Dr. Ning Yu is an Associate Professor in the Department of Computing Sciences at SUNY Brockport, State University of New York. He earned his Ph.D. in Computer Science from Georgia State University and joined SUNY Brockport in 2017, after serving as a Tenure-Track Assistant Professor at the University of South Carolina Upstate.
Dr. Yu has authored over 40 publications in prestigious journals and conferences, including ACM/IEEE Transactions, BMC, PLoS, and Information Sciences. His research interests encompass artificial intelligence, network and information security, big data analytics, deep learning, and cloud computing. An active contributor to academia, he serves on the editorial boards of several international journals and leads a multi-campus SUNY IITG-funded initiative focused on AI education development.
As an educator, Dr. Yu has taught a wide range of courses, including Artificial Intelligence & Machine Learning, Operating Systems, Computer Networks, Cloud Computing, Big Data Analysis, and Computer Security. His excellence in teaching has been recognized through many awards, including “Teacher of the Year,” “Professor Influencer 2022,” and the “Provost’s Post-Tenure Fellowship Award”. He also founded SUNY Brockport’s first ACM SIGAI Student Chapter, the inaugural AI-focused special interest group in Western New York.
Before transitioning to academia, Dr. Yu accumulated 10 years of professional experience in software development and system networking, earning certifications from Cisco, Microsoft, Google, and other leading technology organizations.
Education
Georgia State University, Computer Science, Ph.D.
Southern Illinois University Carbondale, Computer Science, M.S.
Areas of Specialty
Artificial Intelligence, Networking, Embedded Systems, Big Data Analytics, Security, Cloud Computing
Dr. Yu’s research group is actively recruiting student scholars for research projects and ACM Student Chapter software development initiatives, including Azure/GCP/AWS cloud development/deployment, CI/CD, Docker/K8s, software design, architecture, software testing, and more. Interested students are encouraged to contact him via email for further information.
Courses Taught
CSC 414, Operating Systems and Parallel Programming
CSC 434, Artificial Intelligence and Machine Learning
CIS/CSC 419, Computer Networks
CSC 311, Computer Architecture and Organization
CSC 499, Independent Studies
CIS/CSC 421, Computer and Network Security
CSC/CIS 446, Principles of Cloud Computing
CSC 412 Operating Systems
CSC 209, Unix Tools
Research Interests
AI & ML, Big Data, Bioinformatics, Cybersecurity
Provost’s Post-Tenure Fellowship Award, SUNY Brockport, Spring 2024
Teacher of The Year, School of Art & Science, SUNY Brockport, Spring 2023
Google Research Credits Grant, Google Inc. 2021
Scholarly Incentive Award, SUNY Brockport, 2019
Pre-Tenure Proposal Development Grant, SUNY Brockport, 2018
WORLDWIDE TOP 10 FINALISTS, IBM 2017 Watson Analytics Global Competition, 2017
RISE Funding, University of South Carolina Upstate, 2017
William M. Suttles Award, Georgia State University, 2016 (one/two recipients per year)
Outstanding Graduate Student Award, Department of Computer Science, Georgia State University, 2016
PhD Dissertation Grant, Georgia State University, 2016 (20 awarded/year in GSU)
Co-PI,USDANational Institute of Food and Agriculture, 2013-2015
R. Yan, Y. Zheng, N. Yu, C. Liang. Multi-Smart Meter Data Encryption Scheme Based on Distributed Differential Privacy. Big Data Mining and Analytics, 2023, 7(1), 131-141.
R. Yan, Y. Liu, N. Yu. A New Migration and Reproduction Intelligence Algorithm: Case Study in Cloud-Based Microgrid. Information 2023, 14, 562.
W. Peng, R. Wu, W. Dai, N. Yu. Identifying cancer driver genes based on multi-view heterogeneous graph convolutional network and self-attention mechanism. BMC Bioinformatics, 24(16). 2023
R. Yan, Y. Lin, N. Yu, Y. Wu. A Low-carbon Economic Dispatch Model for Electricity Market with Wind Power Based on Improved ALO Algorithm. CAAI Transactions on Intelligence Technology, 8(1), 29-39. 2022
N. Yu and T. Haskins. “Bagging Machine Learning Algorithms: A Generic Computing Framework Based on Machine-Learning Methods for Regional Rainfall Forecasting in Upstate New York.” In Informatics, vol. 8, no. 3, p. 47. July 2021.
W. Zhong, N. Yu and C. Ai, “Applying Big Data Based Deep Learning System to Intrusion Detection,” in Big Data Mining and Analytics, vol. 3, no. 3, pp. 181-195, Sept. 2020, doi: 10.26599/BDMA.2020.9020003.
N. Yu, and K. Darling, “A Low-Cost Approach to Crack Python CAPTCHAs Using AI-Based Chosen-Plaintext Attack”. Applied Sciences, 9(10), 2010, May 2019.
Z. Yu, T. Li, N. Yu, Y. Pan, H. Chen and B. Liu, “Reconstruction of Hidden Representation for Robust Feature Extraction”, ACM Transactions on Intelligent Systems and Technology, vol. 10, No. 2 (18), Dec 2018
N. Yu, Z. Yu and Y. Pan, “A deep learning method for lincRNA detection using auto-encoder algorithm”, BMC Bioinformatics, Dec 2017, Vol. 18(S15):511
Z. Li, Zi. Li, N. Yu and S. Wen, “Locality-based visual outlier detection algorithm for time series”, Security and Communication Networks, vol. 2017, Article ID 1869787, 10 pages, 2017. doi:10.1155/2017/1869787
N. Yu, X. Guo, A. Zelikovsky and Y, Pan, “GaussianCpG: A Gaussian Model for Detection of CpG Island in Human Genome Sequences”, BMC Genomics, 2017, 18(S 4):392
N. Yu, Z. Yu, F. Gu, T. Li, X. Tian and Y. Pan. “Deep Learning in Genomic and Medical Image Data Analysis: Challenges and Approaches”, Journal of Information Processing Systems, Vol.13, No.2, pp.204~214, April 2017
