Ly Ly Trieu

Ph.D. student, NMSU, USA

  • Email: lytrieu@nmsu.edu
  • Office: Room 133, Science Hall, NMSU, USA

Find my CV here: https://www.cs.nmsu.edu/~ltrieu/cv.pdf

Education

I am currently a PhD candidate in the Department of Computer Science at New Mexico State University and successfully defended on October 17th, 2025. I earned my bachelor (excellent degree) from Danang University of Science and Technology, Vietnam, where my major was Computer Science. During my undergraduate studies, I visited Kogakuin University in Japan for a week, and was also an exchange student at Kanazawa University in Japan for 5 months. The study was funded by Japan Student Services Organization scholarship.

Work Experience

Research Assistant, Computer Science Department, New Mexico State University, USA.

January 2019 - Present

  • Primary Research Topic: Explainable AI, Logic Programming.
  • Secondary Research Topic: Machine Learning and Data Mining Applications in Agriculture.

Instructor, Computer Science Department, New Mexico State University, USA.

  • Summer 2025: Python Programming I (grad/undergrad) (primary instructor).
  • Summer 2023: Python Programming I (grad/undergrad) (primary instructor), Java Programming (grad/undergrad) (secondary instructor).
  • Spring 2023: Python Programming I (grad/undergrad) (primary instructor).
  • Summer 2022: Python Programming I (grad/undergrad) (primary instructor), Java Programming (grad/undergrad) (secondary instructor).

Guest Lecturer, Computer Science Department, New Mexico State University, USA.

  • Spring 2025: Artificial Intelligence and Arid Land Agriculture (CS 579) (grad level).

Research Engineer, School of Information System, Singapore Management University, Singapore.

April 2018 - December 2018

My research focuses on advanced data mining techniques for recommendation systems.

Publications

Articles in Refereed Conferences

[1] Ly Ly Trieu (2025). "Research summary: Explainable artificial intelligence in answer set programming and machine learning." To appear in the Proceeding of the 21st Doctoral Consortium (DC) on Logic Programming, 2025.

[2] Ly Ly Trieu , and Tran Cao Son (2025). "xDNN(ASP): Explanation Generation System for Deep Neural Networks powered by Answer Set Programming." To appear in the Proceeding of the 41st International Conference on Logic Programming (ICLP), 2025.

[3] Mario Alviano, Ly Ly Trieu, Tran Cao Son, and Marcello Balduccini (2023). "Explanations for Answer Set Programming." Electronic Proceedings in Theoretical Computer Science, Volume 385, pp. 27-40.

[4] Mario Alviano, Ly Ly Trieu, Tran Cao Son, and Marcello Balduccini (2023). "Advancements in xASP, an XAI System for Answer Set Programming." In Proceedings of the 38th Italian Conference on Computational Logic, Volume 3428. Best paper award.

[5] Ly Ly Trieu, Tran Cao Son, Marcello Balduccini (2022). "xASP: An Explanation Generation System for Answer Set Programming." In International Conference on Logic Programming and Nonmonotonic Reasoning, Lecture Notes in Computer Science, Volume 13416, Springer, Cham.

[6] Ly Ly Trieu, Tran Cao Son, Marcello Balduccini (2021). "exp(ASPc): Explaining ASP Programs with Choice Atoms and Constraint Rules." Electronic Proceedings in Theoretical Computer Science 345, pp. 155-161.

[7] Ly Ly Trieu, Tran Cao Son, Enrico Pontelli, Marcello Balduccini (2021). "Generating explanations for answer set programming applications." Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III, 11746, International Society for Optics and Photonics, SPIE, pp. 390-403.

[8] Botros N. Hanna, Ly Ly Thi Trieu, Tran Cao Son, Nam T. Dinh (2020). "An Application of ASP in Nuclear Engineering: Explaining the Three Mile Island Nuclear Accident Scenario." Theory and Practice of Logic Programming, Volume 20, pp. 926–941.

[9] Trieu Thi Ly Ly, Le Thi Ha Binh, Bui Thanh Son, Ninh Khanh Duy (2017). "A Solution for English Transliteration to Vietnamese." The 10th National Conference on Fund amental and Applied IT Research (FAIR) conference, Danang, Vietnam, August, 2017, pp. 502-510.

[10] Trieu Thi Ly Ly, Nguyen Van Quy, Ninh Khanh Duy, Huynh Huu Hung, Dang Minh Thang (2017). "Representing Context in Abbreviation Expansion using Machine Learning Approach." The 10th National Conference on Fundamental and Applied IT Research (FAIR) conference, Danang, Vietnam, August, 2017, pp. 816-822.

Journal Articles

[1] Ly Ly Trieu, Derek W. Bailey, Huiping Cao, Tran Cao Son, Colin T. Tobin, and Cory Oltjen (2025). "Detecting Frequent Sequential Patterns between Weather and Cattle Behavior using Data Mining." Frontiers in Animal Science, Volume 6, 1640550.

[2] Ly Ly Trieu, Derek W. Bailey, Huiping Cao, Tran Cao Son, Justin Macor, Mark G. Trotter, Lauren O'Connor, and Colin T. Tobin (2025). "Potential of Accelerometers to Remotely Early Detect Bovine Ephemeral Fever in Cattle Using Pattern Mining." Translational Animal Science, Volume 9, txaf008.

[3] Barto, Amadeus O., Derek W. Bailey, Ly Ly Trieu, Pippa Pryor, Kieren D. McCosker, and Santigo Utsumi (2025). "Monitoring Behavior and Welfare of Cattle in Response to Summer Weather in an Arizona Rangeland Pasture Using a Commercial Rumen Bolus." Animals 15, no. 10: 1448.

[4] Mario Alviano, Ly Ly Trieu, Tran Cao Son, Marcello Balduccini (2024). "The XAI system for answer set programming xASP2." Journal of Logic and Computation, Volume 34, Issue 8, pp. 1500–1525.

[5] Colin Tobin, Derek Bailey, Caroline Wade, Ly Ly Trieu, Kelsey Nelson, Cory Oltjen, Huiping Cao, Tran Cao Son, Victor Flores, Briza Castro, Jennifer Hernandez Gifford, Mark Trotter, David Kramar (2024). "Evaluation of experimental error in accelerometer monitoring: Variation among individual animals versus variation among devices." Smart Agricultural Technology, Volume 7: 100432.

[6] Ly Ly Trieu, Derek W. Bailey, Huiping Cao, Tran Cao Son, David R. Scobie, Mark G. Trotter, David E. Hume, B. Lee Sutherland, and Colin T. Tobin (2022). "Potential of accelerometers and GPS tracking to remotely detect perennial ryegrass staggers in sheep." Smart Agricultural Technology, Volume 2, 100040.

Oral & Poster Presentations

[1] The 21st Doctoral Consortium on Logic Programming (Remote Presentation): "Research summary: Explainable artificial intelligence in answer set programming and machine learning", 2025.

[2] Graduate Research and Arts Symposium at New Mexico State University (Poster Presentation): "Explanations for Answer Set Programming", 2023.

[3] American Society of Animal Science Annual Meeting (Oral Presentation): "Potential of Accelerometers to Remotely Detect Bovine Ephemeral Fever in Heifers using Pattern Recognition", 2023.

[4] The 28th Joint University of Texas at El Paso and New Mexico State University on Mathematics, Computer Science, and Computational Sciences (Oral Presentation): "Explanation Generation Systems for Answer Set Programming", 2022.

[5] Society for Range Management Annual Meeting (Poster Presentation): "Detection of animal illness using machine learning", 2022.

[6] The 37th International Conference on Logic Programming (ICLP) (Remote Presentation): "exp(ASPc) : Explaining ASP Programs with Choice Atoms and Constraint Rules", 2021.

[7] SPIE Defense and Commercial Sensing (Remote Presentation): "Generating explanations for answer set programming applications", 2021.

[8] Kanazawa University (Poster Presentation): "Survey of General Object Recognition", 2018.