About

I am currently the Research Manager of the Biomedical and Clinical Informatics Lab at the University of Michigan, under the direction of Kayvan Najarian. I am also a Lecturer III in the Department of Computational Medicine and Bioinformatics.

Previously, I was a Ph.D. student at The Graduate Center, CUNY; as well as the Infrastructure Manager of the Westport Public Schools.

My research interests are in theoretical computer science, with a focus on machine learning, cryptography, and computational group theory, and well as computational medicine and computer networking/network security.

Teaching

Fall 2018

BIOINF 501 - Mathematical Foundations for Bioinformatics - Please visit the course website in U-M's Canvas system for all course materials.

Research

Journal Articles

  1. J. Gryak, D. Kahrobaei, C. Martinez-Perez, On The Conjugacy Problem in Certain Metabelian Groups, Glasgow Mathematical Journal, Cambridge University Press (preprint)
  2. J. Gryak, R. Haralick, D. Kahrobaei, Solving the Conjugacy Decision Problem via Machine Learning, Experimental Mathematics, Taylor and Francis (preprint)
  3. J. Gryak, D. Kahrobaei, The Status of Polycyclic Group-Based Cryptography: A Survey and Open Problems, Groups Complexity Cryptology, De Gruyter, Volume 8, Issue 2, 171--186 (2016) (preprint)

Conference Papers

  1. A. Gribov, K. Horan, J. Gryak, D. Kahrobaei, V. Shpilrain, S.M.R. Soroushmehr, K. Najarian, Medical Diagnostics Based on Encrypted Medical Data, BICT 2019
  2. Z. Li, H. Derksen, J.Gryak, M. Hooshmand, A. Wood, H. Ghanbari, P. Gunaratne, K. Najarian, Supraventricular Tachycardia Detection via Machine Learning Algorithms, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
  3. O. Alge, J.Gryak, K. Najarian, Classifying Osteosarcoma Using Meta-Analysis of Gene Expression, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
  4. Z. Li, H. Derksen, J.Gryak, H. Ghanbari, P. Gunaratne, K. Najarian, Atrial Fibrillation Prediction using Recordings from Portable Devices, Conf Proc IEEE Eng Med Biol Soc. 2018 Jul.
  5. S. Ansari, J. Gryak, K. Najarian, Noise Detection in Electrocardiography Signal for Robust Heart Rate Variability Analysis: A Deep Learning Approach, Conf Proc IEEE Eng Med Biol Soc. 2018 Jul.
  6. A. Nguyen, S. Ansari, M. Hooshmand, K. Lin, H. Ghanbari, J. Gryak, K. Najarian, Comparative Study on Heart Rate Variability Analysis for Atrial Fibrillation Detection in Short Single-Lead ECG Recordings, Conf Proc IEEE Eng Med Biol Soc. 2018 Jul.
  7. H. Yao, W. Zhang, R. Malhan, J. Gryak, K. Najarian, Filter-Pruned 3D Convolutional Neural Network for Drowsiness Detection, Conf Proc IEEE Eng Med Biol Soc. 2018 Jul.
  8. H. Yao, C. Williamson, S.M.R. Soroushmehr, J. Gryak, K. Najarian, Hematoma Segmentation Using Dilated Convolutional Neural Network, Conf Proc IEEE Eng Med Biol Soc. 2018 Jul.
  9. M. Hooshmand, S.M.R. Soroushmehr, C. Williamson, J. Gryak, K. Najarian, Automatic Midline Shift Detection in Traumatic Brain Injury, Conf Proc IEEE Eng Med Biol Soc. 2018 Jul.
  10. N. Farzaneh, S.M.R. Soroushmehr, H. Patel, A. Wood, J. Gryak, D. Fessell, K. Najarian, Automated Kidney Segmentation for Traumatic Injured Patients through Ensemble Learning and Active, Conf Proc IEEE Eng Med Biol Soc. 2018 Jul.
  11. A. Wood, S.M.R. Soroushmehr, N. Farzaneh, K. Ward, D. Fessell, J. Gryak, K. Najarian, Fully Automated Spleen Localization and Segmentation Using Machine Learning and 3D Active Contours, Conf Proc IEEE Eng Med Biol Soc. 2018 Jul.
  12. R. Shen, Z. Li, L. Zhang, Y. Hua, M. Mao, Z. Li, Z. Cai, Y. Qiu, J. Gryak, K. Najarian, Osteosarcoma Patients Classification Using Plain X-Rays and Metabolomic Data, Conf Proc IEEE Eng Med Biol Soc. 2018 Jul.

Submitted Articles

  1. E. Sabeti, J. Gryak, H. Derksen, C. Biwer, S. Ansari, H. Isenstein, A. Kratz, K. Najarian, Learning Using Concave and Convex Kernels: Applications in Predicting Quality of Sleep and Level of Fatigue in Fibromyalgia Sufferers, Submitted
  2. H. Yao, R. Stidham, S.M.R. Soroushmehr, J. Gryak, K. Najarian, Automated Detection of Non-Informative Frames for Colonoscopy Through a Combination of Deep Learning and Feature Extraction, Submitted
  3. Z. Li, H. Derksen, J.Gryak, M. Hooshmand, A. Wood, H. Ghanbari, P. Gunaratne, K. Najarian, Markov Models for Detection of Ventricular Arrhythmia, Submitted
  4. B. Fine, J. Gryak, B. Mittag, M. Zabinski, Goodness of Fit for Normality and Poisson, Submitted
  5. E. Sabeti, J. Drews, N. Reamaroon, E. Warner, J. Gryak, M. Sjoding, K. Najarian, Learning Using Partially Available Privileged Information and Label Uncertainty: A Paradigm with Applications in Clinical Decision Support Systems, Submitted
  6. E. Sabeti, J. Drews, N. Reamaroon, J. Gryak M. Sjoding, K. Najarian, Detection Of Acute Respiratory Distress Syndrome By Incorporation Of Label Uncertainty And Partially Available Privileged Information, Submitted
  7. K. Thurnhofer-Hemsi, C. Cui, A. Mishra, J. Gryak, S.M.R. Soroushmehr, J. Wrobel, E. Domìnguez, K. Najarian, E. Lòpez-Rubio, Diabetic Wounds Segmentation Using Convolutional Neural Networks, Submitted
  8. M. Hooshmand, C. Williamson, J. Gryak, V. Rajajee, K. Najarian, Use of Supervised Machine Learning to Predict Outcome in Moderate and Severe Traumatic Brain Injury, Submitted
  9. H. Yao, J. Gryak, A. Attili, H. Derksen, K. Najarian, Automatic Left Ventricle Segmentation Using Dilated and Adversarial Convolutional Neural Network, Submitted

Dissertation

  1. J. Gryak, Solving Algorithmic Problems in Finitely Presented Groups via Machine Learning, City University of New York, April 2017