Ioannis A. Kakadiarias

Ioannis A. Kakadiarias, PhD

Adjunct Professor of Surgery, Academic Institute
Full Affiliate Member, Research Institute
Houston Methodist


Biography

Professor Ioannis A. Kakadiaris, Ph.D. is a Hugh Roy and Lillie Cranz Cullen University Professor of Computer Science, Electrical & Computer Engineering, and Biomedical Engineering at the University of Houston, Houston, TX, USA. He joined UH in August 1997 after a postdoctoral fellowship at the University of Pennsylvania. He earned his B.Sc. in Physics at the University of Athens in Greece, his M.Sc. in Computer Science from Northeastern University and his Ph.D. at the University of Pennsylvania. He is also the founder and director of the Computational Biomedicine Lab. His research interests include biometrics, computer vision, and pattern recognition, biomedical image analysis and cardiovascular informatics.

Dr. Kakadiaris is an international expert in biometrics, data / video analytics, and biomedical computing. His team has made contributions in the areas of 3D face (and ear) recognition, 3D-aided 2D Face Recognition, 2D-2D Face Recognition, and profile-based face recognition. CBL’s 3D-3D face recognition software ranked first in the 3D-shape section of the 2007 Face Recognition Vendor Test (FRVT) organized by NIST, while CBL’s 3D-2D method outperforms the state of the art 2D face recognition methods. Currently, CBL researchers are addressing critical challenges including low resolution data, indoor/outdoor illumination, accurate landmark and pose estimation, cross-resolution matching, and score normalization.

Publications

Building an open-source collaborative platform for migration research: A metadata modeling approach using XML
Bikaki, A, Peters, M, Krozel, J & Kakadiaris, IA 2024, , Knowledge-Based Systems, vol. 299, 111823. https://doi.org/10.1016/j.knosys.2024.111823

What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care
Young, RA, Martin, CM, Sturmberg, JP, Hall, S, Bazemore, A, Kakadiaris, IA & Lin, S 2024, , Journal of the American Board of Family Medicine, vol. 37, no. 2, pp. 332-345. https://doi.org/10.3122/jabfm.2023.230219R1

AI-SNIPS: A Platform for Network Intelligence-Based Pharmaceutical Security
Burt, TA, Passas, N & Kakadiaris, IA 2023, . in B Williams, Y Chen & J Neville (eds), AAAI-23 Special Programs, IAAI-23, EAAI-23, Student Papers and Demonstrations. Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023, vol. 37, AAAI Press, pp. 16407-16409, 37th AAAI Conference on Artificial Intelligence, AAAI 2023, Washington, United States, 2/7/23.

Measuring Public Policy Effectiveness in the Age of Data and AI: Insights from COVID-19
Tibebu, H, Mekonnen, E, Kakadiaris, IA & De Silva, V 2023, . in 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023. 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023, Institute of Electrical and Electronics Engineers Inc. 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023, London, United Kingdom, 5/19/23. https://doi.org/10.1109/GlobConET56651.2023.10150134

Artificial intelligence research strategy of the United States: critical assessment and policy recommendations
Gursoy, F & Kakadiaris, IA 2023, , Frontiers in Big Data, vol. 6, 1206139, pp. 1206139. https://doi.org/10.3389/fdata.2023.1206139

Competencies for the Use of Artificial Intelligence in Primary Care
Liaw, W, Kueper, JK, Lin, S, Bazemore, A & Kakadiaris, I 2022, , Annals of Family Medicine, vol. 20, no. 6, pp. 559-563. https://doi.org/10.1370/afm.2887

Factors Contributing to SARS-CoV-2 Vaccine Hesitancy of Hispanic Population in Rio Grande Valley
Bikaki, A, Machiorlatti, M, Clark, LC, Robledo, CA & Kakadiaris, IA 2022, , Vaccines, vol. 10, no. 8, 1282. https://doi.org/10.3390/vaccines10081282

Advancing primary care with Artificial Intelligence and Machine Learning
Yang, Z, Silcox, C, Sendak, M, Rose, S, Rehkopf, D, Phillips, R, Peterson, L, Marino, M, Maier, J, Lin, S, Liaw, W, Kakadiaris, IA, Heintzman, J, Chu, I & Bazemore, A 2022, , Healthcare, vol. 10, no. 1, 100594. https://doi.org/10.1016/j.hjdsi.2021.100594

Equal Confusion Fairness: Measuring Group-Based Disparities in Automated Decision Systems
Gursoy, F & Kakadiaris, IA 2022, . in KS Candan, TN Dinh, MT Thai & T Washio (eds), Proceedings - 22nd IEEE International Conference on Data Mining Workshops, ICDMW 2022. IEEE International Conference on Data Mining Workshops, ICDMW, vol. 2022-November, Institute of Electrical and Electronics Engineers Inc. pp. 137-146, 22nd IEEE International Conference on Data Mining Workshops, ICDMW 2022, Orlando, United States, 11/28/22. https://doi.org/10.1109/ICDMW58026.2022.00027

Accuracy-Fairness Tradeoff in Parole Decision Predictions: A Preliminary Analysis
Gardner, JW, Gursoy, F & Kakadiaris, IA 2022, . in Proceedings - 2022 IEEE/ACM 9th International Conference on Big Data Computing, Applications and Technologies, BDCAT 2022. Proceedings - 2022 IEEE/ACM 9th International Conference on Big Data Computing, Applications and Technologies, BDCAT 2022, Institute of Electrical and Electronics Engineers Inc. pp. 284-287, 9th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2022, Vancouver, United States, 12/6/22. https://doi.org/10.1109/BDCAT56447.2022.00047

Accuracy, Fairness, and Interpretability of Machine Learning Criminal Recidivism Models
Ingram, E, Gursoy, F & Kakadiaris, IA 2022, . in Proceedings - 2022 IEEE/ACM 9th International Conference on Big Data Computing, Applications and Technologies, BDCAT 2022. Proceedings - 2022 IEEE/ACM 9th International Conference on Big Data Computing, Applications and Technologies, BDCAT 2022, Institute of Electrical and Electronics Engineers Inc. pp. 233-241, 9th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2022, Vancouver, United States, 12/6/22. https://doi.org/10.1109/BDCAT56447.2022.00040

Is Artificial Intelligence the Key to Reclaiming Relationships in Primary Care?
Liaw, W, Kakadiaris, IA & Yang, Z 2021, , American Family Physician, vol. 104, no. 6, pp. 558-559.

TBIOM Special Issue on 'Best Reviewed Papers from IJCB 2020 - Editorial'
Ratha, N, Singh, R, Struc, V, Kakadiaris, IA, Phillips, JP & Vatsa, M 2021, , IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 3, no. 4, pp. 441-442. https://doi.org/10.1109/TBIOM.2021.3128673

Human activity recognition using robust adaptive privileged probabilistic learning
Vrigkas, M, Kazakos, E, Nikou, C & Kakadiaris, IA 2021, , Pattern Analysis and Applications, vol. 24, no. 3, pp. 915-932. https://doi.org/10.1007/s10044-020-00953-x

Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates
Huang, T, Chu, Y, Shams, S, Kim, Y, Annapragada, AV, Subramanian, D, Kakadiaris, I, Gottlieb, A & Jiang, X 2021, , Journal of Biomedical Informatics, vol. 119, 103818. https://doi.org/10.1016/j.jbi.2021.103818

A Case Study of Deep Learning-Based Multi-Modal Methods for Labeling the Presence of Questionable Content in Movie Trailers
Shafaei, M, Smailis, C, Kakadiaris, IA & Solorio, T 2021, . in G Angelova, M Kunilovskaya, R Mitkov & I Nikolova-Koleva (eds), International Conference Recent Advances in Natural Language Processing, RANLP 2021: Deep Learning for Natural Language Processing Methods and Applications - Proceedings. International Conference Recent Advances in Natural Language Processing, RANLP, Incoma Ltd, pp. 1297-1307, International Conference on Recent Advances in Natural Language Processing: Deep Learning for Natural Language Processing Methods and Applications, RANLP 2021, Virtual, Online, 9/1/21. https://doi.org/10.26615/978-954-452-072-4_146

Selected Best Works from Biometrics: Theory, Applications, and Systems 2019
Kakadiaris, IA, Woodard, DL & Schuckers, SAC 2020, , IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 2, no. 4, 9205348, pp. 308-309. https://doi.org/10.1109/TBIOM.2020.3022299

DVRNet: Decoupled visible region network for pedestrian detection
Shi, L, Livermore, C & Kakadiaris, IA 2020, . in IJCB 2020 - IEEE/IAPR International Joint Conference on Biometrics., 9304883, IJCB 2020 - IEEE/IAPR International Joint Conference on Biometrics, Institute of Electrical and Electronics Engineers Inc. 2020 IEEE/IAPR International Joint Conference on Biometrics, IJCB 2020, Virtual, Online, United States, 9/28/20. https://doi.org/10.1109/IJCB48548.2020.9304883

DBLFace: Domain-Based Labels for NIR-VIS Heterogeneous Face Recognition
Le, HA & Kakadiaris, IA 2020, . in IJCB 2020 - IEEE/IAPR International Joint Conference on Biometrics., 9304884, IJCB 2020 - IEEE/IAPR International Joint Conference on Biometrics, Institute of Electrical and Electronics Engineers Inc. 2020 IEEE/IAPR International Joint Conference on Biometrics, IJCB 2020, Virtual, Online, United States, 9/28/20. https://doi.org/10.1109/IJCB48548.2020.9304884

Detecting multi-scale faces using attention-based feature fusion and smoothed context enhancement
Shi, L, Xu, X & Kakadiaris, IA 2020, , IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 2, no. 3, 9091528, pp. 235-244. https://doi.org/10.1109/TBIOM.2020.2993242

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