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25 26 27</head> 28<body class="bg-light" data-spy="scroll" data-target="#navbar-year" data-offset="100"> 29 <nav class="navbar navbar-expand-sm navbar-light bg-light fixed-top mb-5 shadow-sm"> 30 <div class="container-lg"> 31 <a class="navbar-brand"><strong>Fei Dou</strong></a> 32 <button class="navbar-toggler" style="font-size: 1em; padding: 0.5em;" type="button" data-toggle="collapse" data-target="#navbarResponsive" aria-controls="navbarResponsive" aria-expanded="false" aria-label="Toggle navigation"> 33 <i class="fas fa-map"></i> Menu 34 </button> 35 36 <div class="collapse navbar-collapse" id="navbarResponsive"> 37 <ul class="navbar-nav ml-auto"> 38 39 <li class="nav-item "> 40 <a class="nav-link" href="/">Home</a> 41 </li> 42 43 <li class="nav-item "> 44 <a class="nav-link" href="/publications">Publications</a> 45 </li> 46 47 <li class="nav-item "> 48 <a class="nav-link" href="/teaching">Teaching</a> 49 </li> 50 51 <li class="nav-item active"> 52 <a class="nav-link" href="/research">Research</a> 53 </li> 54 55 <li class="nav-item "> 56 <a class="nav-link" href="/group">Group</a> 57 </li> 58 59 <li class="nav-item "> 60 <a class="nav-link" href="/showcase">Showcase</a> 61 </li> 62 63 </ul> 64 </div> 65 </div> 66</nav> 67 68 <div class="container-lg"> 69 <div class="container py-4"> 70 <h1 class="mb-4">Research Overview</h1> 71 <p>Our group investigates problems at the intersection of machine learning, sensing systems, and human-centered AI. Our research spans multiple domains with the shared goal of building robust, privacy-friendly, and adaptive intelligent systems.</p> 72 73 <hr class="my-4"> 74 75 <h2 class="mt-4">Key Research Areas</h2> 76 77 <ul class="list-unstyled"> 78 79 <li class="mb-3"> 80 <h4>ð Ambient Intelligence and Spatial Context Understanding in Smart Environments</h4> 81 <p> We develop machine learning and sensing methods that enable smart environments to understand human activities, locations, and spatial context. Our research includes activity recognition from event-triggered sensors, layout-aware and trajectory-aware modeling, cross-modal sensor alignment, generative modeling for symbolic sensor streams, and indoor localization with wireless and mobile sensing. </p> 82 <p class="mb-2"><strong>Representative publications:</strong></p> 83 <ul class="mb-0"> 84 <li class="mb-2"> <strong>HomeTwin: Interaction-Aware Synthetic Data Generation for Multi-Resident Smart Homes.</strong> <span class="badge badge-paper">UbiComp'26 Student Challenge</span><br> <span class="text-muted"> <u>Z Liu</u>, <u>R Fang</u>, J Lu, <strong><em>F Dou</em></strong>#. </span> </li> 85 <li class="mb-2"> <strong>LastAct: Trajectory-Guided Latest-Activity Localization for Real-Time Smart-Home Activity Recognition.</strong> <span class="badge badge-paper">UbiComp/IMWUT'26</span><br> <span class="text-muted"> <u>Z Liu</u>*, <u>R Fang</u>*, J Lu, <strong><em>F Dou</em></strong>#. </span> </li> 86 <li class="mb-2"> <strong>ADLGen: Synthesizing Symbolic, Event-Triggered Sensor Sequences for Human Activity Modeling.</strong> <span class="badge badge-paper">SenSys'26</span><br> <span class="text-muted"> <u>W You</u>*, H Jiang*, <u>J Li</u>*, <u>Z Liu</u>*, T Liu, J Lu, <strong><em>F Dou</em></strong>#. </span> </li> 87 <li class="mb-2"> <strong>CARE: Contrastive Alignment for ADL Recognition from Event-Triggered Sensor Streams.</strong> <span class="badge badge-paper">PerCom'26</span><br> <span class="text-muted"> <u>J Zhao</u>, <u>Z Liu</u>, <u>R Fang</u>, J Lu, L Zhang, <strong><em>F Dou</em></strong>#. </span> </li> 88 <li class="mb-2"> <strong>Cross-Modal Translation and Alignment of Sensor Events for Layout-Aware Activity Modeling.</strong> <span class="badge badge-paper">ISWC'25</span><br> <span class="text-muted"> <u>W You</u>, <u>Z Liu</u>, <strong><em>F Dou</em></strong>#. </span> </li> 89 <li class="mb-2"> <strong>MARAuder's Map: Motion-Aware Real-time Activity Recognition with Layout-Based Trajectories.</strong> <span class="badge badge-paper">arXiv'25</span><br> <span class="text-muted"> <u>Z Liu</u>, <u>W You</u>, J Lu, <strong><em>F Dou</em></strong>#. </span> </li> 90 <li class="mb-2"> <strong>On-Device Indoor Positioning: A Federated Reinforcement Learning Approach With Heterogeneous Devices.</strong> <span class="badge badge-paper">IoT-J'23</span><br> <span class="text-muted"> <strong><em>F Dou</em></strong>, J Lu, T Zhu, J Bi. </span> </li> 91 <li class="mb-2"> <strong>A Bisection Reinforcement Learning Approach to 3-D Indoor Localization.</strong> <span class="badge badge-paper">IoT-J'20</span><br> <span class="text-muted"> <strong><em>F Dou</em></strong>, J Lu, T Xu, C-H Huang, J Bi. </span> </li> 92 <li class="mb-2"> <strong>Top-Down Indoor Localization with Wi-Fi Fingerprints Using Deep Q-Network.</strong> <span class="badge badge-paper">MASS'18</span><br> <span class="text-muted"> <strong><em>F Dou</em></strong>, J Lu, Z Wang, X Xiao, J Bi, C-H Huang. </span> </li> </ul> 93 </ul> 94 <p class="mt-2 mb-0 text-muted small"> * Equal contribution. # Corresponding author. </p> 95 </li> 96 97 <hr class="my-5"> 98 99 100 101 102 <li class="mb-3"> 103 <h4>ð« Contactless Health Sensing and Physiological AI</h4> 104 <p>We develop machine learning and sensing systems for contactless monitoring of human physiology in real-world environments. Our work spans problems such as blood pressure estimation, sleep apnea detection, respiration and snoring analysis, posture recognition, and physiological peak detection, with an emphasis on robustness, interpretability, and deployment in everyday and clinical settings.</p> 105 <p class="mb-2"><strong>Representative publications:</strong></p> 106 <ul class="mb-0"> 107 <li class="mb-2"> <strong>EarlyDx: An Admission-Anchored Benchmark for Open-Ended Generation of Evidence-Supported ED-Encounter Diagnoses.</strong> <span class="badge badge-paper">arXiv'26</span><br> <span class="text-muted"> <u>J Li</u>, <u>R Fang</u>, <u>Z Liu</u>, <u>Y Guo</u>, N Yang, W Song, J Lu, <strong><em>F Dou</em></strong>#. </span> </li> 108 <li class="mb-2"> <strong>DeepArrhythmia: Segment-Contextualized ECG Arrhythmia Classification via Selective Evidence Acquisition.</strong> <span class="badge badge-paper">NeurIPS'26</span><br> <span class="text-muted"> <u>J Li</u>, <u>R Fang</u>, <u>Z Liu</u>, W Song, J Lu, <strong><em>F Dou</em></strong>#. </span> </li> 109 <li class="mb-2"> <strong>Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods.</strong> <span class="badge badge-paper">PBME'26</span><br> <span class="text-muted"> T Li, Y Yan, <strong><em>F Dou</em></strong>, W Song, X Zhang. </span> </li> 110 <li class="mb-2"> <strong>Peak-Detector: Explainable Peak Detection via Instruction-Tuned Large Language Models in Cardiac Physiological Signal.</strong> <span class="badge badge-paper">UbiComp/IMWUT'26</span><br> <span class="text-muted"> <u>J Li</u>, Y Zhang, Z Zeng, J Chen, Y Song, Y Xiao, N Dong, J Lu, Y Kwon, X Zhang, J Lu, W Song, <strong><em>F Dou</em></strong>#. </span> </li> 111 <li class="mb-2"> <strong>Contactless Sleep Apnea Detection with Bodyseismography.</strong> <span class="badge badge-paper">UbiComp/IMWUT'26</span><br> <span class="text-muted"> Y Song*, J Chen*, Z Zeng, Y Zhang, Z F Pitafi, D K Das, B G Phillips, Y Kwon, X Zhang, <strong><em>F Dou</em></strong>, W Song. </span> 112 </li> <li class="mb-2"> <strong>Attention Feature Fusion with Cluster Contrastive Learning for Snoring and Breath-Holding Detection Using Seismic Sensing.</strong> <span class="badge badge-paper">PerCom'26</span><br> <span class="text-muted"> Y Song*, J Chen*, Z Zeng, Y Zhang, Z F Pitafi, X Zhang, <strong><em>F Dou</em></strong>, W Song. </span> </li> 113 <li class="mb-2"> <strong>
113Peak-R1: Instruction-Tuned Large Language Models for Robust J-Peak Detection in Cardiomechanical Signals.</strong> <span class="badge badge-paper">TS4H @ NeurIPS'25</span><br> <span class="text-muted"> <u>J Li</u>, Y Zhang, Z Zeng, J Chen, X Zhang, J Lu, W Song, <strong><em>F Dou</em></strong>#. </span> </li> 114 <li class="mb-2"> <strong>Multi-granularity Supervised Contrastive Learning with Online Adaptation for Contactless In-bed Posture Classification.</strong> <span class="badge badge-paper">UbiComp/IMWUT'25</span><br> <span class="text-muted"> Y Song*, H Xiang*, Z Zeng, J Chen, Y Zhang, Z F Pitafi, H Yang, Q Lu, X Zhang, B G Phillips, <strong><em>F Dou</em></strong>, W Song. </span> </li> 115 <li class="mb-2"> <strong>Proximal Federated Learning for Body Mass Index Monitoring using Commodity WiFi.</strong> <span class="badge badge-paper">PICASSO @ MobiCom'24</span><br> <span class="text-muted"> J Li, K Davuluri, K Mottakin, Z Song, <strong><em>F Dou</em></strong>, J Lu. </span> </li> 116 <li class="mb-2"> <strong>Self-Supervised Representation Learning and Temporal-Spectral Feature Fusion for Bed Occupancy Detection.</strong> <span class="badge badge-paper">UbiComp/IMWUT'24</span><br> <span class="text-muted"> Y Song, Z F Pitafi, <strong><em>F Dou</em></strong>, J Sun, X Zhang, B G Phillips, W Song. </span> </li> </ul> <p class="mt-2 mb-0 text-muted small"> * Equal contribution. # Corresponding author. </p> 117 </li> 118 119 <hr class="my-5"> 120 121 122 123 <li class="mb-3"> 124 <h4>ð§ Foundation Models, Representation Learning, and Scientific AI</h4> 125 <p>We investigate modern machine learning methods, including foundation models, contrastive learning, cross-modal understanding, model merging, efficient LLM fine-tuning, representation learning, computer vision, biomedical AI, and scientific machine learning.</p> 126 <p class="mb-2"><strong>Representative publications:</strong></p> 127 <ul class="mb-0"> 128 <li class="mb-2"> <strong>LARV: Data-Free Layer-wise Adaptive Rescaling Veneer for Model Merging.</strong> <span class="badge badge-paper">arXiv'26</span><br> <span class="text-muted"> X Wang, K Deng, <strong><em>F Dou</em></strong>, J Bi, J Lu. </span> </li> 129 <li class="mb-2"> <strong>SIACL: Structure-Invariant Autoregressive Contrastive Learning for Generative Chemical Language Models via Isomorphic Trajectory Alignment.</strong> <span class="badge badge-paper">arXiv'26</span><br> <span class="text-muted"> X Wang, <strong><em>F Dou</em></strong>, J Bi, M Song. </span> </li> 130 <li class="mb-2"> <strong>Achieving Fine-grained Cross-modal Understanding through Brain-inspired Hierarchical Representation Learning.</strong> <span class="badge badge-paper">arXiv'26</span><br> <span class="text-muted"> <u>W You</u>, H Jiang, Y Pan, J Chen, T Liu, <strong><em>F Dou</em></strong>#. </span> </li> 131 <li class="mb-2"> <strong>HELENE: Hessian Layer-wise Clipping and Gradient Annealing for Accelerating Fine-tuning LLM with Zeroth-order Optimization.</strong> <span class="badge badge-paper">EMNLP'25</span><br> <span class="text-muted"> H Zhao*, J Li*, Y Pan, S Liang, X Yang, <strong><em>F Dou</em></strong>, T Liu, J Lu. </span> </li> 132 <li class="mb-2"> <strong>LOCAL: Latent Orthonormal Contrastive Learning for Paired Image Classification.</strong> <span class="badge badge-paper">ICCV Findings'25 Oral</span><br> <span class="text-muted"> <strong><em>F Dou</em></strong>, J Lu, T Zhu, J Bi. </span> </li> 133 <li class="mb-2"> <strong>Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM.</strong> <span class="badge badge-paper">NeurIPS'23</span><br> <span class="text-muted"> Z Parsons, <strong><em>F Dou</em></strong>, H Du, Z Song, J Lu. </span> </li> 134 <li class="mb-2"> <strong>Polyhedron Attention Module: Learning Adaptive-order Interactions.</strong> <span class="badge badge-paper">NeurIPS'23</span><br> <span class="text-muted"> T Zhu, <strong><em>F Dou</em></strong>, X Wang, J Lu, J Bi. </span> </li> 135 <li class="mb-2"> <strong>Customized Positional Encoding to Combine Static and Time-varying Data in Robust Representation Learning for Crop Yield Prediction.</strong> <span class="badge badge-paper">IJCAI'23</span><br> <span class="text-muted"> Q Liu, <strong><em>F Dou</em></strong>, M Yang, E Amdework, G Wang, J Bi. </span> </li> 136 </ul> 137 </li> 138 139 <hr class="my-5"> 140 141 142 143 144 <li class="mb-3"> 145 <h4>âï¸ Distributed, Federated, and Adaptive Machine Learning</h4> 146 <p>We design learning and optimization methods for decentralized, heterogeneous, infrastru
146cture-less, and resource-constrained environments. Our work addresses federated learning, personalized optimization, federated reinforcement learning, and adaptive decision-making for networked and sensing systems.</p> 147 <p class="mb-2"><strong>Representative publications:</strong></p> 148 <ul class="mb-0"> 149 <li class="mb-2"> <strong>Deep Q-Learning-Based Mobile Charger Path Planning in Wireless Powered Communication Networks.</strong> <span class="badge badge-paper">TECS'25</span><br> <span class="text-muted"> M Mondal, <strong><em>F Dou</em></strong>, J Bi, S Han. </span> </li> 150 <li class="mb-2"> <strong>Proximal Federated Learning for Body Mass Index Monitoring using Commodity WiFi.</strong> <span class="badge badge-paper">PICASSO @ MobiCom'24</span><br> <span class="text-muted"> J Li, K Davuluri, K Mottakin, Z Song, <strong><em>F Dou</em></strong>, J Lu. </span> </li> 151 <li class="mb-2"> <strong>Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM.</strong> <span class="badge badge-paper">NeurIPS'23</span><br> <span class="text-muted"> Z Parsons, <strong><em>F Dou</em></strong>, H Du, Z Song, J Lu. </span> </li> 152 <li class="mb-2"> <strong>On-Device Indoor Positioning: A Federated Reinforcement Learning Approach With Heterogeneous Devices.</strong> <span class="badge badge-paper">IoT-J'23</span><br> <span class="text-muted"> <strong><em>F Dou</em></strong>, J Lu, T Zhu, J Bi. </span> </li> 153 </ul> 154 </li> 155 156 <hr class="my-5"> 157 158 159 <li class="mb-3"> 160 <h4>ð§© Self-Supervised and Contrastive Representation Learning: Methods and Applications</h4> 161 <p> 162 We develop methods in contrastive and self-supervised representation learning, with an emphasis on latent-space geometry, cross-view alignment, structure-aware invariance, and robust generalization. 163 </p> 164 165 166 167 <p class="mb-2"><strong>Representative publications:</strong></p> 168 169 <ul class="mb-0"> 170 171 <li class="mb-2"> 172 <strong>LOCAL: Latent Orthonormal Contrastive Learning for Paired Image Classification.</strong> 173 <span class="badge badge-paper">ICCV Findings'25 Oral</span><br> 174 <span class="text-muted"> 175 <strong><em>F Dou</em></strong>, J Lu, T Zhu, J Bi. 176 </span> 177 </li> 178 179 <li class="mb-2"> 180 <strong>SIACL: Structure-Invariant Autoregressive Contrastive Learning for Generative Chemical Language Models via Isomorphic Trajectory Alignment.</strong> 181 <span class="badge badge-paper">arXiv'26</span><br> 182 <span class="text-muted"> 183 X Wang, <strong><em>F Dou</em></strong>, J Bi, M Song. 184 </span> 185 </li> 186 187 <li class="mb-2"> 188 <strong>CARE: Contrastive Alignment for ADL Recognition from Event-Triggered Sensor Streams.</strong> 189 <span class="badge badge-paper">PerCom'26</span><br> 190 <span class="text-muted"> 191 <u>J Zhao</u>, <u>Z Liu</u>, <u>R Fang</u>, J Lu, L Zhang, 192 <strong><em>F Dou</em></strong>#. 193 </span> 194 </li> 195 196 <li class="mb-2"> 197 <strong>Attention Feature Fusion with Cluster Contrastive Learning for Snoring and Breath-Holding Detection Using Seismic Sensing.</strong> 198 <span class="badge badge-paper">PerCom'26</span><br> 199 <span class="text-muted"> 200 Y Song*, J Chen*, Z Zeng, Y Zhang, Z F Pitafi, X Zhang, 201 <strong><em>F Dou</em></strong>, W Song. 202 </span> 203 </li> 204 205 206 207 <li class="mb-2"> 208 <strong>Cross-Modal Translation and Alignment of Sensor Events for Layout-Aware Activity Modeling.</strong> 209 <span class="badge badge-paper">ISWC'25</span><br> 210 <span class="text-muted"> 211 <u>W You</u>, <u>Z Liu</u>, <strong><em>F Dou</em></strong>#. 212 </span> 213 </li> 214 215 <li class="mb-2"> 216 <strong>Multi-granularity Supervised Contrastive Learning with Online Adaptation for Contactless In-bed Posture Classification.</strong>
217 <span class="badge badge-paper">UbiComp/IMWUT'25</span><br> 218 <span class="text-muted"> 219 Y Song*, H Xiang*, Z Zeng, J Chen, Y Zhang, Z F Pitafi, H Yang, 220 Q Lu, X Zhang, B G Phillips, <strong><em>F Dou</em></strong>, W Song. 221 </span> 222 </li> 223 224 225 226 <li class="mb-2"> 227 <strong>Self-Supervised Representation Learning and Temporal-Spectral Feature Fusion for Bed Occupancy Detection.</strong> 228 <span class="badge badge-paper">UbiComp/IMWUT'24</span><br> 229 <span class="text-muted"> 230 Y Song, Z F Pitafi, <strong><em>F Dou</em></strong>, J Sun, 231 X Zhang, B G Phillips, W Song. 232 </span> 233 </li> 234 </ul> 235 236 <p class="mt-2 mb-0 text-muted small"> 237 * Equal contribution. # Corresponding author. 238 </p> 239 </li> 240 241 <hr class="my-5"> 242 243 244 245 <li class="mb-3"> 246 <h4>ð Earlier Work in Underwater Sensing and Networking Systems</h4> 247 <p>Our earlier work focused on underwater wireless sensor networks, including secure localization, underwater acoustic communication, MAC protocols, network simulation, and sensing/communication in challenging environments.</p> 248 <p class="mb-2"><strong>Representative publications:</strong></p> 249 <ul class="mb-0"> 250 <li class="mb-2"> <strong>Secure Localization for Underwater Wireless Sensor Networks via AUV Cooperative Beamforming with Reinforcement Learning.</strong> <span class="badge badge-paper">TMC'24</span><br> <span class="text-muted"> R Fan, A Boukerche, P Pan, Z Jin, Y Su, <strong><em>F Dou</em></strong>. </span> </li> 251 <li class="mb-2"> <strong>A Secure Localization Scheme for UWSNs Based on AUV Formation Cooperative Beamforming.</strong> <span class="badge badge-paper">ICC'24</span><br> <span class="text-muted"> R Fan, P Pan, Z Jin, Y Su, <strong><em>F Dou</em></strong>. </span> </li> 252 <li class="mb-2"> <strong>A Secure Communication Scheme Based on Spatio-Temporal Dynamics of Underwater Acoustic Channel.</strong> <span class="badge badge-paper">ICC'24</span><br> <span class="text-muted"> Y Su, P Pan, R Fan, S Yang, <strong><em>F Dou</em></strong>. </span> </li> 253 <li class="mb-2"> <strong>Aqua-Sim Next Generation: A NS-3 Based Simulator for Underwater Sensor Networks.</strong> <span class="badge badge-paper">WUWNet'15</span><br> <span class="text-muted"> R Martin, Y Zhu, L Pu, <strong><em>F Dou</em></strong>, Z Peng, J-H Cui, S Rajasekaran. </span> </li> 254 <li class="mb-2"> <strong>On-Demand Pipelined MAC for Multi-Hop Underwater Wireless Sensor Networks.</strong> <span class="badge badge-paper">WUWNet'15</span><br> <span class="text-muted"> <strong><em>F Dou</em></strong>, Z Peng. </span> </li> 255 <li class="mb-2"> <strong>The Multi-Channel MAC Protocol for High-Performance Underwater Sensor Networks.</strong> <span class="text-muted small">(in Chinese)</span> <span class="badge badge-paper">JHEU'15</span><br> <span class="text-muted"> Y Su, Z Jin, <strong><em>F Dou</em></strong>. </span> </li> 256 <li class="mb-2"> <strong>Motion Prediction Based MAC for Underwater Wireless Sensor Networks.</strong> <span class="text-muted small">(in Chinese)</span> <span class="badge badge-paper">JEIT'13</span><br> <span class="text-muted"> Z Jin, Y Su, Z Liu, <strong><em>F Dou</em></strong>#. </span> </li> 257 <li class="mb-2"> <strong>WSF-MAC: A Weight-Based Spatially Fair MAC Protocol for Underwater Sensor Networks.</strong> <span class="badge badge-paper">CECNet'12</span><br> <span class="text-muted"> <strong><em>F Dou</em></strong>, Z Jin, Y Su, J Liu. </span> </li> 258 <li class="mb-2"> <strong>Nodes Distribution Method Aiming at Improving the Fairness for Underwater Acoustic 3D Sensor Networks.</strong> <span class="badge badge-paper">Patent</span><br> <span class="text-muted"> Z Jin, Z Liu, <strong><em>F Dou</em></strong>. CN103095382B. </span> </li> 259 <li class="mb-2"> <strong>Spatially Fair Media Access Control Method for Underwater Sensor Networks.</strong> <span class="badge badge-paper">Patent</span><br> <span class="text-muted"> Z Jin, <strong><em>F Dou</em></strong>, Y Su. CN102612091B. </span> </li> 260 </ul> 261 </li> 262 263 264 265 </ul> 266</div> 267 268 </div> 269 <footer class="footer"> 270 <div class="container-lg"> 271 <div class="row my-3"> 272 <div class="col-6"> 273 <div class="text-muted"> 274 <i>Last updated: Oct 2026</i> 275 </div> 276 </div> 277 <div class="col-6"> 278 <div class="text-right text-muted"> 279 <a href="https://github.com/luost26/academic-homepage" target="_blank"><i class="fas fa-pencil-ruler"></i> academic-homepage</a> 280 </div> 281 </div> 282 </div> 283 </div> 284</footer> 285 286 287 <!-- Scripts --> 288
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Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.