Jaturong Kongmanee

I am a Ph.D. candidate at the University of Toronto , fortunately supervised by Professor Mark H. Chignell. I work on making Interactive Machine Learning usable and reliable for applications in Cybersecurity (textual data) and Healthcare (speech data).

Prior to joining UofT, I started my Ph.D. at the Computer Science and Engineering Department at Michigan State University, fortunately working with Professor Kalyanmoy Deb and Professor Vishnu Naresh Boddeti on Deep Learning, Multi-Objective Optimization, Evolutionary Algorithm (EA).

I obtained my master's degree in computer science from the Red Raiders land, Texas Tech University. I was fortunately supervised by Professor Rattikorn Hewett to work on Blockchain and Model Checking.

Email / Google Scholar / Github

Research

My research focuses on developing robust and reliable interactive machine learning (iML) that enhances human-ML/AI team compatibility and data labeling processes for applications in cybersecurity and healthcare. The goal is to advance our understanding of how and when human operators and ML systems can work together effectively and efficiently.

Selected Publications

	A Simplified and More Efficient Training Procedure for OOD Detection Jaturong Kongmanee, Mark H. Chignell IJCAI 2024 : International Joint Conference on Artificial Intelligence Jeju Island, South Korea, August 3-9, 2024 [ paper (coming soon) ]
	Unsupervised Early Sampling Helps Focus Human Expertise in Active Learning of Anomalies Jaturong Kongmanee, Khilan Jerath, Abhay Raman, Mark H. Chignell IJCAI 2024 : International Joint Conference on Artificial Intelligence Jeju Island, South Korea, August 3-9, 2024 [ paper (coming soon) ]
	A Human-AI Interaction Dashboard for Detecting Potentially Malicious Emails Jaturong Kongmanee, Mu-Huan Chung, April Luna, Khilan Jerath, Abhay Raman, Mark H. Chignell IEEE ICHMS 2024 : IEEE International Conference on Human-Machine Systems Toronto, Canada, May 15-17, 2024 [ paper (coming soon) ]
	Dual-Stage OOD Detection Learning with an Unsupervised Start Jaturong Kongmanee, Thanyathorn (Smile) Thanapattheerakul, Mark H. Chignell IAIT 2023 : International Conference on Advances in Information Technology Bangkok, Thailand, December 6-9, 2023 [ paper ]
	Unsupervised Learning of Distributional Properties can Supplement Human Labeling and Increase Active Learning Efficiency in Anomaly Detection Jaturong Kongmanee, Mark H. Chignell , Khilan Jerath, Abhay Raman ICML 2023 workshop on AI & HCI: International Conference on Machine Learning Honolulu, Hawaii, United States, July 23-29, 2023 [ paper ] [ ICML_website ]
	Multi-objective Coevolution and Decision-making for Cooperative and Competitive Environments Anirudh Suresh, Jaturong Kongmanee, Kalyanmoy Deb, Vishnu Naresh Boddeti CEC 2021: IEEE Congress on Evolutionary Computation Kraków, Poland (VIRTUAL), June 28- July 1, 2021 [ paper ]
	Securing smart contracts in blockchain Jaturong Kongmanee, Phongphun Kijsanayothin, Rattikorn Hewett ASE 2019: IEEE/ACM International Conference on Automated Software Engineering San Diego, California, United States, November 10-15, 2019 [ paper ]

Certificates

	The ML research community focused on reducing risks from advanced AI systems. Safety Engineering: Risk Decomposition, A Systems View of Safety, Black Swans Robustness: Adversaries, Long Tails Monitoring: Anomalies, Interpretable Uncertainty, Transparency, Trojans, Emergent Behavior Control: Honesty, Value Learning, Machine Ethics, Intrasystem Goals Systemic Safety: ML for Improved Epistemics, ML for Improved Cyberdefense, Cooperative AI Additional X-Risk Discussion: Future Scenarios, Selection Pressures, Avoiding Capabilities Externalities Certification Date: Aug 22, 2023 Host: The Center for AI Safety (CAIS — pronounced 'case')
	Mathematics for Machine Learning Specialization Represent data in a linear algebra context and manipulate these objects mathematically Summarise properties of data sets and map them onto lower dimensional spaces with PCA Solve optimization problems ans use this skill to train ML models for describing data such as neural networks [ Verify this certificate at ] Certification Date: Mar 11, 2023 Host: Imperial College London
	Mathematics for Machine Learning: PCA Derive PCA from a projection perspective and Dimensionality Reduction Understand how orthogonal projections work Implement mathematical concepts using real-world data [ Verify this certificate at ] Certification Date: Mar 11, 2023 (96.5% Grade Achieved) Host: Imperial College London
	Mathematics for Machine Learning: Multivariate Calculus Linear Regression Vector and Multivariate Calculus Gradient Descent [ Verify this certificate at ] Certification Date: Feb 10, 2023 (98.5% Grade Achieved) Host: Imperial College London
	Mathematics for Machine Learning: Linear Algebra Linear Algebra, Basis (Linear Algebra) Transformation Matrix Eigenvalues And Eigenvectors [ Verify this certificate at ] Certification Date: Feb 5, 2023 (98% Grade Achieved) Host: Imperial College London
	Certified CyberAmbassador A professional skills training in **Communication, Teamwork and Leadership** developed with support from the National Science Foundation (NSF). [ website ] Certification Date: July, 19, 2022 Host: Michigan State University

Blog

Sept 16, 2023: Empirical Risk(or error) Minimization (ERM): what is it and its connection to Probably Approximately Correct (PAC) learning framework

Talks

Fundamental Challenges in Applying ML to Data Exfiltration Detection

CMKL University Thailand, Bangkok, Thailand.

Date: Sept 8, 2023

Last updated: Feb 19, 2024 Website Layout from Jon Barron