Mingyue TangPh.D. StudentDepartment of Computer Science University of Illinois Urbana-Champaign (UIUC) Email: mt55 [at] illinois [dot] edu
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Bio
My name is Mingyue Tang, I am a Ph.D. student in the Department of Computer Science at the University of Illinois Urbana-Champaign (UIUC).
Working with Prof. Elahé Soltanaghai on wireless and IoT problems with machine learning approches. Check our group website here.
I was a M.Eng. (originally a Ph.D.) student at the University of Virginia (UVa) Link Lab .
I am passionate about exploring the potential of technology to improve our daily lives.
My research interests include Mobile Sensing, Mobile Computing, Signal Processing and Internet of Things, Data Mining, Pervasive Computing, and Healthcare Systems.
Through my work, I aim to create innovative wireless/mobile sensing solutions that can address real-world problems and make a positive impact on society.
I believe that technology has the power to revolutionize the way we live and work, and I am excited to share my research and ideas with you!
Previously, I cooperated with Prof. Laura Barnes (UVa), Prof. Ang Li (UMD), Prof. Mehdi Boukhechba (UVa, now at Janssen R&D), Prof. Carl Yang (Emory),
Prof. Pan Li (GaTech), Prof. José Luis Ambite (USC ISI), Prof. Tiffany Tang (WKU), and Prof. Pinata Winoto(WKU)
Main Research Interests
Mingyue's research interests are Wireless Sensing, Mobile Sensing, Intelligent Internet of Things (IoT) System, and all the above things + Healthcare.
- Mobile Sensing/Wireless Sensing
- Artificial intelligence in Internet of Things (AIoT)
- Ubiquitous Computing in Healthcare and other applications
News
| [03/2025] | Our Paper "ChirpEye: Passive Sensing and Profiling of FMCW Radars with a Resource-constrained Tag" has been accepted to MobiCom 2025. |
| [02/2025] | Our team has been selected as a finalist for the Qualcomm Innovation Fellowship. |
| [02/2025] | Our (with UVa) Paper "Atlas: Ensuring Accuracy for Privacy-Preserving Federated IoT Applications" has been accepted to ICCPS 2025. |
| [12/2024] | The paper from my internship at Abbott, Case report: Potential physiological sources of the late response in epidural spinal recordings induced by spinal cord stimulation during intraoperative neuromonitoring, has been accepted to Clinical Neurophysiology Practice. |
| [10/2024] | I have been selected for an N2Women Young Researcher Fellowship to organize an N2Women event at SenSys 2024. |
| [09/2024] | Our Paper "BSENSE: In-vehicle Child Detection and Vital Sign Monitoring with a Single mmWave Radar and Synthetic Reflectors" was accepted by SenSys 2024 . |
| [09/2024] | Our Poster "Extended-Range Two-way Radar Backscatter Communication with Low-Power IoT Tags" was accepted by MobiCom 2024. |
| [08/2024] | Semi-volunteered as a student co-ordinators for CS 591 WN: Wireless Networking Seminar, register if you are interested in wireless topics! |
| [08/2024] | Our (with WKU) recently accepted workshop in UbiComp 2024 on the topic of Interactive Design with Autistic Children Using LLM and IoT for Personalized Training: The Good, The Bad and The Challenging will happening in Melbourne, Australia this year. |
| [05/2023] | Transfer to UIUC. Graduated again, glad to received my master degree in Systems and Information engineering at UVa! |
| [04/2023] | Our fluid overload detection paper accepted by CHIL 2023 has been selected for an oral presentation (13.3%)! |
| [04/2023] | One paper was accepted by EMBC 2023 on personalized state anxiety detection using linguistic indicators! |
| [04/2023] | One paper was accepted by CHIL 2023 on fluid overload detection in ESKD patients! |
| [03/2023] | I decided to choose University of Illinois Urbana-Champaign (UIUC) as my next stop to continue my Ph.D. journey. |
| [01/2023] | I started my internship at Abbott as Scientist I. |
Selected Publications
See my full list at [Google Scholar]* indicates equal contribution!
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ChirpEye: Passive Sensing and Profiling of FMCW Radars with a Resource-constrained Tag |
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Atlas: Ensuring Accuracy for Privacy-Preserving Federated IoT Applications |
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BSENSE: In-vehicle Child Detection and Vital Sign Monitoring with a Single mmWave Radar and Synthetic Reflectors |
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Extended-Range Two-way Radar Backscatter Communication with Low-Power IoT Tags |
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Personalized State Anxiety Detection: An Empirical Study with Linguistic Biomarkers and Machine Learning Pipeline |
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SRDA: Mobile Sensing based Fluid Overload Detection for End Stage Kidney Disease Patients using Sensor Relation Dual Autoencoder |
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PFed-LDP: A Personalized Federated Differential Privacy framework for IoT sensing |
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Mobile Sensing in the COVID-19 Era |
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Dynamic Network Anomaly Modeling of Cell-Phone Call Detail Records for Infectious Disease Surveillance |
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GNNs in IoT: A Survey |
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Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction |
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Using Ubiquitous Mobile Sensing and Temporal Sensor-Relation GNN to Predict Fluid Intake of End Stage Kidney Patients |
Experience
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Abbott, TX, US Scientist I, Spring 2023 Mentor: Mingming Zhang |
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University of Virginia, Data Science School VA, US Teaching Assistant, Spring 2021 - Present |
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Novartis, Inc., NJ, US Data Strategy Team, Summer 2020 |
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University of Southern California, Information Science Institute (ISI) , Marina Del Rey, US Research Assistant, Fall 2019 & Fall 2020 Mentors: José Luis Ambite , Pedro Szekely |
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Selected Projects
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Federated Learning on IoT data Optimized the accuracy of collaborative training data from IoT edge devices while preserving privacy. |
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SIMS - Social Interactions Monitoring Study Monitoring social state anxiety with wearable sensors and webcams. |
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FluiSense Using multi-modal mobile sensing for better fluid control for end stage kidney disease (ESKD) Patients. Conducted a 4-week study and collected time-series data with on-body physiological and behavioral sensors (e.g., PPG, IMU) from ESKD patients.
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Graph Unsupervised Representation Learning A new unsupervised way of graph learning, addressed existing limitations in graph autoencoder, graph structure learning, and infomax-based methods.
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Service