Research
Dr. Tešić's research project span topics in machine learning and data science for large unstructured imagery, social, health, and sensor data sources. More details on the current projects can be found on DataLab12 page.
Courses Recently Taught
Image Processing and COmputer Vision (Ph.D.): Spring 2024
Introduction to Machine Learning: Spring 2024 Fall 2023
Introduction to Recommender Systems : Fall 2023
Data-Driven Computational Methods (Ph.D): Spring 2023
Object Oriented Design and Programming: Spring 2023
Machine Learning and Applications (M.Sc.): Fall 2021
Research Courses Offered Every Semester
Ph.D. Dissertation in Computer Science
Ph.D. Research in Computer Science
Master Thesis A and B
Master Independent Study
Service
CS3354 Course Coordinator
NSF REU (2018-2021) advisor
Mathworks (2019, 2020) mentor
SURE (2020-2021) research advisor
Short Bio
Jelena Tešić is an Assistant Professor, Department of Computer Science, Texas State Unviersity, San Marcos, Texas, USA. From 2009 to 2017 Dr. Tešić was a senior research scientist @ Mayachitra Inc. From 2014 to 2017, she led research project on bio-inspired methods and deep learning for object and activity recognition in aerial imagery. From 2009 to 2014 Dr. Tešićled the research efforts on scaling multimedia indexing, search and retrieval for large image and video repositories within DARPA VIRAT and IARPA FINDER projects. From 2004 to 2009, Dr. Tešić was a Research Staff Member at IBM T. J. Watson Research Center, Yorktown, NY. There, she worked on developing systems for multimedia data management and its various applications; addressed selected research topics in the areas of scalable content information modeling, collaborative tagging of multimedia, and mining of content networks; and contributed to the to the top performance of the IBM team in NIST benchmark TRECVID. Dr. Tešić received her Ph.D. (2004), M.Sc. (1999) in Electrical and Computer Engineering from University of California Santa Barbara, CA, USA, and Dipl. Ing. (1998) in Electrical Engineering from University of Belgrade, Serbia. Dr. Tešić served as an Area Chair for ACM Multimedia 2019, 2020, 2021, IEEE ICIP 2019, and IEEE ICME 2018 and 2019. Prior, she has served as Guest Editor in a Special Issue on Collaborative Tagging of Multimedia, in IEEE Multimedia Magazine, July-September 2008 issue, and as a reviewer for numerous IEEE and ACM Journals. She has authored over 30 scientific papers, and currently holds 6 U.S. patents: 9,710,760; 8,738,695; 8,032,539; 7,958,068; 7,818,329; and 7,707,162.PDFs of papers under review in journals or submitted to conferences
Network Science: Scaling Frustration Index and Corresponding Balanced State Discovery for Real Signed Graphs, ABCD: Algorithm for Balanced Component Discovery in Signed Networks, and Multimodal Mining of Twitter Networks for Improved Label Propagation. Computer Vision: Stratified Graph Indexing for Efficient Search in Deep Descriptor Databases, Domain Adaptation with Contrastive Learning for Object Detection in Satellite Imagery, and EVIREC: Efficient Visual Indexing and Retrieval for Edge Crowd-sensing Noisy Tabular Data: Ranking Resilience Attributes for Texas Public School Districts and Data Driven Teacher Attrition Modeling.