Bruno Jedynak

Bruno Jedynak, Maseeh Professor of Mathematical Sciences Fariborz Maseeh Department of Mathematics and StatisticsPortland State University632 SW Hall StreetEast Hall room 210Portland, Oregon, 97201Email:  bruno.jedynak@pdx.eduPhone: 503-725-8283 Fax: 503-725-3661

Biosketch: Bruno M. Jedynak received his doctorate in Applied Mathematics and Statistics from the Université Paris Sud in January 1995. He spent a year as a post-doc in the Department of Statistics at the University of Chicago. He was then appointed as an assistant professor at the Université des Sciences et Technologies de Lille. From 2003 to 2015, he was a faculty member of the Department of Applied Mathematics and Statistics at Johns Hopkins University. In 2015, he moved to the Fariborz Maseeh Department of Mathematics and Statistics at Portland State University in Oregon where he is currently appointed as a Maseeh Professor in Mathematical Sciences.

Research interests: Machine learning, Statistical learning, Statistical modeling, Stochastic search. Applications in computer vision, medical image processing, natural language processing, bioinformatics, and computational neurosciences.  

Publications: PDXScholar, Google scholar citation page, Researchgate profile

Software: Progression score model (GNU license)

Recent teaching:  2023-24: Statistical Learning I, II and III (STAT 671/2/3), Intro to Statistical Learning (STAT 387), and Statistical Consulting (STAT 570).   

Recent vsits: On sabbatical leave during the academic year 2021-22. Visiting professor in the Applied Mathematics & Statistics department at Johns Hopkins University during the fall term of 2021.  Visiting professor at ICM (Paris Brain Institute) during May and June 2022. Visiting professor at UPenn with Christos Davatsikos during Fall 2023. 

News:

4/9/2024: The paper  "Learning Nonparametric Ordinary Differential Equations: Application to Sparse and Noisy Data" by Kamel Lahouel, Michael Wells, David Lovitz, Victor Rielly, Ethan Lew, Bruno Jedynak has been accepted for publication in the Journal of Computational Physics. It is available free of charge at https://authors.elsevier.com/a/1iuyl508H%7EBMP until 5/29/2024. 

6/16/2023: the paper "Learning High-Dimensional Nonparametric Differential Equations via Multivariate Occupation Kernel Functions", Victor Rielly, Kamel Lahouel, Ethan Lew, Michael Wells, Vicky Haney, Bruno Jedynak is available at https://arxiv.org/abs/2306.10189

5/22/2023: the paper "Longitudinal changes in Alzheimer's‐related plasma biomarkers and brain amyloid", Bilgel, M., An, Y., Walker, K.A., Moghekar, A.R., Ashton, N.J., Kac, P.R., Karikari, T.K., Blennow, K., Zetterberg, H., Jedynak, B.M. and Thambisetty, M., was published in Alzheimer's & Dementia.

4/25/2023: the paper "Longitudinal changes in Alzheimer’s-related plasma biomarkers and brain amyloid", Bilgel, M., An, Y., Walker, K.A., Moghekar, A.R., Ashton, N.J., Kac, P.R., Karikari, T.K., Blennow, K., Zetterberg, H., Jedynak, B.M. and Thambisetty, M., 2023.. medRxiv, pp.2023-01, has been accepted for publication in Alzheimer & Dementia.  

4/20/2023: the abstract: "Cluster analysis of the longitudinal progression of plasma biomarkers and amyloid imaging in the Wisconsin Registry for Alzheimer’s Prevention", Michael Wells, Murat Bilgel, Erin Jonaitis, Rebecca Langhough, Lianlian Du, Tobey Betthauser, Kaj Blennow, Nick Ashton, Henrik Zetterberg, Sterling C. Johnson, and Bruno Jedynak, has been accepted as a  poster presentation at the Alzheimer's Imaging Consortium (AIC) Preconference at the Alzheimer's Association International Conference (AAIC 2023) as well as for the AAIC 2023 main conference. 

2/20/2023: the preprint "Learning Nonparametric Ordinary differential Equations: Application to Sparse and Noisy Data", Kamel Lahouel, Michael Wells, David Lovitz, Victor Rielly, Ethan Lew, Bruno Jedynak, available at https://arxiv.org/abs/2206.15215 has ben updated with experiments on the Lorenz system and more comparisons with competing algorithms. 

9/11/2022: The First PSU workshop on learning nonparametric differential equations from data will take place at Portland State University on September 13th, 2022, see https://sites.google.com/pdx.edu/psuworkshoponlearningodes/home 

8/8/2022: Postdoctoral position available in data-intensive statistical learning with flexible joining dates  (Dec 2022, Mar 2023, and Sep 2023).  https://jobs.hrc.pdx.edu/postings/39288 Note that per the National Science Foundation: participating postdoctoral associates supported with NSF funds in RTG must be citizens, nationals, or permanent residents of the United States or its territories and possessions. Contact me at bruno.jedynak@pdx.edu if interested. 

7/20/2022:  Paper available online: Tobey J Betthauser, Murat Bilgel, Rebecca L Koscik, Bruno M Jedynak, Yang An, Kristina A Kellett, Abhay Moghekar, Erin M Jonaitis, Charles K Stone, Corinne D Engelman, Sanjay Asthana, Bradley T Christian, Dean F Wong, Marilyn Albert, Susan M Resnick, Sterling C Johnson, for the Alzheimer's Disease Neuroimaging Initiative, Multi-method investigation of factors influencing amyloid onset and impairment in three cohorts, Brain, 2022;, awac213, https://doi.org/10.1093/brain/awac213 

7/10/2022: the paper "Learning Nonparametric Ordinary differential Equations: Application to Sparse and Noisy Data", Kamel Lahouel, Michael Wells, David Lovitz, Victor Rielly, Ethan Lew, Bruno Jedynak, is available at https://arxiv.org/abs/2206.15215

5/20/2022: the paper "Multi-method investigation of factors influencing amyloid onset and impairment in three cohorts", authored by  Tobey J. Betthauser,  Murat Bilgel,  Rebecca L. Koscik, Bruno M. Jedynak, Yang An, Kristina A. Kellett, Abhay Moghekar, Erin M. Jonaitis, Charles K. Stone,  Corinne D. Engelman, Sanjay Asthana, Bradley T. Christian, Dean F. Wong, Marilyn Albert, Susan M. Resnick, Sterling C. Johnson, the Alzheimer’s Disease Neuroimaging Initiative has been accepted for publication  in Brain

5/13/2022: the NSF training grant RTG: Program in Computation- and Data-Enabled Science has been awarded.  PI: Jay Gopalakrishnan, co-PIs: Jeffrey Ovall, Panayot Vassilevski, Bruno Jedynak, and Daniel Taylor Rodriguez.  This RTG (Research and Training Group) in Computation- And Data-Enabled Science (CADES) produces unique workforce additions with deep knowledge in computational mathematics and statistics and a broad understanding of current issues in data-driven science. Research in CADES, being at the intersection of mathematics, statistics, and computing, is characterized by tremendous intellectual diversity of techniques. Integration across this diversity will result in enhanced research productivity and uniquely qualified trainees. To do so thoughtfully, eight faculty experts at Portland State University (the host institution of this RTG) propose this collaborative vertically integrated research and education enterprise for five years, involving up to five postdoctoral researchers during the grant term, plus three undergraduate and three graduate students per year.

5/6/2022 Kruti Pandya successfully  defended her PhD thesis. Congratulations Kruti. 

1/4/2022: The review paper " The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up" is out . It can be found at https://www.melba-journal.org/papers/2021:019.html

11/01/2021: the paper  "Multi-method investigation of factors influencing amyloid onset and impairment in three cohorts", authored by  Tobey J. Betthauser,  Murat Bilgel,  Rebecca L. Koscik, Bruno M. Jedynak, Yang An, Kristina A. Kellett, Abhay Moghekar, Erin M. Jonaitis, Charles K. Stone,  Corinne D. Engelman, Sanjay Asthana, Bradley T. Christian, Dean F. Wong, Marilyn Albert, Susan M. Resnick, Sterling C. Johnson, the Alzheimer’s Disease Neuroimaging Initiative is available in medRxiv at  https://www.medrxiv.org/content/10.1101/2021.12.02.21266523v1

09/28/2021: the paper "Learning Riemannian metric for disease progression modeling" co-authored by Samuel Gruffaz, Pierre-Emmanuel Poulet, Etienne Maheux, Bruno Michel Jedynak, and Stanley Durrleman has been accepted for publication in the proceedings of NeurIPS 2022. 

02/22/2021:  the grant proposal entitled "OCT and OCTA image processing for retinal assessment of people with MS" has been awarded by the National Eye Institute of NIH. The PI is Jerry Prince. Co-PIS are  Dr. Shiv Saidha, Dr. Peter Calabresi, Dr. Bruno Jedynak, and Dr. Tin Yan Liu.  The PSU subaward will allow to further develop the modeling of disease progression and apply it to an imaging and clinical data cohort of Multiple Sclerosis subjects and controls.  

12/12/2020: We presented our work during the Machine Learning for Mobile Health workshop at NeurIPS 2020. The paper presented is available here:  Unstructured Primary Outcome in Randomized Controlled Trials, authored by Daniel Taylor-Rodriguez, David Lovitz, Nora Mattek, Chao-Yi Wu, Hiroko Dodge, Jeffrey Kaye, and Bruno M. Jedynak. 

6/19/2020: The 1st OHSU-PSU Workshop on Machine Learning for Health was organized online. See  http://www.pi4cs.org/mlhworkshop. More than 80 unique participants attended the sessions. 13 posters were presented by students of OHSU and PSU. Prizes of $300, $200 and $100 were awarded to the best posters. 

6/17/2020: I received the Annual Sigma Xi Award for Outstanding Research for Mathematics. Thank you. 

June 2020: An interdisciplinary group of PSU faculty led by Feng Liu (CS) and comprising Christof Teuscher (ECE), Jay L Nadeau (Physics),  Bruno Jedynak (Math+Stat), Steve L Reichow (Chemistry), and systems architect William Garrick (OIT Research Computing Manager and Architect) has been awarded a two-year, $395,926 NSF grant for a high-performance GPU-based computing cluster. 

June 2020: Our team (viking AI) participated in the BEAT-PD Dream challenge organized by Synapse.org, see https://www.synapse.org/#!Synapse:syn20825169/wiki/596118 . 

3/4/2020: The paper: "A statistical model of FBMC-OQAM signals for predicting spectral regrowth ",  Siyuan Yan, xianzhen Yang, xiao Li, Bruno Jedynak and Fu Li, is accepted for publication in the International Journal of Electronics Letters, doi=10.1080/21681724.2020.1734865.