Name: HumanSys 2026
Start: 2026-10-30
End: 2026-10-30
Location: Austin, Texas, USA

Overview

HumanSys 2026 brings together researchers and practitioners working on sensing, models, and interactive systems that are designed around real human needs.

Human-centered sensing for health, behavior, activity, and context understanding
AI and statistical models that support human-in-the-loop decision making and adaptation
Systems, interfaces, and deployments evaluated in real-world environments with people

The workshop aims to create a focused venue for discussing methods, systems, and lessons learned across sensing, modeling, interaction design, and deployment.

Program

2 Keynotes

23 Oral talks

10 Posters

4 Sessions

Morning

8:00–8:30 AM

Arrival
Tea, coffee, and continental breakfast
8:30–8:40 AM

Welcome
Opening remarks
8:40–9:30 AM

Keynote Sense the Invisible: From Commodity Devices to Programmable Physics and Wearables
Dr. Lili Qiu

NAI Fellow, ACM Fellow, IEEE Fellow, Professor, Dept. of Computer Science, University of Texas at Austin

40-minute talk + 10-minute Q&A
9:30–10:30 AM
Session 1
6 oral presentations · 8 min talk + 2 min Q&A
1. HeadSense: Head Orientation Tracking for AI Wearables using Ultra-Wideband Ranging
  
  A. K. Agrawal, A. Dhekne, R. R. Choudhury
2. ABreath: Bed-Frame-Mounted Vibration Sensing for Noise-Robust Abnormal Breathing Detection
  
  S. Yin, J. Zhang, L. Yang, Y. Rong, L. Qian, P. Zhang, J. Zhu
3. Design and Characterization of an Energy-Aware Embedded System for On-Device Postural Muscle Profiling
  
  J. Reyes, R. Vargas, B. Sanchez, S. Rohal, S. Pan, X. Yu
4. Comparing Self-Supervised Pretraining Methods and Transfer Configurations for Wrist ECG under Motion
  
  Y. Hu, Z. Jia, S. Chen, D. Kelly, M. Zhao, T. Chen, R. Liu, J. Nie
5. RecoverRL: Reliability-Guided Reinforcement Learning for RFID-Based Heartbeat Waveform Recovery
  
  Y. Wang, C. Liu, D. Nguyen, H. Bai, Z. Jiao, S. Mao, X. Wang
6. Optimizing the Duty Cycle in Smartwatches for Sleep Sensing
  
  T. Srivastava, V. Viswanath, Z. Yang, V. Nathan, J. Kuang
10:30–11:00 AM

Break
Coffee break
11:00 AM–12:10 PM
Session 2
7 oral presentations · 8 min talk + 2 min Q&A
1. mmSketcher: Physics-Grounded and Editable Scenes for mmWave Human-Sensing Simulation
  
  S. Lu, T. Toha, S. Nirjon
2. HERO: Human-Centered, Environment-Aware Optimization for Designing Gait Sensing Under Requirement Uncertainty
  
  A. Green, Y. Li, S. Billington, Y. Dong
3. RadarAgent: Agentic Tool Utilization for Radar-to-Language Understanding
  
  S. He, Y. Gao, R. Nandakumar
4. Generating Human Pose and Activity Videos from Wearable Ultra-Wideband Sensors
  
  T. Toha, Z. Wang, D. Jagadeesh, G. Zhang, T. Chen, S. Nirjon
5. Open-World Continuous Human Activity Recognition with Novel Class Discovery
  
  J. Jiang, E. Thomaz
6. CausalGait: Towards Personalized Gait Interpretation via Causality-Informed Knowledge Graphs
  
  M. Ma, M. Yang, K. Clewes, E. Lowe, J. Rose, Y. Dong
7. Only Speaking FACTs: Foundation Models for Activity-Centric Timeline Description
  
  D. Lee, T. Patil, S. Pan, A. Weakley
12:10–12:15 PM

Transition
Announcements

12:15–1:30 PM

Lunch break

Afternoon

1:30–2:20 PM

Keynote Chatbot: Empowering Medical Communication using AI
Dr. Ying Ding

Bill & Lewis Suit Professor, iSchool, University of Texas at Austin

40-minute talk + 10-minute Q&A
2:20–3:30 PM
Session 3
7 oral presentations · 8 min talk + 2 min Q&A
1. HumanSpeech-TeleOp: Human-in-the-Loop Edge-IoT Framework for Speech and LLM-Driven Robot Teleoperation and Object Detection
  
  H. Nambiappan, C. Song, A. Truong, F. Makedon
2. HotRGB: Temperature Aware RGB-to-Thermal Training Data for Drive-by Urban People Detection
  
  T. Fernandez, Y. Chang, C. Codling, J. Zhang, J. Gersey, N. Sochocki, S. Ganti, J. Aggarwal, J. Ko, H. Noh, L. Junghans, P. Zhang
3. FollowMe: Automating Precise Image Annotation Across Various Environments
  
  S. Xia, J. Du, C. Peng
4. Evidence-Grounded Mapping of Multimodal Human Sensing to Psychological Transdiagnostic Dimensions
  
  X. Hu, X. Xue, Y. Lyu, H. Shao, J. Nie
5. When Not to Diagnose: Evaluating Evidence-Sufficiency Recognition in ECG Multimodal Language Models with ECGTrustBench
  
  Q. Huang, J. Jiang, F. Syed, A. Riaz, Y. Chen, J. Nie
6. GREAF: Graph-based Real-time Anomaly Detection via Forecasting for IoT-Enabled Indoor Spaces
  
  M. Tanvir, F. Irfan, R. Iqbal
7. Will My Assistant Remember My Allergy? What Personal LLM Assistants Forget When Conversation Memory Is Compressed
  
  L. Zhu, Y. Lin, Y. Wang, Y. Liu, H. Li, Y. Chen
3:30–4:00 PM

Break
Coffee break and poster setup
4:00–4:50 PM
Posters
10 posters
1. Vision: HomeLM for Ambient Intelligence in the Smart Home
  
  A. Agrawal
2. Out-of-Clinic Measurement of Time-Domain Gait Parameters From Low-Frame-Rate Videos
  
  Y. Fu, Y. Luo, S. Ndiaye, C. Xu
3. Harnessing Agent Capabilities to Integrate Human Demands into Energy Infrastructure Operations
  
  T. Zhou, J. Wen, J. Yang
4. From Community Feedback to Measurement Redesign: Iterating mRehab for Accessible Home-Based Stroke Rehabilitation
  
  E. Liu, K. Dandapat, T. Master, A. Das, A. Gherardi, W. Bo, L. Cavuoto, S. Bhattachariya, H. Subryan, W. Ji, W. Xu
5. Exploring Privacy Risks of Inertial Sensing on Wearable Rings: A Feasibility Study on Keystroke Classification
  
  C. Arvonen, N. Maldei-Stumm, A. Chatterjee, A. Jain, S. Sanghavi, E. Thomaz
6. FocusSync: A Multisensory Audio–Visual–Haptic Stimulation System for Attention Support
  
  N. Anjum, C. Cao, C. Shultz, Y. Dong
7. Contact-Free Continuous ABP Waveform Reconstruction via Triaxial Bodyseismography
  
  Y. Wu, Y. Zhang, Y. Zhang, J. Li, F. Dou, W. Song, H. Noh
8. Separating Safety from Preference in Clinical LLM Evaluation
  
  K. Dandapat, T. Master, A. Das, W. Bo, M. Lei, E. Liu, L. Cavuoto, S. Bhattachariya, H. Subryan, W. Xu
9. A Real-World Study of Sport-Based Support for Autism Spectrum Disorder
  
  H. Yang, E. Liu, X. Zhang, W. Bo, Y. Wu, Y. Liu, Q. Xie, W. Xu
10. Comparing Three On-Device Classifier Deployments for Ring Microgesture Recognition
  
  Y. Du, E. Thomaz
4:50–5:20 PM
Session 4
3 oral presentations · 8 min talk + 2 min Q&A
1. HearFocus: Low-Latency Speech Separation for User-Focused Listening
  
  H. Zhao, K. Shen, H. Li
2. RAST: Resolution-Aware Privileged Structure Transfer for Low-Resolution Audio Activity Recognition
  
  J. Park, G. Gudur, Y. Shen, D. Liang, E. Thomaz
3. Identifying Office Door Closing from Acoustic and Vibration Data
  
  B. Fengler, A. Reinhardt
5:20–5:30 PM

Closing
Awards and closing remarks

Keynotes

Keynote 1 · 8:40–9:30 AM

Dr. Lili Qiu

NAI Fellow, ACM Fellow, IEEE Fellow, Professor, Dept. of Computer Science, University of Texas at Austin

Sense the Invisible: From Commodity Devices to Programmable Physics and Wearables

Abstract

Our world is filled with information we cannot easily see: how people move, breath, and interact, what lies beyond our line of sight, and subtle signals from within our bodies. Traditionally, accessing such information has required specialized sensors, carefully instrumented environments, or cumbersome devices. But what if the devices and environments already around us could reveal far more?

In this talk, I will share our journey toward sensing the invisible. We began by showing that everyday devices can do much more than they were designed for: ordinary speakers and microphones can track motion, locate people, and even form images of their surroundings. We then asked whether, instead of simply listening more carefully to the signals nature gives us, we could shape the physical world to reveal information that is otherwise difficult to see. This led us to metasurfaces that manipulate waves to enable new forms of sensing, imaging, and even non-invasive physiological monitoring. Most recently, we are exploring how lightweight wearables can quietly capture rich signals from the human body, bringing sensing from the environment increasingly close to the individual.

Together, these efforts point toward a future where sensing becomes both more powerful and less visible -- woven into the devices we use, the environments we inhabit, and the things we wear. As sensing fades into the background, it can enable a world that understands and responds to us more naturally, continuously, and almost invisibly.

Bio

Lili Qiu is a Professor of Computer Science at The University of Texas at Austin. She received her Ph.D. in Computer Science from Cornell University in 2001. From 2001 to 2004, she was a researcher at Microsoft Research in Redmond before joining UT Austin in 2005. From 2022 to 2025, she served as an Assistant Managing Director at Microsoft Research Asia, where she led cross-disciplinary research spanning AI, systems, and wireless technologies. Her research spans wireless and mobile systems, sensing, and AI, with recent work exploring commodity-device sensing, metasurfaces, and wearable sensing. She is a Fellow of the ACM, IEEE, and the National Academy of Inventors (NAI).

Keynote 2 · 1:30–2:20 PM

Dr. Ying Ding

Bill & Lewis Suit Professor, iSchool, University of Texas at Austin

Chatbot: Empowering Medical Communication using AI

Abstract

Conventional medical communication has been fundamentally broken, placing an increasing burden on healthcare professionals and significantly contributing to burnout and inefficiency. Physicians, nurses, and administrative staff face overwhelming demands, fragmented workflows, and ineffective communication channels, which detract from patient care. A major breakthrough is imminent with the emergence of intelligent chatbots powered by Large Language Models (LLMs). This talk will highlight several perspectives on how LLM powered chatbots revolutionize healthcare communication: 1) a voice powered chatbot for reminiscence therapy for early dementia patients; 2) a patient simulator for medical communication training; and 3) a medical transcript assistant to identify care gaps using inductive thematic analysis.

Bio

Dr. Ying Ding is Bill & Lewis Suit Professor at School of Information, University of Texas at Austin. She co-chairs AI in Health Lab at School of Information and Dell Medical School at UT Austin. She has collaborated widely with researchers in healthcare and drug discovery. Together with her colleague at Dell Medical School, the AI Health Lab aims to build human-centered AI approaches to deliver better health. Her lab is actively developing and applying chatbot to facilitate medical communication and counseling, LLM on drug combination synergy prediction, visual question answer for pathology images, medical annotation for social determinants of health, and LLM hallucination and uncertainty quantification for agentic AI in healthcare. Furthermore, her lab also focuses on developing deep learning method for medical imaging diagnosis , applying Natural Language Processing (NLP) for medical note annotation and summary, utilizing explainable AI and knowledge graph for health risk prediction, and understanding AI fairness in healthcare. She has published 400+ papers, chaired 60+ workshops, and served as a Program Committee member for 300+ international conferences. Her lab is supported by NIH, NSF, and major industry partners.

Call for Papers

This workshop aims to foster collaboration among researchers and practitioners from academia, industry, and service sectors, providing a platform to share ideas and experiences in developing human-centered systems.

We welcome contributions that emphasize human-centric sensing technologies, novel models for human-centered systems, and applications in areas including, but not limited to:

Human-Centered Sensing and Data Acquisition

Novel sensing approaches for health, activity, gesture, and behavior monitoring of individuals or groups
Camera, VR/AR, wearables, mobile platforms, vibration, acoustics, IMU, mmWave, and WiFi sensing
Data management and transmission methodologies, including communication and networking

Human-Centered Static and AI Driven Models

Statistical models for representing and analyzing human behavior, preferences, and environmental interactions
Advanced AI models and techniques, including LLMs, convolutional neural networks, transformers, graph neural networks, time-series models, and statistical learning models
System models or frameworks for human-in-the-loop applications and data interpretation in cyber-physical systems

Human-Centered System Design and Implementation

Integration of human needs and preferences in the design of cyber-physical systems
Privacy considerations, UI/UX design, and the integration of LLM agents or related intelligent systems
Prototyping and iterative system design to refine and validate human-centered solutions

Applications and Real-World Studies

Real-world deployment experience with human participants
Evaluation methodologies and insights of cyber-physical systems with humans in the loop
Applications across healthcare, smart living, accessibility, and everyday environments

Submission

Submitted papers must be unpublished and must not be currently under review for any other publication.

We will solicit papers in three categories:

Full Papers (up to 6 pages including references) should report reasonably mature work in human-centered sensing, modeling, or intelligent systems.
Experience Papers (up to 4 pages including references) should present experiences with the implementation, deployment, and operation of novel sensing or modeling technologies for human-centered applications.
Extended Abstracts (up to 2 pages including references) are encouraged to report novel and creative ideas that may benefit from early community feedback.

All papers will be at most 6 single-spaced 8.5" x 11" pages with 10-pt font size in two-column format, including figures, tables, and references. All submissions must use the LaTeX (preferred) or Word styles found here. LaTeX submissions should use the acmart.cls template (sigconf option), with the 10-pt font. All of the accepted papers (regardless of category) will be included in the ACM Digital Library.

HumanSys'26 follows a single-blind review process.

Please submit your papers via this link: https://humansys26.hotcrp.com/.

A Best Paper Award, sponsored by Nokia, will be presented at the workshop.

Important Dates

Paper submission ~~July 8, 2026~~ July 15, 2026 AOE (Firm deadline)

Acceptance notification August 15, 2026

Camera-ready deadline August 30, 2026

Workshop date October 30, 2026

Submission Notes

Submission link HotCRP
Review processsingle-blind review process
Page limitsFull Papers: up to 6 pages; Experience Papers: up to 4 pages; Extended Abstracts: up to 2 pages

Policies

Human Participants Policy

All submissions are subject to ACM Publications Policies, including ACM's policy on research involving human participants and subjects. Authors should review the policy carefully before submission.

Learn more about the ACM policy

ORCID Requirement

Authors of accepted papers should ensure that they have an ORCID ID available for the ACM publishing workflow. ORCID helps improve author discoverability, attribution, and name normalization across publications.

Organization

General Chairs

Yiwen Dong (yiwen@illinois.edu, University of Illinois Urbana-Champaign, USA)
Jingping Nie (jingping@unc.edu, UNC Chapel Hill, USA)
Yang Liu (yang.16.liu@nokia.com, Nokia, UK)

Program Chairs

Sijie Ji (sijieji@caltech.edu, California Institute of Technology, USA)
Huining Li (hli83@ncsu.edu, North Carolina State University, USA)

Publicity Chairs

Yuyan Wu (wuyuyan@stanford.edu, Stanford University, USA)
Ruiqing Wang (ruiqing@illinois.edu, University of Illinois Urbana-Champaign, USA)

Social Media Chairs

Jiale Zhang (jiale@umich.edu, University of Michigan, USA)
Mingrui Ma (mma36@illinois.edu, University of Illinois Urbana-Champaign, USA)

Web Chairs

Julia Gersey (gersey@umich.edu, University of Michigan, USA)
Jinsi Guo (jinsig2@illinois.edu, University of Illinois Urbana-Champaign, USA)
Jingxia Jiang (jjingxia@unc.edu, UNC Chapel Hill, USA)

Steering Committee Members

Fred Xiaofan Jiang (Columbia University, USA)
Pei Zhang (University of Michigan, USA)

Technical Program Committee

Ananta Narayanan Balaji (Nokia, UK)
Andrea Ferlini (ŌURA, UK)
Dong Ma (University of Cambridge, UK)
Junlong Chen (University of Cambridge, UK)
Jiale Zhang (University of Michigan, USA)
Lilin Xu (Columbia University, USA)
Longfei Shangguan (University of Pittsburgh, USA)
Minghui Zhao (Columbia University, USA)
Qiang Yang (University of Cambridge, UK)
Qijia Huang (Duke University, USA)
Qijia Shao (The Hong Kong University of Science and Technology, China)
Sheng Lyu (The University of Hong Kong, China)
Sheng Sheng (The University of Hong Kong, China)
Shubham Rohal (UC Merced, USA)
Tao Chen (Samsung Research America, USA)
Ting Dang (The University of Melbourne, Australia)
Wei Bo (University at Buffalo, the State University of New York (SUNY), USA)
Xinzhe Zheng (National University of Singapore, Singapore)
Yang Liu (Florida State University, USA)
Yiting Wang (Florida International University, USA)
Ziyan An (Vanderbilt University, USA)

Venue

HumanSys 2026 is co-located with ACM MobiCom 2026 in Austin, Texas, USA, and shares its venue. Please refer to the MobiCom venue page for the conference hotel, travel, and local information.

ACM MobiCom 2026 venue information

Registration

Workshop attendance is handled through ACM MobiCom 2026 registration. Please refer to the MobiCom registration page for rates, deadlines, and the registration form.

ACM MobiCom 2026 registration