Machine Learning

Uncovering New Data Science, Solutions

people talk and laugh in computer lab, bird's-eye viewSJSU faculty work in machine learning includes deep learning, big data, new technologies, and tools for integrating multidisciplinary knowledge in practical analytics projects. This includes mining and management, modeling, algorithms, presenting results, and assessing impact.

Our research applications meet a broad range of pressing societal needs, from drug discovery to climate science; agriculture to smart cities; and from the stock market to space travel. Below is a rotating selection of our standout investigators in machine learning.

   ○ Recent News and Highlights
   ○ Related Strength: Artificial Intelligence
   ○ Related Strength: Ethical Technology

 

Selected Publications

Damodaran, A., Di Troia, F., Visaggio, C. A., Austin, T. H., & Stamp, M. (2017). A comparison of static, dynamic, and hybrid analysis for malware detection. Journal of Computer Virology and Hacking Techniques, 13.

Eirinaki, M., et al (2022). Real-time recommendations for energy-efficient appliance usage in households. Frontiers in Big Data, 5.

Huang, Y., Srivastava, R., Ngo, C., Gao, J., Wu, J., & Chiao, S. (2023). Data-driven soil analysis and evaluation for smart farming using machine learning approaches. Agriculture, 13(9). 

Liu, G., et al. (2022). Novel Robust Indoor Device-Free Moving-Object Localization and Tracking Using Machine Learning With Kalman Filter and Smoother. IEEE Systems Journal, 16(4).

Patil, P., Wu, C. S., Potika, K., & Orang, M. (2020). Stock market prediction using ensemble of graph theory, machine learning and deep learning models. Proceedings of the 3rd International Conference on Software Engineering and Information Management.

Wu, C. S., Bhandary, U. (2020). Detection of Hate Speech in Videos Using Machine Learning, 2020 International Conference on Computational Science and Computational Intelligence.

Award Highlights

Guzun, “Scalable and Adaptable Sparsity-driven Methods for more Efficient AI Systems” — NSF CAREER, 2023

Park, Di Troia, “REU Site: Undergraduate Research Experience for Women in Machine Learning-based Cybersecurity” — NSF, 2023

Ramasubramanian, Lee, S.J., Lee, W., "Thrombosis in Microgravity" — NASA, 2020

Innovations

Neural Network In-Memory Computing [pdf]
A solution to slow training speeds and other issues associated with synapses in neural network in-memory computing.

Affiliates

Agricultural Research Institute (ARI)

CSU STEM-​NET

Featured Faculty

ditroiaFabio Di Troia
Assistant Professor of Computer Science
Machine Learning, Cybersecurity, Malware Detection, Network Analysis, Biometrics, Sentiment Analysis, Spam Detection
ORCID: 0000-0003-2355-7146

eirinakiMagdalini Eirinaki
Professor of Computer Engineering
Recommender Systems, Machine Learning, Graph Mining, Deep Learning
ORCID: 0000-0002-4711-3366

guzunGheorghi Guzun
Assistant Professor of Computer Engineering
Big Data, Machine Learning, Energy Efficient AI, Compression, Quantization, Scalable Algorithms and Data Structures
ORCID: 0000-0001-9162-7981

leeWendy Lee
Assistant Professor of Computer Science
Sequencing Artifacts Detection, Machine Learning, Microbiome, Bisphenol-A, RNA-Seq
ORCID: 0000-0002-8421-0536

liuGuannan Liu
Assistant Professor of Applied Data Science
Machine-Learning Techniques, Artificial-Intelligence Systems, Big-Data Analytics, Wireless Signal Processing
ORCID: 0000-0001-5548-9040

potikaKaterina Potika
Associate Professor of Computer Science
Algorithmic Design, Network Analysis, Machine Learning, Deep Learning, Intrusion Detection and Malware, Blockchain, Distributed Algorithms, Game Theory, Graphing
ORCID: 0000-0003-0332-1347

wuMike Wu
Associate Professor of Computer Science
Big Data, Machine Learning, Software Engineering
ORCID: 0000-0001-7382-499X

Potential collaborators and members of the media may contact us at officeofresearch@sjsu.edu.