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Amid increasing demand, CT colleges in arms race to add cybersecurity programs, faculty

Posted on October 31, 2023October 31, 2023 by Guilbeault, Jessica

Man presenting

With thousands of cybersecurity job openings around the state — and entry-level positions that can command a six-figure starting salary — training the next generation of security engineers is a key challenge for Connecticut.

Colleges around the state say the fast-changing curriculum, difficulty of retaining expert faculty, importance of linking closely to industry, and looming challenge of AI make cybersecurity one of the most dynamic fields in education right now.

Another challenge is the ever-widening circle of people who need to be trained in combating cyberattacks.

Benjamin Fuller

“It’s not going to be good enough for there to be 10% or 15% of computer scientists who fix everybody else’s problems,” said Benjamin Fuller, an associate professor in the computer science department at the University of Connecticut.

Four From UConn Named Fellows By AAAS

Posted on October 26, 2023 by Guilbeault, Jessica

The official University of Connecticut seal, in painted gold on an oak panel.

The AAAS is the world’s largest general scientific society.

Four University of Connecticut faculty members have been elected by the American Association for the Advancement of Science (AAAS) to its newest class of fellows. The AAAS is the world’s largest general scientific society and publisher of the Science family of journals.

The four are:

* Bahram Javidi, a professor in the Department of Electrical and Computer Engineering Department in the School of Engineering

* James Magnuson, a professor in the Department of Psychological Sciences in the College of Liberal Arts and Sciences

* Wolfgang Peti, a professor in the Department of Molecular Biology and Biophysics at UConn School of Medicine

* Anthony Vella, a professor and chair of the Department of Immunology at UConn School of Medicine and the Senior Associate Dean for Research Planning and Coordination

CT officials: Cybersecurity a threat, but also a source of jobs

Posted on October 25, 2023October 25, 2023 by Guilbeault, Jessica

Kazem Kazerounian, dean of the UConn School of Engineering, discussed combating cyberattacks during a forum Monday with Gov. Ned Lamont.

HARTFORD — The age of increasing cyberattacks threatens businesses, state infrastructure, government and Connecticut's utilities.

But the current vulnerabilities have also created opportunities to share information and train people to fill an estimated 600,000 future cyber-security jobs across the country, state experts said Monday during a forum at the University of Connecticut School of Business.

"If I was a bad actor, I would think I'd go after the low-hanging fruit" presented by smaller towns in the state, said Gov. Ned Lamont. "I would assume that they would be a little less sophisticated when it comes to cyber protections. I would worry that that's a back door into the Department of Revenue Services or your financial entity, or your utility. I assume this is a really good way to check on those doors that are left ajar and to make sure they're locked. That makes an awful lot of sense to me. Get on-board with these skills. You're going to have to learn these skills. It's an incredibly important skill set to have. There's a guaranteed job."

Cyberattack Continues to Impact ECHN and Waterbury Health: NBC CT News interviews UConn Professor Laurent Michel

Posted on August 23, 2023August 23, 2023 by Guilbeault, Jessica

A systemwide IT outage caused by a cyberattack continues to affect Eastern Connecticut Health Network and Waterbury HEALTH.

Both health networks are owned by Los Angeles-based Prospect Medical, which is experiencing a system-wide outage because of the cyberattack.

ECHN said its hospitals and affiliated providers are continuing to treat patients and its emergency departments are open.

Click view video to watch UConn Professor Laurent Michel's interview with NBC CT News.

View Video @ NBC Connecticut

Please Join Us in Congratulating Caiwen Ding and Derek Aguiar on Their Grant Awards

Posted on July 20, 2023July 20, 2023 by Guilbeault, Jessica

Congratulations to CSE Assistant Professor Caiwen Ding who, in collaboration with Wujie Wen from Lehigh University and Xiaolin Xu from Northeastern University, was awarded a $1.2M NSF grant for “Accelerating Privacy-Preserving Machine Learning as a Service: From Algorithm to Hardware.” This research project focuses on the design of efficient algorithm-hardware co-optimized solutions to accelerate privacy-preserving machine learning on diverse hardware platforms.

Congratulations to CSE Assistant Professor Derek Aguiar who was awarded an NSF CAREER award titled “Practical algorithms and high dimensional statistical methods for multimodal haplotype modelling.” This project addresses major challenges in computational biology and applied machine learning by innovating new robust mathematical models that make few assumptions and efficient training algorithms to leverage massive and complex cellular data.

Journals/Conference Papers Published by Faculty

Posted on June 22, 2023June 22, 2023 by Guilbeault, Jessica

Professor Aguiar Journal and Article Produced

M. Hosseini, A. Palmer, W. Manka, P. G. Grady, V. Patchigolla, J. Bi, R. O’Neill, Z. Chi, and D. Aguiar. Deep statistical modelling of nanopore sequencing translocation times reveals latent non-B DNA structures. Bioinformatics (Supplement_1) (2023). This work was published in Intelligent Systems for Molecular Biology 2023 and will be presented in Lyon, France in late July. Info on ISMB: “The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the flagship meeting of the International Society for Computational Biology (ISCB). The 2023 conference is the 31st ISMB conference, which has grown to become the world’s largest bioinformatics and computational biology conference.”

Non-canonical DNA structures, which deviate from the canonical double helix, play an important role in cellular processes from genomic instability to oncogenesis. Professor Aguiar and Bi’s Ph.D. students Marjan Hosseini and Aaron Palmer led the development of a deep statistical model for predicting non-canonical DNA. This work represents the first computational pipeline to predict non-canonical DNA from nanopore sequencing and will be presented at ISMB 2023, a top conference in computational biology.

Aaron Palmer led the development of the Goodness-of-Fit Autoencoder (GoFAE), a deterministic generative autoencoder that optimizes goodness-of-fit test statistics, and the associated theory to justify its gradient-based optimization. The work will be presented at ICLR 2023, a top machine learning conference.
Palmer, A., Chi, Z., Aguiar, D., & Bi, J. (2023). Auto-Encoding Goodness of Fit. The Eleventh International Conference on Learning Representations.

Learn More @ https://openreview.net/forum?id=JjCAdMUlu9v

Caiwen Ding Produced 11 Conference Papers So Far

[23’ICML] Ran Ran, Xinwei Luo, Wei Wang, Tao Liu, Gang Quan, Xiaolin Xu, Caiwen Ding, Wujie Wen. SpENCNN: Orchestrating Encoding and Sparsity for Fast Homomorphically Encrypted Neural Network Inference. In Proceedings of the 40th International Conference on Machine Learning (ICML 2023). Acceptance rate: 21.4%.
[23’IJCAI] Bingbing Li, Zigeng Wang, Shaoyi Huang, Mikhail Bragin, Ji Li, Caiwen Ding. Towards Lossless Head Pruning through Automatic Peer Distillation for Large Language Models. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI), 2023. Acceptance rate: 15%.
[23′Oakland] Ce Feng∗, Nuo Xu∗, Wujie Wen, Parv Venkitasubramaniam, Caiwen Ding, Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering, IEEE Symposium on Security and Privacy (IEEE S&P “Oakland”).
[23’DAC] Hongwu Peng*, Shanglin Zhou*, Yukui Luo*, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding, PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment, In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC).
[23’DAC] Shanglin Zhou*, Yingjie Li*, Minhan Lou, Weilu Gao, Zhijie Shi, Cunxi Yu, Caiwen Ding, Physics-aware Roughness Optimization for Diffractive Optical Neural Networks, In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC).
[23’CVPR] Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu, You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model, 2023 the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[23’CVPR] Lei Zhang*, Jie Zhang*, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu, Accelerating Dataset Distillation via Model Augmentation, 2023 the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[23’DAC] Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding, Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off, In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC).
[23’DAC] Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen and Caiwen Ding, Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration, In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC), 2023.
[23’ISPASS] Mohsin Shan, Deniz Gurevin, Jared Nye, Caiwen Ding, Omer Khan, Workload Balancing to Unlock Extreme Parallelism for Graph Neural Network Acceleration, In Proceedings of the 2023 International Symposium on Performance Analysis of Systems and Software (ISPASS).
[23’ICRA] Sanbao Su, Yiming Li, Sihong He, Songyang Han, Chen Feng, Caiwen Ding, Fei Miao, Uncertainty Quantification of Collaborative Detection for Self-Driving, In Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA).

Connecticut Advanced Computing Center