{"id":26,"date":"2025-09-21T05:33:36","date_gmt":"2025-09-21T05:33:36","guid":{"rendered":"https:\/\/www.ieeesmc.org\/ichms-2026\/?page_id=26"},"modified":"2026-06-19T16:43:42","modified_gmt":"2026-06-19T16:43:42","slug":"program-2","status":"publish","type":"page","link":"https:\/\/www.ieeesmc.org\/ichms-2026\/program-2\/","title":{"rendered":"Program"},"content":{"rendered":"\t\t
\n\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

Program-At-A-Glance<\/h2>\n\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n
\n
\n Day 1 \u2014 Wednesday, 1 July 2026<\/span>\n NTU ARC<\/span>\n <\/div>\n
\n \n \n \n \n \n \n \n \n \n \n \n
Time<\/th>\n TR-26<\/th>\n TR-27<\/th>\n TR-28<\/th>\n TR-29<\/th>\n TR-24<\/th>\n <\/tr>\n <\/thead>\n
8:45 \u2013 9:00<\/td>\n \n
Opening Ceremony<\/div>\n
ARC Lecture Theatre · All delegates<\/div>\n <\/td>\n <\/tr>\n
9:00 \u2013 10:00<\/td>\n \n
10:00 \u2013 10:15<\/td>\n Tea break<\/td>\n <\/tr>\n
10:15 \u2013 13:15<\/td>\n \n
ISACT Summer School<\/div>\n
Organiser-led sessions<\/div>\n <\/td>\n
\n
AI Thought Leaders Panel<\/div>\n
Open to all · Free entry<\/div>\n <\/td>\n
\n
Workshop: WAISERER<\/div>\n
AM session<\/div>\n <\/td>\n
\n
Workshop: Biodynamics & HMI<\/div>\n
Shared control, BCI & workload<\/div>\n <\/td>\n
\n
IEEE Young Professionals<\/div>\n
11:15 \u2013 12:15<\/div>\n <\/td>\n <\/tr>\n
13:15 \u2013 14:00<\/td>\n Lunch break<\/td>\n <\/tr>\n
14:00 \u2013 17:00<\/td>\n \n
ISACT Summer School<\/div>\n
Continued<\/div>\n <\/td>\n
\n
AI Thought Leaders Panel<\/div>\n
Continued<\/div>\n <\/td>\n
\n
Workshop: WAISERER<\/div>\n
PM session<\/div>\n <\/td>\n
\n
Workshop: Adaptive Microlearning<\/div>\n
Goal-driven learning systems<\/div>\n <\/td>\n
\n
Workshop: Mixed Reality Digital Twin<\/div>\n
Collaborative simulation<\/div>\n <\/td>\n <\/tr>\n
17:00 \u2013 17:15<\/td>\n Tea break · All delegates<\/td>\n <\/tr>\n <\/tbody>\n <\/table>\n <\/div>\n <\/div>\n<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n
\n
Day 2 \u2014 Thursday, 2 July 2026<\/span>\nNTU ARC<\/span><\/div>\n
\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time<\/th>\nTR-27<\/th>\nTR-28<\/th>\nTR-29<\/th>\n<\/tr>\n<\/thead>\n
9:00 \u2013 10:00<\/td>\nKeynote 2 \u2014 Prof. Toshio Fukuda<\/a><\/span>\nARC Lecture Theatre \u00b7 All delegates<\/span><\/td>\n<\/tr>\n
10:00 \u2013 10:15<\/td>\nTea break<\/td>\n<\/tr>\n
10:15 \u2013 13:15<\/td>\n\n
CHAIS Summer School<\/div>\n
Collaborative Human-AI Symbiosis<\/div><\/td>\n
Session A: Aviation, Vehicle Human Factors and Simplified Vehicle Operation<\/a><\/td>\nSession B: Hybrid Intelligence, Airspace Management and Autonomous Mobility<\/a><\/td>\n<\/tr>\n
13:15 \u2013 14:00<\/td>\nLunch break<\/td>\n<\/tr>\n
14:00 \u2013 16:15<\/td>\n\n
CHAIS Summer School<\/div>\n
Continued<\/div><\/td>\n
Session C: Generative AI, Human-Robot Interaction, Digital Twins and Robot Control<\/a><\/td>\nSession D: Linguistic Reasoning, AI Education and Responsible AI<\/a><\/td>\n<\/tr>\n
16:15 \u2013 16:30<\/td>\nTea break \u00b7 All delegates<\/td>\n<\/tr>\n
16:30 \u2013 17:30<\/td>\nIEEE Distinguished Lecture \u2014 Prof. Henry Leung<\/span>\nARC Lecture Theatre \u00b7 All delegates<\/span><\/td>\n<\/tr>\n
17:30 \u2013 18:30<\/td>\nBus to YWCA at Fort Canning<\/span><\/td>\n<\/tr>\n
18:30 \u2013 21:30<\/td>\n \n Gala Dinner<\/span> · YWCA Fort Canning<\/span>\n <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n
\n
\n Day 3 \u2014 Friday, 3 July 2026<\/span>\n NTU ARC<\/span>\n <\/div>\n
\n \n \n \n \n \n \n \n \n \n \n
Time<\/th>\n TR-26<\/th>\n TR-27<\/th>\n TR-28<\/th>\n TR-29<\/th>\n <\/tr>\n <\/thead>\n
9:00 \u2013 10:00<\/td>\n \n Keynote 3 — Prof. Chen Chun-Hsien<\/a><\/span>\n ARC Lecture Theatre · All delegates<\/span>\n <\/td>\n <\/tr>\n
10:00 \u2013 10:15<\/td>\n Tea break<\/td>\n <\/tr>\n
10:15 \u2013 13:15<\/td>\n \n
ISACT Summer School<\/div>\n
Organiser-led sessions<\/div>\n <\/td>\n
\n Session E: Physiological Sensing, Workload and BCI<\/a>\n Session F: Human-Robot Interaction and Human-AI Collaboration<\/a>\n <\/td>\n \n Session G: Autonomous Systems, Control and Robotics<\/a>\n <\/td>\n \n Session H: Human Factors, Safety, Healthcare and Speech<\/a>\n <\/td>\n <\/tr>\n
13:15 \u2013 14:00<\/td>\n Lunch break<\/td>\n <\/tr>\n
14:00 \u2013 16:10<\/td>\n \n
ISACT Summer School<\/div>\n
Continued<\/div>\n <\/td>\n
\n Virtual Presentations: Special Sessions and Contributed Papers<\/a>\n <\/td>\n \n Virtual Contributed Papers: General Human-Machine Systems<\/a>\n <\/td>\n \n
Closing Ceremony<\/div>\n
Awards, Farewell & Networking<\/div>\n <\/td>\n <\/tr>\n
16:15 \u2013 16:30<\/td>\n Tea break · Farewell<\/td>\n <\/tr>\n <\/tbody>\n <\/table>\n <\/div>\n <\/div>\n<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

Sessions<\/h2>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\nDay 2 \u00b7 TR-28 \u00b7 AM \u00b7 Session A: Aviation, Vehicle Human Factors and Simplified Vehicle Operation<\/summary>\n
\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Thursday, 2 July 2026 \u00b7 10:15 \u2013 13:15 \u00b7 TR-28<\/td>\n<\/tr>\n
Time<\/th>\nPaper #<\/th>\nPaper Title<\/th>\nType<\/th>\n<\/tr>\n
Special Session: Aviation & Vehicle Human Factors (61kwa)<\/td>\n<\/tr>\n
10:15 \u2013 10:25<\/td>\n116<\/td>\nAdaptive Automation Levels in Air Traffic Control: Balancing Human Workload, Situation Awareness, and Performance<\/td>\nIn-person<\/td>\n<\/tr>\n
10:25 \u2013 10:35<\/td>\n119<\/td>\nAdaptive HMI Design Strategies for Mitigating Pilot Spatial Attention-Loss Driven by Scanning Series Monitoring<\/td>\nIn-person<\/td>\n<\/tr>\n
10:35 \u2013 10:45<\/td>\n52<\/td>\nMethodological Challenges in Human Factors Research for Air Traffic Management<\/td>\nIn-person<\/td>\n<\/tr>\n
10:45 \u2013 10:55<\/td>\n84<\/td>\nRecognising Emotions in Air-Ground Communications with Deep Learning<\/td>\nIn-person<\/td>\n<\/tr>\n
10:55 \u2013 11:05<\/td>\n104<\/td>\nThe Transparency of Insights into Cockpit Evolution for Future Single-Pilot Operation: Evidence from Eye Tracker Patterns<\/td>\nIn-person<\/td>\n<\/tr>\n
11:05 \u2013 11:15<\/td>\n114<\/td>\nTemporal and Spatial Constraints on Peripheral Signal Accessibility During Continuous Task Engagement<\/td>\nIn-person<\/td>\n<\/tr>\n
11:15 \u2013 11:25<\/td>\n115<\/td>\nFrom Misunderstanding to Alignment: LLM-Supported Training to Enhance Controller-Pilot Collaboration<\/td>\nIn-person<\/td>\n<\/tr>\n
11:25 \u2013 11:35<\/td>\n153<\/td>\nEvaluating the Impact of a Multi-Sector Planner Configuration on Air Traffic Controller Workload and Support Tool Requirements<\/td>\nIn-person<\/td>\n<\/tr>\n
Special Session: Simplified Vehicle Operation (3e38s)<\/td>\n<\/tr>\n
11:35 \u2013 11:45<\/td>\n93<\/td>\nA Quantum-Like Many-Body Wave Function-Based Modeling Approach for Dynamic Human-Machine Function Allocation<\/td>\nIn-person<\/td>\n<\/tr>\n
11:45 \u2013 11:55<\/td>\n97<\/td>\nImplementing Gaze Entropy to Evaluate the Design of an eVTOL with SVO Concept<\/td>\nIn-person<\/td>\n<\/tr>\n
11:55 \u2013 12:05<\/td>\n86<\/td>\nAn MTE-Based Handling Quality Assessment Framework for SVO Fixed-Wing VTOL Aircraft<\/td>\nIn-person<\/td>\n<\/tr>\n
12:05 \u2013 12:15<\/td>\n125<\/td>\nA Fast Computational Approach for Wing Lift Prediction in Tilt-Propeller Slipstream Toward Enhanced SVO Envelope Protection<\/td>\nIn-person<\/td>\n<\/tr>\n
Contributed Papers: Aviation and Vehicle Human Factors<\/td>\n<\/tr>\n
12:15 \u2013 12:25<\/td>\n45<\/td>\nRunA-Fit Adaptive Feature Refinement and Alignment for CLIP-Based Few-Shot Airfield Runway Anomaly Classification<\/td>\nIn-person<\/td>\n<\/tr>\n
12:25 \u2013 12:35<\/td>\n36<\/td>\nEvaluating Psychophysiological Variables for Real-Time Activity Recognition in Manned-Unmanned Teaming Missions<\/td>\nIn-person<\/td>\n<\/tr>\n
12:35 \u2013 12:45<\/td>\n82<\/td>\nLinking Vehicle Dynamics to User Experience in L2 Automated Urban Turning: A Driving Simulator Study<\/td>\nIn-person<\/td>\n<\/tr>\n
12:45 \u2013 12:55<\/td>\n71<\/td>\nA Framework on Human-Autonomy Unified Control and Strategies for EVTOL<\/td>\nIn-person<\/td>\n<\/tr>\n
12:55 \u2013 13:15<\/td>\nQ&A \/ Buffer<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/details><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\nDay 2 \u00b7 TR-29 \u00b7 AM \u00b7 Session B: Hybrid Intelligence, Airspace Management and Autonomous Mobility<\/summary>\n
\n
\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Thursday, 2 July 2026 \u00b7 10:15 \u2013 13:15 \u00b7 TR-29<\/td>\n<\/tr>\n
Time<\/th>\nPaper #<\/th>\nPaper Title<\/th>\nType<\/th>\n<\/tr>\n
Special Session: Hybrid Intelligence for Airspace Management (5wjur)<\/td>\n<\/tr>\n
10:15 \u2013 10:25<\/td>\n23<\/td>\nAI-Enhanced Tactical Congestion Management Framework for Human-in-the-Loop Decision Support<\/td>\nIn-person<\/td>\n<\/tr>\n
10:25 \u2013 10:35<\/td>\n67<\/td>\nA Linguistics-Guided Hybrid Intelligence Framework for Conversational Decision Support Toward Smarter Air Traffic Management<\/td>\nIn-person<\/td>\n<\/tr>\n
10:35 \u2013 10:45<\/td>\n91<\/td>\nBridging the Experience Gap: Multimodal Agent-Driven AI for Knowledge Transfer in Air Traffic Management<\/td>\nIn-person<\/td>\n<\/tr>\n
10:45 \u2013 10:55<\/td>\n121<\/td>\nSystem-Level Performance Analysis of AI-Assisted and Conventional Coordination in Air Traffic Management<\/td>\nIn-person<\/td>\n<\/tr>\n
10:55 \u2013 11:05<\/td>\n123<\/td>\nEvaluation of GenLLM-Based Air Traffic Complexity Assessment<\/td>\nIn-person<\/td>\n<\/tr>\n
11:05 \u2013 11:15<\/td>\n138<\/td>\nRetrieval-Augmented Large Language Models for Evidence-Based Hazard Log Generation in Emerging Aviation Systems<\/td>\nIn-person<\/td>\n<\/tr>\n
11:15 \u2013 11:25<\/td>\n139<\/td>\nHuman-AI Collaboration for UAS Traffic Management: A Review of Decision Support, Trust, and Assurance<\/td>\nIn-person<\/td>\n<\/tr>\n
11:25 \u2013 11:35<\/td>\n140<\/td>\nA Hybrid Learning Control Framework for Safety-Constrained Multi-Agent Aerial Pursuit in Airport Airspace<\/td>\nIn-person<\/td>\n<\/tr>\n
11:35 \u2013 11:45<\/td>\n64<\/td>\nA Physiological Feature-Based Machine Learning Approach for Identification of Multiple Visual Monitoring Tasks<\/td>\nIn-person<\/td>\n<\/tr>\n
Special Session: Human-Machine Cooperative Intelligence and Autonomous Driving (6a4h1)<\/td>\n<\/tr>\n
11:45 \u2013 11:55<\/td>\n79<\/td>\nSafe Driving for Human-Machine Shared Control: A Prediction-Informed Risk-Aware SMPC<\/td>\nIn-person<\/td>\n<\/tr>\n
11:55 \u2013 12:05<\/td>\n126<\/td>\nLIT-Bench: A Multi-Level Evaluation Benchmark for Vision-Language Models in Intelligent Transportation Systems<\/td>\nIn-person<\/td>\n<\/tr>\n
12:05 \u2013 12:15<\/td>\n151<\/td>\nVision-Conditioned Structured Trajectory Planning via Flow Matching<\/td>\nIn-person<\/td>\n<\/tr>\n
Contributed Papers: Autonomous Systems and Multi-Agent Control<\/td>\n<\/tr>\n
12:15 \u2013 12:25<\/td>\n168<\/td>\nCity-Wide Low-Altitude Urban Air Mobility: A Scalable Global Path Planning Approach Via Risk-Aware Multi-Scale Cell Decomposition<\/td>\nIn-person<\/td>\n<\/tr>\n
12:25 \u2013 12:35<\/td>\n142<\/td>\nBeyond Transportation: Autonomous Vehicles As a Human-City Interface for Future Mobility (presented by Keqi)<\/td>\nIn-person<\/td>\n<\/tr>\n
12:35 \u2013 12:45<\/td>\n48<\/td>\nDistributed Swarm Deployment in Fourier Coordinates Via Riesz Energy Shaping<\/td>\nIn-person<\/td>\n<\/tr>\n
12:45 \u2013 12:55<\/td>\n49<\/td>\nCBF-QP Based Collision-Constrained Shared Control for Multi Agent Robot Swarms<\/td>\nIn-person<\/td>\n<\/tr>\n
12:55 \u2013 13:05<\/td>\n25<\/td>\nART: Adaptive Relational Transformer for Pedestrian Trajectory Prediction with Temporal-Aware Relations<\/td>\nIn-person<\/td>\n<\/tr>\n
13:05 \u2013 13:15<\/td>\nQ&A \/ Buffer<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/details><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n
\nDay 2 \u00b7 TR-28 \u00b7 PM \u00b7 Session C: Generative AI, Human-Robot Interaction, Digital Twins and Robot Control<\/summary>\n
\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Thursday, 2 July 2026 \u00b7 14:00 \u2013 16:15 \u00b7 TR-28<\/td>\n<\/tr>\n
Time<\/th>\nPaper #<\/th>\nPaper Title<\/th>\nType<\/th>\n<\/tr>\n
Special Session: Generative AI, Human-Robot Interaction and Digital Twins (5mbyy)<\/td>\n<\/tr>\n
14:00 \u2013 14:10<\/td>\n118<\/td>\nMultimodal Voice Distress Detection for Real-Time Safety Monitoring in Schools<\/td>\nIn-person<\/td>\n<\/tr>\n
14:10 \u2013 14:20<\/td>\n164<\/td>\nSpeech Emotion Recognition with Dual-Stream Channel Attention<\/td>\nIn-person<\/td>\n<\/tr>\n
14:20 \u2013 14:30<\/td>\n170<\/td>\nGeo-NWM: A Theoretical Framework for Geometry-Consistent World Models in 6-DoF Humanoid Navigation<\/td>\nIn-person<\/td>\n<\/tr>\n
14:30 \u2013 14:40<\/td>\n172<\/td>\nToward a Humanoid Conductor: Beat-Pattern Gesture Synthesis and Evaluation on the Unitree<\/td>\nIn-person<\/td>\n<\/tr>\n
14:40 \u2013 14:50<\/td>\n120<\/td>\nAutomated Diagnostic Evaluation of Vision-Guided Waste Sorting Via LLMs<\/td>\nIn-person<\/td>\n<\/tr>\n
Special Session: Privacy-Preserving and Trustworthy Human-Agent Collaboration (ndkq7)<\/td>\n<\/tr>\n
14:50 \u2013 15:00<\/td>\n152<\/td>\nContactless Palmprint Identification with Programmable Multispectral Imaging and Foundation Models on the Edge<\/td>\nIn-person<\/td>\n<\/tr>\n
15:00 \u2013 15:10<\/td>\n145<\/td>\nEfficient and Interpretable Tabular Learning Via Visual Transformation<\/td>\nIn-person<\/td>\n<\/tr>\n
15:10 \u2013 15:20<\/td>\n122<\/td>\nGovernance-Aligned Chatbot Operationalizing the Fourth Edition of the Occupational Therapy Practice Framework (OTPF-4)<\/td>\nIn-person<\/td>\n<\/tr>\n
Contributed Papers: Human-Robot Interaction and Control<\/td>\n<\/tr>\n
15:20 \u2013 15:30<\/td>\n32<\/td>\nAdaptive Energy-Based Robot Control for Physical Human-Robot Interaction: A Less Conservative Approach<\/td>\nIn-person<\/td>\n<\/tr>\n
15:30 \u2013 15:40<\/td>\n39<\/td>\nDelay-Compensated Stiffness Estimation for Robot-Mediated Dyadic Interaction<\/td>\nIn-person<\/td>\n<\/tr>\n
15:40 \u2013 15:50<\/td>\n53<\/td>\nAdaptive Observer-Based Control for Reduced-Sensor Dual-Parallel PMSMs with Stator Resistance Variation<\/td>\nIn-person<\/td>\n<\/tr>\n
15:50 \u2013 16:15<\/td>\nQ&A \/ Buffer<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/details><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n
\nDay 2 \u00b7 TR-29 \u00b7 PM \u00b7 Session D: Linguistic Reasoning, AI Education and Responsible AI<\/summary>\n
\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Thursday, 2 July 2026 \u00b7 14:00 \u2013 16:15 \u00b7 TR-29<\/td>\n<\/tr>\n
Time<\/th>\nPaper #<\/th>\nPaper Title<\/th>\nType<\/th>\n<\/tr>\n
Special Session: Human-AI Systems for Linguistic Reasoning and AI Education (vv157)<\/td>\n<\/tr>\n
14:00 \u2013 14:10<\/td>\n69<\/td>\nAI-Supported Linguistic Reasoning: A Human-AI Decision Support Framework for Multilingual Meaning and Ambiguity<\/td>\nIn-person<\/td>\n<\/tr>\n
14:10 \u2013 14:20<\/td>\n107<\/td>\nJoyful Learning with Digital Escape Rooms: A Human-Centered Framework for Teacher Education and AI-Enabled Extension<\/td>\nIn-person<\/td>\n<\/tr>\n
14:20 \u2013 14:30<\/td>\n108<\/td>\nAI Powered Interactive Role Play Simulator for Authentic Spoken Language Practice<\/td>\nIn-person<\/td>\n<\/tr>\n
14:30 \u2013 14:40<\/td>\n109<\/td>\nDiscriminant Insights: Applying Linear Discriminant Analysis to Tamil Vowel Usage for Social Awareness and Emotional Lyrics in Education<\/td>\nIn-person<\/td>\n<\/tr>\n
14:40 \u2013 14:50<\/td>\n110<\/td>\nStatistical Modeling of Tamil Vowel Usage for Human-AI Collaborative Language Education: A Comparative Study of LDA and Regularized Logistic Regression<\/td>\nIn-person<\/td>\n<\/tr>\n
14:50 \u2013 15:00<\/td>\n111<\/td>\nQuantitative Analysis of Vallinam and Idaiyinam Patterns in Sangam-Era Tamil Texts for Interpretable Language Analytics<\/td>\nIn-person<\/td>\n<\/tr>\n
15:00 \u2013 15:10<\/td>\n68<\/td>\nAction-Conditioned Prompting for Air Traffic Control: A Smart Prompt Producer That Converts Controller HMI Actions into Verified, Explainable LLM Outputs<\/td>\nIn-person<\/td>\n<\/tr>\n
Contributed Papers: Trust, Responsible AI and Community Systems<\/td>\n<\/tr>\n
15:10 \u2013 15:20<\/td>\n41<\/td>\nFSC-CD: A Feature-Structure Coupled Approach for Community Deception in Networks<\/td>\nIn-person<\/td>\n<\/tr>\n
15:20 \u2013 15:30<\/td>\n77<\/td>\nClosing the Context Gap: Community Rules as a Correction Layer for Algorithmic Moderation<\/td>\nIn-person<\/td>\n<\/tr>\n
15:30 \u2013 15:40<\/td>\n112<\/td>\nTowards Responsible AI in Safety-Critical Human-Machine Systems: A Literature-Based Governance Framework (Elias Panner)<\/td>\nIn-person<\/td>\n<\/tr>\n
15:40 \u2013 15:50<\/td>\n129<\/td>\nIntegrating Responsible AI into the Model Development Life Cycle: A Practical Framework for Predictive Maintenance<\/td>\nIn-person<\/td>\n<\/tr>\n
15:50 \u2013 16:00<\/td>\n137<\/td>\nA Task-Based Benchmark for Model Context Protocol-Driven Geospatial Dataset Discovery: LLM Agents vs Human Search<\/td>\nIn-person<\/td>\n<\/tr>\n
16:00 \u2013 16:15<\/td>\nQ&A \/ Buffer<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/details><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
<\/span> <\/span>
\nDay 3 \u00b7 TR-27 \u00b7 AM \u00b7 Sessions E & F: Physiological Sensing, Workload, BCI, HRI and Human-AI Collaboration<\/summary>\n
\n
\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Friday, 3 July 2026 \u00b7 10:15 \u2013 13:15 \u00b7 TR-27<\/td>\n<\/tr>\n
Time<\/th>\nPaper #<\/th>\nPaper Title<\/th>\nType<\/th>\n<\/tr>\n
Session E: Physiological Sensing, Workload and BCI<\/td>\n<\/tr>\n
10:15 \u2013 10:25<\/td>\n21<\/td>\nQuantifying Biological Sex Leakage in Electroencephalography-Based Mental Workload Measurement and Its Impact on Model Performance<\/td>\nIn-person<\/td>\n<\/tr>\n
10:25 \u2013 10:35<\/td>\n61<\/td>\nContinuous Neurophysiological Modeling of Flow Dynamics across Machine-Mediated Task Contexts<\/td>\nIn-person<\/td>\n<\/tr>\n
10:35 \u2013 10:45<\/td>\n62<\/td>\nA Multimodal Continuous Emotional Workload Index for Quantifying Stress-Recovery Dynamics<\/td>\nIn-person<\/td>\n<\/tr>\n
10:45 \u2013 10:55<\/td>\n85<\/td>\nMSTformer: A Multi-Scale Spatial-Temporal Transformer for Interpretable Mental Workload Monitoring in Simplified Vehicle Operations<\/td>\nIn-person<\/td>\n<\/tr>\n
10:55 \u2013 11:05<\/td>\n47<\/td>\nConsumer Trait Prediction from EEG Using a Novel SpectralTraitNet for Neuromarketing Application<\/td>\nIn-person<\/td>\n<\/tr>\n
11:05 \u2013 11:15<\/td>\n57<\/td>\nA TCN-Based Framework for Physiological EOG Artifact Removal in Motor Imagery EEG Signals<\/td>\nIn-person<\/td>\n<\/tr>\n
11:15 \u2013 11:25<\/td>\n90<\/td>\nTemporal Uncertainty and Reliability of EMG-Based Machine Learning During Dynamic Contractions<\/td>\nIn-person<\/td>\n<\/tr>\n
11:25 \u2013 11:35<\/td>\n42<\/td>\nHuman Activity Recognition Using 5G Channel State Information with Deep Learning<\/td>\nIn-person<\/td>\n<\/tr>\n
Session F: Human-Robot Interaction and Human-AI Collaboration<\/td>\n<\/tr>\n
11:35 \u2013 11:45<\/td>\n46<\/td>\nPhysical Human-Robot Interaction: A Review from the Guide Robot Perspective<\/td>\nIn-person<\/td>\n<\/tr>\n
11:45 \u2013 11:55<\/td>\n59<\/td>\nSpatial Context-Aware VLM-Assisted Goal Reasoning for Navigation in Guide Service Robots<\/td>\nIn-person<\/td>\n<\/tr>\n
11:55 \u2013 12:05<\/td>\n154<\/td>\nEmbodiment Matters in LLM-Driven Interactive Storytelling: Comparing a Physical Robot and a Virtual Agent<\/td>\nIn-person<\/td>\n<\/tr>\n
12:05 \u2013 12:15<\/td>\n28<\/td>\nHuman-In-The-Loop Rebar Inspection: Integrating Vision Foundation Model with Mixed Reality for Construction Quality Assurance<\/td>\nIn-person<\/td>\n<\/tr>\n
12:15 \u2013 12:25<\/td>\n99<\/td>\nQuantifying Mentor Resilience in the Digital Companion Program: Human Factors Analysis Via Teaching Log Text Mining<\/td>\nIn-person<\/td>\n<\/tr>\n
12:25 \u2013 13:15<\/td>\nQ&A \/ Buffer<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/details><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\nDay 3 \u00b7 TR-28 \u00b7 AM \u00b7 Session G: Autonomous Systems, Control and Robotics<\/summary>\n
\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Friday, 3 July 2026 \u00b7 10:15 \u2013 13:15 \u00b7 TR-28<\/td>\n<\/tr>\n
Time<\/th>\nPaper #<\/th>\nPaper Title<\/th>\nType<\/th>\n<\/tr>\n
Session G: Autonomous Systems, Control and Robotics<\/td>\n<\/tr>\n
10:15 \u2013 10:25<\/td>\n18<\/td>\nA Scenario-Based Warehouse Management Model for Engineering Machinery Maintenance Operations<\/td>\nIn-person<\/td>\n<\/tr>\n
10:25 \u2013 10:35<\/td>\n72<\/td>\nClustering-Based Learning for UAV Tracking and Position Estimation<\/td>\nIn-person<\/td>\n<\/tr>\n
10:35 \u2013 10:45<\/td>\n74<\/td>\nLearning-Based Crash Area Prediction for Hexarotors Using Kolmogorov-Arnold Networks<\/td>\nIn-person<\/td>\n<\/tr>\n
10:45 \u2013 10:55<\/td>\n169<\/td>\nCED-TRL: Curriculum Environment Design for Temporally Extended Reinforcement Learning Tasks<\/td>\nIn-person<\/td>\n<\/tr>\n
10:55 \u2013 11:05<\/td>\n175<\/td>\nSecond-Order Sliding Mode Control with Prescribed Performance Guarantees for Nonlinear Systems<\/td>\nIn-person<\/td>\n<\/tr>\n
11:05 \u2013 11:15<\/td>\n176<\/td>\nEvent-Triggered Adaptive Robust Control for Uncertain Nonlinear Networked Systems under DoS Attacks<\/td>\nIn-person<\/td>\n<\/tr>\n
11:15 \u2013 11:25<\/td>\n177<\/td>\nTemporal Query Persistence for Online Open-Vocabulary 3D Instance Segmentation Via Tracking-By-Detection<\/td>\nIn-person<\/td>\n<\/tr>\n
11:25 \u2013 11:35<\/td>\n179<\/td>\nResearch on the Design and Motion Control of an Underwater Retractable Manipulator<\/td>\nIn-person<\/td>\n<\/tr>\n
11:35 \u2013 11:45<\/td>\n180<\/td>\nPareto-Optimised Sugeno-Adaptive Control for Actuator-Level Trajectory Tracking of Quadrupeds on Complex Terrain<\/td>\nIn-person<\/td>\n<\/tr>\n
11:45 \u2013 11:55<\/td>\n166<\/td>\nFrom Scarcity to Coverage: Generative Behavioral Modeling for Child Identification on Smartphones<\/td>\nIn-person<\/td>\n<\/tr>\n
11:55 \u2013 12:05<\/td>\n10<\/td>\nHuman-AI Collaborative Learning: Human-In-The-Loop Knowledge Infusion via Topological Neural Representations<\/td>\nIn-person<\/td>\n<\/tr>\n
12:05 \u2013 12:15<\/td>\n101<\/td>\nAn AR-HUD and VLM Assisted Interactive Driving: From Lightweight Intent Recognition to Real-Time Visual Grounding<\/td>\nIn-person<\/td>\n<\/tr>\n
12:15 \u2013 13:15<\/td>\nQ&A \/ Buffer<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/details><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\nDay 3 \u00b7 TR-29 \u00b7 AM \u00b7 Session H: Human Factors, Safety, Healthcare and Speech<\/summary>\n
\n
\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n
Friday, 3 July 2026 \u00b7 10:15 \u2013 13:15 \u00b7 TR-29<\/td>\n<\/tr>\n
Time<\/th>\nPaper #<\/th>\nPaper Title<\/th>\nType<\/th>\n<\/tr>\n
Session H: Human Factors, Safety, Healthcare and Speech<\/td>\n<\/tr>\n
10:15 \u2013 10:25<\/td>\n44<\/td>\nEffects of Display Size on Depth Perception During UAV Simulation Flight<\/td>\nIn-person<\/td>\n<\/tr>\n
10:25 \u2013 10:35<\/td>\n56<\/td>\nPPG-Based Assembly Quality Detection for Human-Centric Manufacturing: An Empirical Study of Cross-Participant Generalization<\/td>\nIn-person<\/td>\n<\/tr>\n
10:35 \u2013 10:45<\/td>\n58<\/td>\nRobust Preprocessing for RMSSD-Based Heart Rate Variability in Wearable ECG Data<\/td>\nIn-person<\/td>\n<\/tr>\n
10:45 \u2013 10:55<\/td>\n155<\/td>\nCLARITY: Contextual Linguistic Adaptation and Accent Retrieval for Dual-Bias Mitigation in Text-To-Speech Generation<\/td>\nIn-person<\/td>\n<\/tr>\n
10:55 \u2013 11:05<\/td>\n159<\/td>\nHuman Error Analysis of Excavator-Related Accidents Using Rasmussen\u2019s Skill-Rule-Knowledge Framework: A Retrospective Study<\/td>\nIn-person<\/td>\n<\/tr>\n
11:05 \u2013 11:15<\/td>\n162<\/td>\nExploring Rider Information Processing for E-Scooter Safety: A Pilot Questionnaire Study<\/td>\nIn-person<\/td>\n<\/tr>\n
11:15 \u2013 11:25<\/td>\n167<\/td>\nAccident Types, Contributing Factors, and Risk Controls for Electric Scooter in South Korea: A Systematic Literature Review<\/td>\nIn-person<\/td>\n<\/tr>\n
11:25 \u2013 13:15<\/td>\nQ&A \/ Buffer<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/details><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\nDay 3 \u00b7 TR-27 \u00b7 PM \u00b7 Virtual Presentations: Special Sessions and Contributed Papers<\/summary>\n
\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Friday, 3 July 2026 \u00b7 14:00 \u2013 16:00 \u00b7 TR-27<\/td>\n<\/tr>\n
Time<\/th>\nPaper #<\/th>\nPaper Title<\/th>\nType<\/th>\n<\/tr>\n
Virtual Special Session: Human-Machine Cooperative Intelligence and Autonomous Driving (6a4h1)<\/td>\n<\/tr>\n
14:00 \u2013 14:10<\/td>\n173<\/td>\nWhat Self-Driving Companies Should Learn from Drone Remote Operations<\/td>\nVirtual<\/td>\n<\/tr>\n
14:10 \u2013 14:20<\/td>\n160<\/td>\nRisk-Adaptive Pareto Coordination for Electric Articulated Vehicles<\/td>\nVirtual<\/td>\n<\/tr>\n
14:20 \u2013 14:30<\/td>\n174<\/td>\nVision-Action Coordination During Lane Changes: Temporal Analyzing Gaze and Steering Dynamics in Real-World Driving<\/td>\nVirtual<\/td>\n<\/tr>\n
Virtual Special Session: Simplified Vehicle Operation (3e38s)<\/td>\n<\/tr>\n
14:30 \u2013 14:40<\/td>\n98<\/td>\nA Unified PHM Operation Interface for Cross-Domain Transportation Systems: A Human-Autonomy Teaming and Safety Assurance Framework Based on OSA-CBM and AIOps<\/td>\nVirtual<\/td>\n<\/tr>\n
14:40 \u2013 14:50<\/td>\n89<\/td>\nAttention-Based Deep Reinforcement Learning for eVTOL Visual Landing Assistance in Unstructured Environments<\/td>\nVirtual<\/td>\n<\/tr>\n
Virtual Special Session: Human-AI Systems for Linguistic Reasoning and AI Education (vv157)<\/td>\n<\/tr>\n
14:50 \u2013 15:00<\/td>\n150<\/td>\nPresupposition-Sensitive Analysis of LLM Assisted Tamil Literary Translation for Translation Education<\/td>\nVirtual<\/td>\n<\/tr>\n
Virtual Contributed Papers: General Human-Machine Systems<\/td>\n<\/tr>\n
15:00 \u2013 15:10<\/td>\n161<\/td>\nRobust Building Damage Detection in Cross-Disaster Settings Using Domain Adaptation<\/td>\nVirtual<\/td>\n<\/tr>\n
15:10 \u2013 15:20<\/td>\n171<\/td>\nMulti-Disease Detection and Severity Grading in Guava Leaves Using Deep Learning: A Real-Time Framework for Precision Agriculture<\/td>\nVirtual<\/td>\n<\/tr>\n
15:20 \u2013 15:30<\/td>\n78<\/td>\nWhen Human-In-The-Loop Fails: Accountability Across AI Adoption Levels in Human-Machine Systems<\/td>\nVirtual<\/td>\n<\/tr>\n
15:30 \u2013 15:40<\/td>\n88<\/td>\nCognitive Imprinting: Stabilizing Interaction in Human-AI Cybernetic Systems<\/td>\nVirtual<\/td>\n<\/tr>\n
15:40 \u2013 15:50<\/td>\n35<\/td>\nMMFCyberDetector: A Multimodal Skeleton-Based Framework for Cyberbullying Action Detection<\/td>\nVirtual<\/td>\n<\/tr>\n
15:50 \u2013 16:00<\/td>\nOpen Q&A with virtual presenters<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/details><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\nDay 3 \u00b7 TR-28 \u00b7 PM \u00b7 Virtual Contributed Papers: General Human-Machine Systems<\/summary>\n
\n
\n<\/colgroup>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Friday, 3 July 2026 \u00b7 14:00 \u2013 16:10 \u00b7 TR-28<\/td>\n<\/tr>\n
Time<\/th>\nPaper #<\/th>\nPaper Title<\/th>\nType<\/th>\n<\/tr>\n
Virtual Contributed Papers: General Human-Machine Systems<\/td>\n<\/tr>\n
14:00 \u2013 14:10<\/td>\n14<\/td>\nEvent-Triggered Prescribed-Time Synchronization for Multi-Agent Quadcopters Using Polynomial Error<\/td>\nVirtual<\/td>\n<\/tr>\n
14:10 \u2013 14:20<\/td>\n50<\/td>\nFake Reviews Detection: Evaluation of Machine Learning Methods for Text Classification in Tourism Context<\/td>\nVirtual<\/td>\n<\/tr>\n
14:20 \u2013 14:30<\/td>\n54<\/td>\nSAGE: Student-Focused Adaptive Guidance Engine for Intelligent Tutoring with Regulated Learning<\/td>\nVirtual<\/td>\n<\/tr>\n
14:30 \u2013 14:40<\/td>\n55<\/td>\nALTR: Adaptive Defense Framework against Adversarial LLM Threats in Critical Domain Applications<\/td>\nVirtual<\/td>\n<\/tr>\n
14:40 \u2013 14:50<\/td>\n63<\/td>\nMTTFormer: A Multi-Branch Integrated Network with Temporal Convolutional Transformers for Motor Imagery Brain-Computer Interfaces<\/td>\nVirtual<\/td>\n<\/tr>\n
14:50 \u2013 15:00<\/td>\n66<\/td>\nPharmacological Non-Stationarity in Human-AI Systems: A Framework for Medication-Aware Adaptive Decision Support<\/td>\nVirtual<\/td>\n<\/tr>\n
15:00 \u2013 15:10<\/td>\n70<\/td>\nCAPTAINM: A Real-Time LLM and RAG Based Decision Support System for Navigational Safety and COLREGs Compliance<\/td>\nVirtual<\/td>\n<\/tr>\n
15:10 \u2013 15:20<\/td>\n94<\/td>\nCognitive Training Using a Brain-Computer Interface for \u03b8\/\u03b2 Ratio Self-Regulation – Preliminary Results with Long COVID-19 Survivors<\/td>\nVirtual<\/td>\n<\/tr>\n
15:20 \u2013 15:30<\/td>\n117<\/td>\nOn Selecting Chatbots Utilized by Small and Medium-Sized Enterprises: Evaluation of a New Taxonomy-Based Selection Metric for Generative AI Based on a Think-Aloud Study with Decision-Makers<\/td>\nVirtual<\/td>\n<\/tr>\n
15:30 \u2013 15:40<\/td>\n136<\/td>\nHand Pose Estimation of Point Cloud Dyadic Human-Object-Human Seated Handover Tasks<\/td>\nVirtual<\/td>\n<\/tr>\n
15:40 \u2013 15:50<\/td>\n157<\/td>\nLanguage Model-Based Monitoring of Cynicism and Discourse Convergence in Student Opinion Articles (2010-2024)<\/td>\nVirtual<\/td>\n<\/tr>\n
15:50 \u2013 16:00<\/td>\n19<\/td>\nImpact of Measurement Duration on the Identification of Touchscreen Biodynamic Feedthrough Models (w SERIO LUCA)<\/td>\nVirtual<\/td>\n<\/tr>\n
16:00 \u2013 16:10<\/td>\nOpen Q&A with virtual presenters<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n“`<\/details><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n \n
Keynote 1<\/div>\n
Prof. Ljiljana Trajkovi\u0107<\/div>\n
Data Mining and Machine Learning for Analysis of Network Traffic<\/div>\n <\/summary>\n
\n
\n \"Prof.\n
\n
Abstract<\/div>\n

Collection and analysis of data from deployed networks is essential for understanding communication networks. Hence, data mining and statistical analysis of network data have been employed to determine traffic loads, analyze patterns of users’ behavior, predict future network traffic, and detect traffic anomalies. The Internet has historically been prone to failures and attacks that significantly degrade its performance, affect the Internet connectivity, and cause routing disconnections. Frequent cases of various cyber threats have been encountered over the years and, hence, detection of anomalous behavior is a topic of great interest in cybersecurity. In described case studies, traffic traces collected by various collection sites are used to classify network anomalies. Various anomaly and intrusion detection approaches based on machine learning have been employed to analyze collected data. Deep learning, broad learning, gradient boosted decision trees, and reservoir computing algorithms were used to develop models based on collected datasets that contain Internet worms, viruses, power outages, ransomware events, router misconfigurations, Internet Protocol hijacks, and infrastructure failures in times of conflict. The reported results indicate that while performance of machine learning models greatly depends on the used datasets, they are viable tools for detecting the Internet anomalies.<\/p>\n <\/div>\n

<\/div>\n
\n
Biography<\/div>\n

Ljiljana Trajkovic received the Dipl. Ing. degree from University of Pristina, Yugoslavia, the M.Sc. degrees in electrical engineering and computer engineering from Syracuse University, Syracuse, NY, and the Ph.D. degree in electrical engineering from University of California at Los Angeles. She is currently a professor in the School of Engineering Science, Simon Fraser University, Burnaby, British Columbia, Canada. Her research interests include communication networks and dynamical systems. Dr. Trajkovic served as IEEE Division X Delegate\/Director, President of the IEEE Systems, Man, and Cybernetics Society, and President of the IEEE Circuits and Systems Society. She serves as Editor-in-Chief of the IEEE Transactions on Human-Machine Systems and is a Fellow of the IEEE.<\/p>\n <\/div>\n <\/div>\n <\/div>\n<\/details>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n \n
Keynote 2<\/div>\n
Prof. Toshio Fukuda<\/div>\n
AI Robots and Future Direction: Embodied Intelligence and Robot<\/div>\n <\/summary>\n
\n
\n \"Prof.\n
\n
Abstract<\/div>\n

There are many ways to make research and development of physical AI robotic systems. I focus on “Embodied Intelligence and Robot” here based on the coevolution and self organization capabilities aiming on solving the Mega-Trend problems. There are new and challenging programs and projects aiming at the AI robotic system in future. I will introduce some of the research projects for realization of the future robot in various fields by back-casting technologies from the 2050 to the current ones. It is important to have new ideas for the physical AI robots rather than not only applications of conventional AI.<\/p>\n <\/div>\n

<\/div>\n
\n
Biography<\/div>\n

Toshio Fukuda received Dr. Eng. from the University of Tokyo, Tokyo, Japan, in 1977. Currently, he is Professor Emeritus at Nagoya University, Professor at Waseda University and Vice President of E-JUST. His major is bio-robotics, especially Micro and Nano Robotics. Dr. Fukuda served as IEEE President and CEO (2020), IEEE Director of Division X, Systems and Control (2017\u20132018), IEEE Region 10 Director (2013\u20132014), and President of IEEE Robotics and Automation Society (1998\u20131999). He was Founding President of IEEE Nanotechnology Council (2002\u20132003, 2005). Awards include IEEE Robotics and Automation Pioneer Award (2004), IEEE Robotics and Automation Technical Field Award (2010), Medal of Honor on Purple Ribbon (2015), and The Order of the Sacred Treasure, Gold Rays with Neck Ribbon (2022). He is an IEEE Fellow (1995) and Member of the Japan Academy of Engineering (2013).<\/p>\n <\/div>\n <\/div>\n <\/div>\n<\/details>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n \n
Keynote 3<\/div>\n
Prof. Chen Chun-Hsien<\/div>\n
AI-aided Human Factors in Intelligent Traffic Management Systems<\/div>\n <\/summary>\n
\n
\n \"Prof.\n
\n
Abstract<\/div>\n

The formal field of human factors was originated during World War II, while artificial intelligence (AI) was invented as a field of study in the mid-1950s. Nevertheless, interactions between these two fields of research used to be limited conventionally. However, AI technologies have been increasingly applied to support various human factors tasks in recent years. In traffic management systems, AI has been employed to identify, analyse, and monitor mental states such as fatigue, workload, and stress for ensuring well-being, enhancing performance, and maintaining operational safety. This talk covers the role of AI in human factors, with applications in air traffic management (ATM) and vessel traffic management (VTM), including case studies on human fatigue detection.<\/p>\n <\/div>\n

<\/div>\n
\n
Biography<\/div>\n

Chun-Hsien Chen is Full Professor, Director of the Design Stream, and Professor-in-Charge of the Design & Human Factors Lab in the School of Mechanical & Aerospace Engineering, Nanyang Technological University, Singapore. He received his BS in Industrial Design from National Cheng Kung University, Taiwan, and MS and Ph.D. in Industrial Engineering from the University of Missouri-Columbia, USA. His research interests include design science, engineering informatics, and human factors. He has over 300 publications and serves as Co-Editor-in-Chief of Advanced Engineering Informatics (since 2013). He has been listed in the World’s Top 2% Scientists by Stanford University (2022\u20132025).<\/p>\n <\/div>\n <\/div>\n <\/div>\n<\/details>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Program-At-A-Glance Day 1 \u2014 Wednesday, 1 July 2026 NTU ARC Time TR-26 TR-27 TR-28 TR-29 TR-24 8:45 \u2013 9:00 Opening Ceremony ARC Lecture Theatre · All delegates 9:00 \u2013 10:00 Keynote 1 — Prof. Ljiljana Trajkovi\u0107 ARC Lecture Theatre · All delegates 10:00 \u2013 10:15 Tea break 10:15 \u2013 13:15 ISACT Summer School Organiser-led sessions…<\/p>\n","protected":false},"author":2626,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-26","page","type-page","status-publish","hentry"],"yoast_head":"\nProgram - IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems<\/title>\n<meta name=\"robots\" content=\"noindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Program - IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems\" \/>\n<meta property=\"og:description\" content=\"Program-At-A-Glance Day 1 \u2014 Wednesday, 1 July 2026 NTU ARC Time TR-26 TR-27 TR-28 TR-29 TR-24 8:45 \u2013 9:00 Opening Ceremony ARC Lecture Theatre · All delegates 9:00 \u2013 10:00 Keynote 1 — Prof. Ljiljana Trajkovi\u0107 ARC Lecture Theatre · All delegates 10:00 \u2013 10:15 Tea break 10:15 \u2013 13:15 ISACT Summer School Organiser-led sessions...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.ieeesmc.org\/ichms-2026\/program-2\/\" \/>\n<meta property=\"og:site_name\" content=\"IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems\" \/>\n<meta property=\"article:modified_time\" content=\"2026-06-19T16:43:42+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-content\/uploads\/sites\/27\/2025\/12\/photo_trajkovic-edited.jpg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"16 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/program-2\\\/\",\"url\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/program-2\\\/\",\"name\":\"Program - IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/program-2\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/program-2\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/wp-content\\\/uploads\\\/sites\\\/27\\\/2025\\\/12\\\/photo_trajkovic-edited.jpg\",\"datePublished\":\"2025-09-21T05:33:36+00:00\",\"dateModified\":\"2026-06-19T16:43:42+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/program-2\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/program-2\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/program-2\\\/#primaryimage\",\"url\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/wp-content\\\/uploads\\\/sites\\\/27\\\/2025\\\/12\\\/photo_trajkovic-edited.jpg\",\"contentUrl\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/wp-content\\\/uploads\\\/sites\\\/27\\\/2025\\\/12\\\/photo_trajkovic-edited.jpg\",\"width\":445,\"height\":445},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/program-2\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Program\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/#website\",\"url\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/\",\"name\":\"IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems\",\"description\":\"Official website of IEEE ICHMS 2026. Learn about paper submission, important dates, and venue in NTU, Singapore\",\"publisher\":{\"@id\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/#organization\",\"name\":\"IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems\",\"url\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/#\\\/schema\\\/logo\\\/image\\\/\",\"url\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/wp-content\\\/uploads\\\/sites\\\/27\\\/2025\\\/10\\\/cropped-ICHMS-2026-Site-Banner-v2-scaled.png\",\"contentUrl\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/wp-content\\\/uploads\\\/sites\\\/27\\\/2025\\\/10\\\/cropped-ICHMS-2026-Site-Banner-v2-scaled.png\",\"width\":2560,\"height\":621,\"caption\":\"IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems\"},\"image\":{\"@id\":\"https:\\\/\\\/www.ieeesmc.org\\\/ichms-2026\\\/#\\\/schema\\\/logo\\\/image\\\/\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Program - IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems","robots":{"index":"noindex","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"og_locale":"en_US","og_type":"article","og_title":"Program - IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems","og_description":"Program-At-A-Glance Day 1 \u2014 Wednesday, 1 July 2026 NTU ARC Time TR-26 TR-27 TR-28 TR-29 TR-24 8:45 \u2013 9:00 Opening Ceremony ARC Lecture Theatre · All delegates 9:00 \u2013 10:00 Keynote 1 — Prof. Ljiljana Trajkovi\u0107 ARC Lecture Theatre · All delegates 10:00 \u2013 10:15 Tea break 10:15 \u2013 13:15 ISACT Summer School Organiser-led sessions...","og_url":"https:\/\/www.ieeesmc.org\/ichms-2026\/program-2\/","og_site_name":"IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems","article_modified_time":"2026-06-19T16:43:42+00:00","og_image":[{"url":"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-content\/uploads\/sites\/27\/2025\/12\/photo_trajkovic-edited.jpg","type":"","width":"","height":""}],"twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"16 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/www.ieeesmc.org\/ichms-2026\/program-2\/","url":"https:\/\/www.ieeesmc.org\/ichms-2026\/program-2\/","name":"Program - IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems","isPartOf":{"@id":"https:\/\/www.ieeesmc.org\/ichms-2026\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.ieeesmc.org\/ichms-2026\/program-2\/#primaryimage"},"image":{"@id":"https:\/\/www.ieeesmc.org\/ichms-2026\/program-2\/#primaryimage"},"thumbnailUrl":"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-content\/uploads\/sites\/27\/2025\/12\/photo_trajkovic-edited.jpg","datePublished":"2025-09-21T05:33:36+00:00","dateModified":"2026-06-19T16:43:42+00:00","breadcrumb":{"@id":"https:\/\/www.ieeesmc.org\/ichms-2026\/program-2\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.ieeesmc.org\/ichms-2026\/program-2\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.ieeesmc.org\/ichms-2026\/program-2\/#primaryimage","url":"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-content\/uploads\/sites\/27\/2025\/12\/photo_trajkovic-edited.jpg","contentUrl":"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-content\/uploads\/sites\/27\/2025\/12\/photo_trajkovic-edited.jpg","width":445,"height":445},{"@type":"BreadcrumbList","@id":"https:\/\/www.ieeesmc.org\/ichms-2026\/program-2\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.ieeesmc.org\/ichms-2026\/"},{"@type":"ListItem","position":2,"name":"Program"}]},{"@type":"WebSite","@id":"https:\/\/www.ieeesmc.org\/ichms-2026\/#website","url":"https:\/\/www.ieeesmc.org\/ichms-2026\/","name":"IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems","description":"Official website of IEEE ICHMS 2026. Learn about paper submission, important dates, and venue in NTU, Singapore","publisher":{"@id":"https:\/\/www.ieeesmc.org\/ichms-2026\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.ieeesmc.org\/ichms-2026\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/www.ieeesmc.org\/ichms-2026\/#organization","name":"IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems","url":"https:\/\/www.ieeesmc.org\/ichms-2026\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.ieeesmc.org\/ichms-2026\/#\/schema\/logo\/image\/","url":"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-content\/uploads\/sites\/27\/2025\/10\/cropped-ICHMS-2026-Site-Banner-v2-scaled.png","contentUrl":"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-content\/uploads\/sites\/27\/2025\/10\/cropped-ICHMS-2026-Site-Banner-v2-scaled.png","width":2560,"height":621,"caption":"IEEE ICHMS 2026 \u2013 International Conference on Human-Machine Systems"},"image":{"@id":"https:\/\/www.ieeesmc.org\/ichms-2026\/#\/schema\/logo\/image\/"}}]}},"_links":{"self":[{"href":"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-json\/wp\/v2\/pages\/26","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-json\/wp\/v2\/users\/2626"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-json\/wp\/v2\/comments?post=26"}],"version-history":[{"count":0,"href":"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-json\/wp\/v2\/pages\/26\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.ieeesmc.org\/ichms-2026\/wp-json\/wp\/v2\/media?parent=26"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}