeting 2026. (Available upon request)
Jirong Yi, Krishna K. Patel, Robert J.H. Miller, Anna M. Marcinkiewicz, Aakash Shanbhag, Waseem Hijazi, Mark Lemley, Jianhang Zhou, Joanna X. Liang, Giselle Ramirez, Mouaz Al-Mallah, René R. S. Packard, Terrence D. Ruddy, Andrew J. Einstein, Attila Feher, Edward J. Miller, Wanda Acampa, Steve Mason, Thomas L Rosamond, Leandro Slipczuk, Lixia Wang, Daniel S. Berman, Damini Dey, Marcelo Di Carli, and Piotr J. Slomka. AI-based chest and abdomen body composition quantification from cardiac CT attenuation maps independently improves prognostic prediction of all-cause mortality. Accepted to Society of Nuclear Medicine and Molecular Imaging (SNMMI) Annual Meeting 2026. (Available upon request)
Krishna Patel, Jirong Yi, Anna Marcinkiewicz, Robert JH Miller, Aakash Dhananjay Shanbhag, Aditya Killekar, Mark Lemley, Jianhang Zhou, Giselle Ramirez, Joanna Liang, Samuel Wopperer, Panithaya Chareonthaitawee, Daniel S. Berman, Stacey Knight, Wanda Acampa, Ronny R. Buechel, Thomas L. Rosamond, Rene R.S. Packard, Andrew J. Einstein, Mouaz H. Al-Mallah, Leandro Slipczuk, Estela Isabel Carvajal Juarez, Damini Dey, Marcelo F. Di Carli, and Piotr Slomka. Thoracic body composition outperforms body mass index for predicting coronary microvascular dysfunction (CMD) and adverse cardiac events. Accepted to American College of Cardiology (ACC) Annual Meeting 2026. (Available upon request)
Jingchao Gao, Ziqing Lu, Raghu Mudumbai, Xiaodong Wu, Jirong Yi, Myung Cho, Catherine Xu, Hui Xie, and Weiyu Xu. Feature compression is the root cause of adversarial fragility in neural networks. International Conference on Learning Representations (ICLR) 2026. pdf
Wenhao Zhang, Jacek Kwiecinski, Aakash Shanbhag, Robert J. H. Miller, Shiva Mostafavi, Giselle Ramirez, Jirong Yi, Donghee Han, Damini Dey, Dominika Grodecka, Kajetan Grodecki, Mark Lemley, Paul Kavanagh, Joanna X. Liang, Jianhang Zhou, Valerie Builoff, Jon Hainer, Sylvain Carre, Leanne Barrett, Andrew J. Einstein, Stacey Knight, Steve Mason, Viet T. Le, Wanda Acampa, Samuel Wopperer, Panithaya Chareonthaitawee, Daniel S. Berman, Marcelo F. Di Carli, and Piotr J. Slomka. Multicenter evaluation of interpretable AI for coronary artery disease diagnosis from PET biomarkers. Nature npj Digital Medicine. 2026 Jan 14. pdf (IF 12.4)
Aakash Dhananjay Shanbhag, Anna Marcinkiewicz, Wenhao Zhang, Ryan Zaid, Sebastien Cadet, Mark Lemley, Jirong Yi, Waseem Hijazi, Andrew J. Einstein, Edward J. Miller, Attila Feher, Terrence D. Ruddy, Viet Le, Steve Mason, Stacey Knight, Leandro Slipczuk, Mark Travin, Thomas Rosamond, Samuel Wopperer, Panithaya Chareonthaitawee, Daniel S. Berman, Damini Dey, Marcelo F. Di Carli, Robert JH. Miller, and Piotr J. Slomka. AI-based aortic measurements from cardiac CT attenuation scans identify high-risk patients. American Society of Nuclear Cardiology (ASNC) Annual Meeting 2025. pdf
Jirong Yi, Krishna Patel, Anna Michalowska, Aakash Shanbhag, Robert Miller, Wenhao Zhang, Aditya Killekar, Mark Lemley, Jianhang Zhou, Joanna Liang, Giselle Ramirez, Valerie Builoff, Terrence Ruddy, Andrew Einstein, Attila Feher, Edward Miller, Daniel Berman, Damini Dey, and Piotr Slomka. AI-based integrated body composition assessment from cardiac SPECT CT attenuation maps and its association with mortality. Society of Nuclear Medicine and Molecular Imaging (SNMMI) Annual Meeting 2025. pdf, slides, poster
Jirong Yi, Krishna Patel, Anna Marcinkiewicz, Aakash Dhananjay Shanbhag, Robert JH Miller, Aditya Killekar, Mark Lemley, Jianhang Zhou, Joanna Liang, Giselle Ramirez, Valerie Builoff, Terrence D. Ruddy, Andrew J. Einstein, Attila Feher, Edward James Miller, Daniel S. Berman, Damini Dey, and Piotr Slomka. AI-based liver quantification from cardiac SPECT/CT attenuation maps and association of hepatic steatosis with mortality. American College of Cardiology (ACC) Annual Meeting 2025. pdf, poster
Chunyu Pan, Zhonghao Luo, Jiuchuan Zhang, Lei Shi, Jirong Yi, Zhaohui Yang, and Zhaohui Yang. Federated twin delayed deep deterministic policy gradient for delay and energy consumption optimization in urban air mobility with UAV-assisted MEC. Drones. 2025;9(2):137. pdf (IF 4.8)
Robert J H Miller*, Jirong Yi*, Aakash Shanbhag, Anna Marcinkiewicz, Krishna K Patel, Mark Lemley, Giselle Ramirez, Jolien Geers, Panithaya Chareonthaitawee, Samuel Wopperer, Daniel S Berman, Marcelo Di Carli, Damini Dey, and Piotr J Slomka. Deep learning-quantified body composition from positron emission tomography/computed tomography and cardiovascular outcomes: a multicentre study. European Heart Journal. 2025 Mar 30:ehaf131. pdf (IF 35.7)
Jirong Yi*, Anna M Marcinkiewicz*, Aakash Shanbhag, Robert J H Miller, Jolien Geers, Wenhao Zhang, Aditya Killekar, Nipun Manral, Mark Lemley, Mikolaj Buchwald, Jacek Kwiecinski, Jianhang Zhou, Paul B Kavanagh, Joanna X Liang, Valerie Builoff, Terrence D Ruddy, Andrew J Einstein, Attila Feher, Edward J Miller, Albert J Sinusas, Daniel S Berman, Damini Dey, and Piotr J Slomka. AI-based volumetric six-tissue body composition quantification from CT cardiac attenuation scans enhances mortality prediction: multicenter study. The Lancet Digital Health. 2025 May 16. pdf, medRxiv 2024 (IF 24.1)
Jianhang Zhou, Aakash D Shanbhag, Donghee Han, Anna M Marcinkiewicz, Mikolaj Buchwald, Robert J H Miller, Aditya Killekar, Nipun Manral, Kajetan Grodecki, Jolien Geers, Konrad Pieszko, Jirong Yi, Wenhao Zhang, Parker Waechter, Heidi Gransar, Damini Dey, Daniel S Berman, and Piotr J Slomka. Automated proximal coronary artery calcium identification using artificial intelligence: advancing cardiovascular risk assessment. European Heart Journal-Cardiovascular Imaging. 2025 Jan 16:jeaf007. pdf (IF 6.6)
Jirong Yi*, Jingchao Gao*, Tianming Wang, Xiaodong Wu, and Weiyu Xu. Outlier detection using generative models with theoretical performance guarantees. IEEE Transactions on Information Theory. 2024 Dec 11. pdf (IF 2.8)
Wenhao Zhang, Hidesato Fujito, Aakash Shanbhag, Jirong Yi, Robert Miller, Buchwald Mikolaj, Mark Lemley, Paul Kavanagh, Joanna Liang, Jianhang Zhou, Bryan Bednarski, Valerie Builoff, Marcelo DiCarli, Damini Dey, Daniel Berman, and Piotr Slomka. AI-based approach to improve coronary artery disease diagnosis from cardiac PET. Society of Nuclear Medicine and Molecular Imaging (SNMMI) Annual Meeting 2024. pdf
Jirong Yi, Anna Michalowska, Aakash Shanbhag, Robert Miller, Wenhao Zhang, Aditya Killekar, Nipun Manral, Mark Lemley, Jianhang Zhou, Bryan Bednarski, Joanna Liang, Valerie Builoff, Terrence Ruddy, Andrew Einstein, Attila Feher, Edward Miller, Albert Sinusas, Paul Kavanagh, Damini Dey, Daniel Berman, and Piotr Slomka. Volumetric assessment of body composition from cardiac SPECT CT attenuation maps and association of sarcopenia measures with mortality. Society of Nuclear Medicine and Molecular Imaging (SNMMI) Annual Meeting 2024. pdf, slides, poster
Jirong Yi, Myung Cho, Jingchao Gao, Xiaodong Wu, Weiyu Xu, and Raghuraman Mudumbai. Error correction codes for testing chemical/biological agents: using pooled testing to increase test reliability. In 2023 57th IEEE Asilomar Conference on Signals, Systems, and Computers. 2023 Oct 29 (pp. 960-964). pdf
Jirong Yi, Soura Dasgupta, Jian-Feng Cai, Mathews Jacob, Jingchao Gao, Myung Cho, and Weiyu Xu. Separation-free super-resolution from compressed measurements is possible: an orthonormal atomic norm minimization approach. OUP Information and Inference: A Journal of the IMA. 2023 Sep;12(3):2351-405. pdf, arxiv 2017 (IF 1.6)
Jingchao Gao J, Jirong Yi, Xu W. Outlier detection for generative models with performance guarantees. In 2023 57th Annual Conference on Information Sciences and Systems (CISS). 2023 Mar 22 (pp. 1-6). IEEE. pdf
Kody A Waldstein*, Jirong Yi*, Myung Cho, Raghu Mudumbai, Xiaodong Wu, Steven M Varga, and Weiyu Xu. Use of compressed sensing to expedite high-throughput diagnostic testing for COVID-19 and beyond. PLoS Computational Biology. 2022 Oct 24;18(10):e1010629. pdf, medRxiv 2021 (IF 3.6)
Jirong Yi. Towards adversarial and non-adversarial robustness of machine learning and signal processing: fundamental limits and algorithms (Doctoral dissertation, The University of Iowa). pdf
Jirong Yi and Weiyu Xu. Necessary and sufficient null space condition for nuclear norm minimization in low-rank matrix recovery. IEEE Transactions on Information Theory. 2020 Apr 28;66(10):6597-604. pdf, arxiv 2018 (IF 2.8)
Hui Xie*, Jirong Yi*, Weiyu Xu, and Raghuraman Mudumbai. An information-theoretic explanation for the adversarial fragility of ai classifiers. In 2019 IEEE International Symposium on Information Theory (ISIT). 2019 Jul 7 (pp. 1977-1981). IEEE. pdf, arxiv 2019, arxiv 2019 v2, poster
Jirong Yi, Xiaodong Wu, Quentin Adams, Karolyn Hopfensperger, Kaustubh Patwardhan, Ryan Flynn, Yusung Kim, and Weiyu Xu. Optimized rotating shield brachytherapy treatment plan under treatment time budget. American Association of Physicists in Medicine (AAPM) Annual Meeting 2019. pdf
Chunyu Pan, Jirong Yi, Changchuan Yin, Jian Yu, and Xuehua Li. Joint 3D UAV placement and resource allocation in software-defined cellular networks with wireless backhaul. IEEE Access. 2019 Jul 10;7:104279-93. pdf (IF 3.6)
Weiyu Xu*, Jirong Yi*, Soura Dasgupta, Jian-Feng Cai, Mathews Jacob, and Myung Cho. Separation-free super-resolution from compressed measurements is possible: an orthonormal atomic norm minimization approach. In 2018 IEEE International Symposium on Information Theory (ISIT). 2018 Jun 17 (pp. 76-80). IEEE. pdf, arxiv 2017
Anh Duc Le, Jirong Yi, Yusung Kim, Ryan Flynn, Weiyu Xu, Xiaodong Wu. Keyway selection optimization for multi-helix rotating shield brachytherapy (H-RSBT). American Association of Physicists in Medicine (AAPM) Annual Meeting 2018. pdf
Myung Cho, Xiaodong Wu, Hossein Dadkhah, Jirong Yi, Ryan T Flynn, Yusung Kim, and Weiyu Xu. Fast dose optimization for rotating shield brachytherapy. Medical Physics. 2017 Oct;44(10):5384-92. pdf (IF 3.4)

Preprint Publications: see Google Scholar, * indicate co-first authorships

Robert J.H. Miller, Aakash Shanbhag, Jirong Yi, Paul Kavanagh, Giselle Ramirez, Mark Lemley, Leandro  Slipczuk, Mark I. Travin, Erick Alexanderson, Isabel Carvajal-Juarez, René R.S. Packard, Mouaz Al-Mallah, Andrew J. Einstein, Wanda Acampa, Stacey Knight, Viet T Le, Steve Mason, Samuel Wopperer, Panithaya Chareonthaitawee, Thomas L. Rosamond, Robert A DeKemp, Ronny R Buechel, Daniel S. Berman, Damini Dey, Marcelo F. Di Carli, and Piotr J. Slomka. Opportunistic detection of anemia from routine CT using deep learning: clinical and prognostic implications. Manuscript available upon request.

Jirong Yi*, Krishna K. Patel*, Robert J.H. Miller, Anna M. Marcinkiewicz, Aakash Shanbhag, Waseem Hijazi, Mark Lemley, Jianhang Zhou, Joanna X. Liang, Giselle Ramirez, Leandro Slipczuk, Mark Travin, Erick Alexanderson, Isabel Caraval, René R. S. Packard, Mouaz Al-Mallah, Terrence D. Ruddy, Andrew J. Einstein, Attila Feher, Edward J. Miller, Wanda Acampa, Stacey Knight, Viet T Le, Steve Mason, Vinicius F. Calsavara, Panithaya Chareonthaitawee, Samuel Wopperer, Alan C. Kwan, Lixia Wang, Daniel S. Berman, Jacek Kwiecinski, Damini Dey, Marcelo Di Carli, and Piotr J. Slomka. Development and validation of a body composition index using artificial intelligence from chest CT scans: results from a multi-center longitudinal cohort study. Manuscript available upon request.
Jirong Yi*, Krishna K. Patel*, Robert J.H. Miller, Anna M. Marcinkiewicz, Aakash Shanbhag, Waseem Hijazi, Aditya Killekar, Mark Lemley, Jianhang Zhou, Joanna X. Liang, Giselle Ramirez, Leandro  Slipczuk, Mark Travin, Erick Alexanderson, Isabel Caraval,René R. S. Packard, Mouaz Al-Mallah, Terrence D. Ruddy, Andrew J. Einstein, Attila Feher, Edward J. Miller, Wanda Acampa, Stacey Knight, Viet T Le, Steve Mason, Vinicius F. Calsavara,Panithaya Chareonthaitawee, Samuel Wopperer, Alan Kwan, Lixia Wang, Daniel S. Berman, Damini Dey, Marcelo Di Carli, and Piotr J. Slomka. AI-based body composition measures from attenuation correction CT scans in cardiac imaging correlate with abdominal measures and predicts mortality. Manuscript available upon request.
Krishna K. Patel*, Jirong Yi*, Anna M. Marcinkiewicz, Robert J.H. Miller, Aakash Shanbhag, Aditya Killekar, Mark Lemley, Jianhang Zhou, Giselle Ramirez, Joanna X. Liang, Panithaya Chareonthaitawee, Samuel Wopperer, Viet T. Le, Steve Mason, Stacey Knight, Wanda Acampa, Ronny R. Buechel, Thomas L Rosamond, Rene R. Packard, Andrew J. Einstein, Mouaz Al-Mallah, Isabel Carvajal-Juarez, Erick Alexanderson, Leandro Slipczuk, Annalisa Filtz, Ali Horoub, Mark I. Travin, Daniel S. Berman, Damini Dey, Marcelo Di Carli, and Piotr J. Slomka. Thoracic body composition outperforms body mass index for predicting coronary microvascular dysfunction and adverse cardiac events. (Under reviewing at Circulation) Manuscript available upon request.
Anna Marcinkiewicz, Aakash Shanbhag, Panithaya Chareonthaitawee, Wenhao Zhang, Hasanian Al-Jilaihawi, Ryan Zaid, Sebastien Cadet, Giselle Ramirez, Mark Lemley, Jirong Yi, Waseem Hijazi, Valerie Builoff, Joanna Liang, Andrew Einstein, Edward Miller, Attila Feher, Terrence Ruddy, Viet Le, Steven Mason, Stacey Knight, Leandro Slipczuk, Mark Travin, Thomas Rosamond, Samuel Wopperer, Daniel Berman, Damini Dey, Marcelo Di Carli, Robert Miller, and Piotr Slomka. AI-based aortic measures from attenuation correction CT: transforming byproduct scans into prognostic tools in an international multicenter study. Under reviewing at Circulation: Cardiovascular Imaging. Manuscript available upon request.
Robert J.H. Miller*, Jirong Yi*, Aakash Shanbhag, Krishna Patel, Terrence D. Ruddy, Andrew J. Einstein, Attila Feher, Edward J. Miller, Joanna X. Liang, Giselle Ramireza, Leandro  Slipczuk, Mark I. Travin, Erick Alexanderson, Isabel Carvajal-Juarez, René R.S. Packard, Mouaz Al-Mallah, Wanda Acampa, Stacey Knight, Viet T Le, Steve Mason, Samuel Wopperer, Panithaya Chareonthaitawee, Ronny R. Buechel, Thomas L. Rosamond, Daniel S. Berman,  Damini Dey, Marcelo F. Di Carli, and Piotr J. Slomka. Deep learning-derived body composition: association with cardiorespiratory fitness. (Under reviewing at JACC Imaging) Manuscript available upon request.
Jirong Yi*, Krishna K. Patel*, Robert J.H. Miller, Anna M. Marcinkiewicz, Aakash Shanbhag, Waseem Hijazi, Naga Dharmavaram, Mark Lemley, Assiata S. Kamagate, Jianhang Zhou, Wenhao Zhang, Joanna X. Liang, Giselle Ramirez, Valerie Builoff, Leandro Slipczuk, Mark Travin, Erick Alexanderson, Isabel Carvajal-Juarez, René R. S. Packard, Mouaz Al-Mallah, Terrence D. Ruddy, Andrew J. Einstein, Attila Feher, Edward J. Miller, Wanda Acampa, Stacey Knight, Viet T Le, Steve Mason, Vinicius F. Calsavara, Panithaya Chareonthaitawee, Samuel Wopperer, Alan Kwan, Lixia Wang, Daniel S. Berman, Damini Dey, Marcelo Di Carli, and Piotr J. Slomka. AI-based hepatic steatosis detection and integrated hepatic assessment from cardiac CT attenuation scans enhances all-cause mortality risk stratification: a multi-center study. medRxiv. 2025:2025-06 (2025). pdf (under reviewing at Nature npj Digital Medicine) Manuscript available upon request.
Wenhao Zhang, Robert Miller, Krishna Patel, Aakash Shanbhag, Joanna Liang, Mark Lemley, Giselle Ramirez, Valerie Builoff, Jirong Yi, Jianhang Zhou, Paul Kavanagh, Wanda Acampa, Timothy Bateman, Marcelo Di Carli, Sharmila Dorbala, Andrew Einstein, Mathews Fish, Michael Hauser, Terrence Ruddy, Philipp Kaufmann, Edward Miller, Tali Sharir, Monica Martins, Julian Halcox, Panithaya Chareonthaitawee, Damini Dey, Daniel Berman, and Piotr Slomka. AI-based identification of patients who benefit from revascularization: a multicenter study. medRxiv. 2025:2025-06 (2025). pdf (under reviewing at Nature Communications)
Naga L Dharmavaram, Giselle Ramirez, Aakash Shanbhag, Robert Jh Miller, Paul B Kavanagh, Jirong Yi, Mark Lemley, Valerie Builoff, Anna Marcinkiewicz, Damini Dey, Jon Hainer, Samuel Wopperer, Stacey Knight, Viet T Le, Steve Mason, Erick Alexanderson, Isabel Carvajal-Juarez, René Rs Packard, Thomas L Rosamond, Mouaz H Al-Mallah, Leandro N Slipczuk, Mark I Travin, Wanda Acampa, Andrew J Einstein, Panithaya Chareonthaitawee, Daniel S Berman, Marcelo F Di Carli, and Piotr J Slomka. AI-derived splenic response in cardiac PET predicts mortality: a multi-site study. medRxiv. 2025:2025-06 (2025). pdf (under reviewing at Cardiovascular Research)
Jirong Yi, Qiaosheng Zhang, Zhen Chen, Qiao Liu, Wei Shao, Yusen He, and Yaohua Wang. Mutual information learned regressor: an information-theoretic viewpoint of training regression systems. arXiv preprint arXiv:2211.12685 (2022). pdf
Jirong Yi, Qiaoshen Zhang, Zhen Chen, Qiao Liu, and Wei Shao. Mutual information learned classifiers: an information-theoretic viewpoint of training deep learning classification systems. arXiv preprint arXiv:2210.01000 (2022). pdf
Jirong Yi, Quentin Adams, Karolyn Hopfensperger, Ryan Flynn, Yusung Kim, John Buatti, Weiyu Xu, and Xiaodong Wu. Optimal needle placement for prostate rotating-shield brachytherapy (RSBT). arXiv preprint arXiv:2110.07841 (2021). pdf
Jirong Yi, Myung Cho, Xiaodong Wu, Raghuraman Mudumbai, and Weiyu Xu. Optimal pooling matrix design for group testing without dilution (row degree) constraints. arXiv preprint arXiv:2008.01944 (2020). pdf
Jirong Yi, Raghuraman Mudumbai, and Weiyu Xu. Derivation of information-theoretically optimal adversarial attacks with applications to robust machine learning. arXiv preprint arXiv:2007.14042 (2020). pdf
Jirong Yi, Myung Cho, Xiaodong Wu, Weiyu Xu, and Raghuraman Mudumbai. Error correction codes for COVID-19 virus and antibody testing: using pooled testing to increase test reliability. arXiv preprint arXiv:2007.14919 (2020). pdf
Jirong Yi, Raghuraman Mudumbai, and Weiyu Xu. Low-cost and high-throughput testing of COVID-19 viruses and antibodies via compressed sensing: system concepts and computational experiments. arXiv preprint arXiv:2004.05759 (2020). pdf
Zain Khan, Jirong Yi, Raghuraman Mudumbai, Xiaodong Wu, and Weiyu Xu. Do deep minds think alike? Selective adversarial attacks for fine-grained manipulation of multiple deep neural networks. arXiv preprint rXiv:2003.11816 (2020). pdf
Jirong Yi, Hui Xie, Leixin Zhou, Xiaodong Wu, Weiyu Xu, and Raghuraman Mudumbai. Trust but verify: an information-theoretical explanation for the adversarial fragility of machine learning systems, and a general defense against adversarial attacks. arXiv preprint arXiv:1905.11381 (2019). pdf
Jirong Yi, Zain Khan, Raghuraman Mudumbai, and Weiyu Xu. Designing adversarial attacks against machine learning systems: an optimization framework. pdf

Patents

Xiaodong Wu, Weiyu Xu, Jirong Yi, inventors; University of Iowa Research Foundation UIRF, assignee. High-dose-rate brachytherapy with optimal needle placement for prostate cancer. United States patent application US 18/170,784. 2023 Aug 24. pdf
Weiyu Xu, Xiaodong Wu, Jirong Yi, Raghuraman Mudumbai, Myung Cho, inventors; University of Iowa Research Foundation UIRF, Penn State Research Foundation, assignee. Pooled testing methods using compressed sensing for increasing the throughput and reliability of tests for the detection of defective units in a population. United States patent application US 17/387,863. 2022 Feb 3. pdf

Products

Genius AI Detection, K243341
Genius AI Detection, K221449

Fundings

Post-comprehensive Fellowship Award, University of Iowa Graduate College 2020
Summer Fellowship Award, University of Iowa Graduate College 2020
IEEE ISIT Travel Award, IEEE ISIT 2018

Talks

AI-based integrated body composition assessment from cardiac SPECT CT attenuation maps and its association with mortality. Society of Nuclear Medicine and Molecular Imaging (SNMMI) Annual Meeting, June, 2025
A progressive training approach for object detection in computer aided diagnosis. R&D AI Seminar, Hologic Inc, Santa Clara, 01/24/2023.
Robust AI and domain adaptation series - part I. R&D AI Seminar, Hologic Inc, Santa Clara, California, USA, 11/16/2022.
Vision transformer series - part I. R&D AI Seminar, Hologic Inc, Santa Clara, California, USA, 02/01/2022 and 02/09/2022.
Separation-free super-resolution from compressed measurements is possible: an orthonormal atomic norm minimization approach. IEEE International Symposium on Information Theory (ISIT), June, 2018.

Teaching

ECE 5330 Graph Algorithms and Combinatorial Optimization, U Iowa 2020 spring session, teaching assistant
ECE 5995 Foundations of Deep Learning, U Iowa 2019 fall session, teaching assistant

Services

Journal reviewing

Elsevier Signal Processing, Elsevier Information Sciences
Springer International Journal of Machine Learning and Cybernetics, Springer Signal, Image and Video Processing
IEEE Transactions on Signal Processing, IEEE Transactions on Information Theory, IEEE Transactions on Neural Network and Learning Systems, IEEE Access
Medical Physics, European Heart Journal, SIAM Journal on Imaging Sciences

Conference reviewing

International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2020, 2021, 2023, 2024, 2026
IEEE International Symposium on Information Theory (ISIT) 2021
International Conference on Artificial Intelligence and Statistics (AISTATS) 2022, 2023
AAAI Conference on Artificial Intelligence (AAAI) 2023, 2024, 2025
IEEE International Conference on Acoustics, Speech, & Signal Processing (ICASSP) 2023, 2024, 2025
IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2023, 2024
International Joint Conference on Neural Networks (IJCNN) 2025, 2026

Committee member

Program committee (PC) member of: AAAI 2023, IEEE Statistical Signal Processing (SSP) Workshop 2023, AAAI 2024

Committee member of: College of Engineering Graduate Student Council, University of Iowa, 2021

Memberships

Society of Nuclear Medicine and Molecular Imaging (SNMMI)
American Society of Nuclear Cardiology (ASNC)
Society of Industrial and Applied Mathematics (SIAM)
Institute of Electrical and Electronics Engineer (IEEE)
Institute of Electronics, Information and Communication Engineers (IEICE)
Golden Key International Honor Society, and Phi Beta Delta

Media

Electrical and Computer Engineering professors receive National Science Foundation RAPID grant for novel high-throughput and low-cost COVID-19 testing technologies, University of Iowa College of Engineering News. link
Pooling samples could help you get your COVID-19 test results faster, IEEE Spectrum. link
The mathematics of mass testing for COVID-19, SIAM News. link
Advances rapid COVID-19 testing, University of Iowa Dare to Discover Campaign. link

Recognitions

Best Commercial Strategy Award, HACKUIOWA 2019
Merit-based scholarship 7 times, Harbin Engineering University 2012-2015
Outstanding Graduate, College of Science at Harbin Engineering University 2015
Provincial Merit Student, CUC and Department of Education of Heilongjiang Province 2014
National Endeavor Scholarship, Department of Education of Heilongjiang Province 2014
University Merit Student, Harbin Engineering University 2013
National 3rd Prize in Chinese Mathematical Competition for Math Students, PC of Chinese Math. Society 2013
Provincial 2nd Prize in China Undergraduate Mathematial Contest in Modeling (CUMCM), Department of Education of Heilongjiang and China SIAM 2013
National 3rd Prize in Chinese Mathematical Competition, PC of Chinese Mathematical Society, 2012

Medical imaging and AI collaborators

Xiaodong Wu, Electrical and Computer Engineering, University of Iowa
Weiyu Xu, Electrical and Computer Engineering, University of Iowa
Damini Dey, Bimedical Imaging Research Institute, Cedars-Sinai Medical Center
Piotr Slomka, Artificial Intelligence in Medicine, Cedars-Sinai Medical Center
Jian-Feng Cai, Mathematics, Hong Kong University of Science and Technology
Indranil Guha, MD Anderson Cancer Center
Mathews Jacob, Electrical and Computer Engineering, University of Virginia
Zhenxue Jin, Food and Drug Administration (FDA)
Wei Shao, Quantitative Health, University of Florida
Wenhao Zhang, Automation and Intelligent Sensing, Shanghai Jiaotong University
Qiao Liu, Public Health, Yale University
Qiaosheng Zhang, Shanghai AI Laboratory
Aniket Pramanik, Medical Physics, Memorial Sloan Kettering Cancer Center
Soura Dagupta, Electrical and Computer Engineering, University of Iowa
Raghuraman Mudumbai, Electrical and Computer Engineering, University of Iowa

Medtech and biotech collaborators

Haili Chui, Noah Medical
Adora DSouza, NVIDIA
Bibo Shi, Roche
Ashwini Kshirsagar, Hologic Inc
Biao Chen, Hologic Inc
Junchi Liu, Hologic Inc
Liyang Wei, Hologic Inc
Leixin Zhou, Hologic Inc
Roujia Wang, Merck
Hao Xiong, DeepMind
Lin Xiong, Google
Rui Yan, Atlassian
Qiang Yao, C3.AI
Zhen Chen, Google
Xingxing Liu, Abbott
Dakai Jin, Alibaba Damo Academy
Chang Gao, Siemens

Physician and clinician collaborators

Daniel Berman, Biomedical Imaging Research Institute, Cedars-Sinai Medical Center
Lixia Wang, Biomedical Imaging Research Institue, Cedars-Sinai Medical Center
Andrew Einstein, Medicine, Columbia University
Marcelo Fernando Di Carli, Radiology, Brigham and Women's Hospital
Anna Marcinkiewicz, Radiological Diagnostics, National Medical Institute
Robert Miller, Department of Cardiac Sciences, University of Calgary
Krishna Patel, Cardiology, Mount Sinai
Zhen Li, Radiology, Huazhong University of Science and Technology
Zhongfei Lu, Radiology, Fuwai Hospital
Hao Tang, Radiology, Huazhong University of Science and Technology
Karolyn Hopfensperger, Radiation Oncology, University of Michigan
Yusung Kim, Radiation Oncology, MD Anderson Cancer Center
Ryan Flynn, Radiation Oncology, University of Iowa

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