Research Interests: High
Performance Computing, Machine Learning, Data Science, Computational
Neuroscience, Visualization.
Biographical Sketch:
- Professor: Electrical and Computer Engineering, and
Institute for Advanced Computer Studies, University of Maryland.
- 2018 – 2022: Interim Chair, Department of
Electrical and Computer Engineering, University of Maryland, College Park.
- 2010-2011: Interim VP and CIO, University of Maryland,
College Park.
- 1994-2004: Director of the University of Maryland
Institute for Advanced Computer Studies (UMIACS)
- 2002-2004: Interim Director of the Center for
Bioinformatics and Computational Biology
- Ph.D. 1977, M.S. 1976, Applied Mathematics, Division of
Engineering and Applied Physics, Harvard University.
- Over 250 refereed publications in parallel and
distributed computing, data intensive computing, combinatorial algorithms,
algebraic complexity, and VLSI architectures.
- IEEE and ACM Fellow
- more
Current Projects:
- Machine Learning and Data Science. This research involves a number of efforts related to adversarial
machine learning, disentangled representations, federated learning, lifelong
learning, and techniques related to computational neuroscience. The latter
project addresses the structural and functional organization of the brain
and the characteristics of the corresponding brain networks using DTI and
fMRI data. The project involves collaborations with a number of faculty at
UMD and UMB, and was partially funded under the Center for Health-Related
Informatics and Bioimaging (CHIB) and the Brain and Behavior Initiative
(BBI).
- Parallel Computing. Development of parallel algorithms
and their implementations on current and emerging heterogeneous
multicore/GPU platforms. Applications of interest range from scientific
computing to large scale graph –theoretic problems to machine
learning algorithms for big data.
- Partnership with the Laboratory for Telecommunication
Sciences.
This partnership involves collaborative efforts involving a broad set of
research areas and outreach activities. Current research projects cover
topics in machine learning, quantum networks, wireless, network security,
and visualization.
Teaching:
- Spring
2024: ENEE 436: Foundations of Machine Learning
- Fall
2023: ENEE 290: Introduction to Ordinary Differential Equations and Linear
Algebra
- Fall
2022: ENEE759G: Unsupervised Learning
- Fall
2020 and 2021: ENEE 436: Foundations of Machine Learning
- Fall
2019: ENEE759G: Unsupervised Learning
- Fall
2018, Spring 2019: ENEE101: Introduction to Electrical and Computer
Engineering
Selected Recent Publications:
- HoloCamera: Advanced Volumetric Capture for Cinematic-Quality
VR Applications, J. Heagerty, S. Li, et. al., accepted to IEEE Transactions on Visualization and Computer Graphics, 2024.
- ProtoVAE: Prototypical Networks for
Unsupervised Disentanglement, V. Patil, M. Evanusa,
and J. JaJa, arXiv.2305.09092 https://arxiv.org/abs/2305.09092,
2023.
- Improving
Graph Neural Network with Learnable Permutation Pooling, Y.
Jin and J. JaJa, 2022 IEEE Conference on Data Mining Workshops, Nov.
28-Dec 1, 2022, Orlando, FL.
- TAG: Boosting
Text-VQA via Text-aware Visual Question-answer Generation, J.
Wang, M. Gao, Y. Hu, F. Selvaraju, C. Ramaiah, R. Xu, J. JaJa, and L. Davis
, to appear in the Proceedings of BMVC 2022, Nov. 21-24, London, UK.
- DOT-VAE:
Disentangling One Factor at a Time using Variational
Autoencoders, V. Patil, M. Evanusa,
and J. JaJa, to appear in the Proceedings of the 2022 ICANN conference, Bristol,
UK 6-9 September, 2022.
- FedNet2Net:
Saving Communication and Computations in Federated Learning with Model
Growing, A. Kundu and J. JaJa, Proceedings of the 2022 ICANN,
Bristol, UK, 6-9 September, 2022.
- Class-Similarity
Based Label Smoothing for Confidence Calibration, C. Liu and J.
JaJa, Proceedings of the 30the
International Conference on Artificial Neural Networks
(ICANN’2021), 2021.
- Learning
Brain Dynamics for Decoding and Predicting Individual Differences,
J. Misra, S. Surampudi,
M. Venkatesh, C. Limbachia, J. JaJa, and L.
Pessoa, accepted to PLOS
Computational Biology, 2021.
- Graph
Coarsening with Preserved Spectral Properties, Y. Jin, A. Loukas,
and J. JaJa, accepted to The 23rd
International Conference on Artificial Intelligence and Statistics
(AISTATS 2020).
- Comparing
Functional Connectivity Matrices: A Geometry-Aware Approach applied to
Participant Identification, M. Venkatesh, J. JaJa, and L. Pessoa, Neuroimage, vol 207, Feb 2020.
- Towards a Physiological Scale of Vocal
Fold Agent-based Models of Surgical Inquiry and Repair: Sensitivity
Analysis, Calibration and Validation, A. Garg, S. Yuen, N. Seekhao, G.
Yu, J. Karwowski, M. Powell, J. Sakata, L.
Mongeau, J. JaJa, and N. Li-Jessen, Applied
Sciences, 9(15), 2019.
- Geodesic Distances between Functional
Connectivity Matrices: a Geometry-aware Approach, M. Venkatesh, J.
JaJa, and L. Pessoa, Poster Presentation, Neuroscience 2019, October 19-23, Chicago, IL.
- Analysis and
Forecasting for Traffic Flow Data, Y. Wang and J. JaJa, Sensors and Materials, 31(6), 2143-2154, 2019.
- Feature Prioritization and
Regularization Improve Standard Accuracy and Adversarial Robustness, C. Liu and J. JaJa, to appear in Proceedings for the
International Joint Conference on Artificial Intelligence (IJCAI),
August 2019.
- Brain Dynamics
and Temporal Trajectories during Task and Naturalistic Processing, M. Venkatesh, J. JaJa,
and L. Pessoa, Neuroimage, 2019.
- High-Performance Agent-based Modeling
Applied to Vocal Fold Inflammation and Repair, N. Seekhao, C. Shung,
J. JaJa, L. Mongeau, and N. Li-Jessen, Frontiers in Physiology, April
2018, Vol. 9.
- LEICA: Laplacian Eigenmaps for Group ICA Decomposition, C. Liu, J. JaJa, and L.
Pessoa, Neuroimage,
2017.
- In Situ Visualization for 3D
Agent-Based Vocal Fold Inflammation and Repair Simulation, N. Skeekhao,
J. JaJa, L. Mongeau, and N. Li-Jessen, accepted to Supercomputing Frontiers and Innovations, 2017.
- Real-time Agent-Based Modeling and Simualtion with in-situ Visualization of Complex
Biological Systems: A Case Study on Vocal Fold Inflammation and Healing, N. Seekhao, C. Shung,
J. JaJa, L. Mongeau, and N. Li, Proceedings
of the HiCOMB 2016 Workshop, May 2016,
Chicago.
- A High Performance Implementation of Spectral
Clustering on CPU-GPU Platforms, Y. Jin and J. JaJa, Proceedings of the Parallel Computing and Optimization (PCO 2016)
Workshop, May 2016, Chicago.
- Linking “Toxic Outliers” to Environmental
Justice Communities, M. Collins, I. Munoz, and J. JaJa, Environmental Research Letters, December 2016. Won the ERL Best Article for 2016.
- Connectivity-Based Brain
Parecellations: A Connectivity-Based Atlas for Schizophrenia Research, Q. Wang, R. Chen, J.
JaJa, Y. Jin, E. Hong, and E. Herskovits, Neuroinformatics, October 2015.
- A Data-Driven Approach to Extract
Connectivity Structures from Diffusion Tensor Imaging Data, Y. Jin, J. JaJa, R.
Chen, and E. Herskovits, Proceedings
of the 2015 IEEE International Conference on Big Data (IEEE BigData
2015), Oct 29 – Nov 1, 2015, Santa Clara, CA.
- Achieving Native GPU Performance for
Out-of-Card Large Matrix Multiplication, J. Wu and J. JaJa, Parallel Processing Letters, 2016.
- Resting State Dynamic Functional Network Analysis in
Mild Traumatic Brain Injury, W. Hou, C. Chandler, J. JaJa, and R.
Gullapalli, International
Society for Magnetic Resonance in Medicine ISMRN 2015, Toronto, Ontario, May 30—31, 2015.
- Optimized FFT Computations on Heterogeneous
Platforms with Application to the Poisson Equation. J. Wu and J. JaJa, Journal of Parallel and Distributed
Computing, 2014.
- From Maxout to
Channel-Out: Encoding Information on Sparse Pathways, Q. Wang and J. JaJa, Proceedings of the International
Conference on Artificial Neural Networks, 15-19 September, 2014,
Hamburg, Germany.
- High Performance FFT Based Poisson Solver on a
CPU-GPU Heterogeneous Platform, J. Wu and J. JaJa, International
Parallel and Distributed Processing Symposium (IPDPS), May 2013,
Boston, Massachusetts.
- Hierarchical Exploration of Volumes Using
Multilevel Segmentation of the Intensity-Gradient Histograms, C. Yiu Ip, A.
Varshney, and J. JaJa, VIS 2012, October 2012 (won Best Paper Award for SciVis 2012)
- An Effective Approach to Temporally
Anchored Information Retrieval, Z. Wei and J. JaJa, UMIACS-TR-2012-10, University of
Maryland, College Park, August, 2012.
- Optimized Strategies for Mapping Three-dimensional
FFTs onto CUDA GPUs, J. Wu and J. JaJa, Proceedings of Innovative
Parallel Computing (INPAR) Workshop, San Jose, CA, May
13-14, 2012.
- Constructing Inverted Files: To MapReduce or Not Revisited, Z. Wei and J. JaJa,
Technical Report, University of Maryland, College Park, 2011. Also, to
appear in IEEE Transactions on
Parallel and Distributed Computing.
- A Fast Algorithm for
Constructing Inverted Files on Heterogeneous Platforms, Z. Wei and J. JaJa, International
Parallel and Distributed Processing Symposium (IPDPS), May 2011,
Anchorage, Alaska.
- Optimization of
Linked List Prefix Computations on Multithreaded GPUs Using CUDA, Z Wei and J. JaJa, International
Parallel and Distributed Processing Symposium (IPDPS), April 2010,
Atlanta, GA.
- Techniques to Audit and
Certify the Long Term Integrity of Digital Archives, S. Song and J. JaJa, International
Journal of Digital Libraries, 2010.
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Last Updated, June, 2022.