News
January 2024: We are happy to publish the dataset of human airway measurements, produced by our integrated AI and sensing systems for smart pulmonary telemedicine, namely Acoustic Waveform Respiratory Evaluation (AWARE). This dataset contains airway measurements of 382 human subjects, including patients with various pulmonary diseases and healthy control subjects, recruited from the Children's Hospital of Pittsburgh during the past 3 years. The contents of the dataset include raw WAV files from acoustic sensing, segmented and aligned acoustic signal pulses, and processed measurements of airway cross-sectional areas. More details can be found in dataset page and source codes of using the dataset can be found here. To our best knowledge, this is the first public dataset of human airway measurements with pulmonary diseases, and we welcome any feedback from the smart health research community.
January 2024: Our paper, Towards Green AI in Fine-Tuning Large Language Models via Adaptive Backpropagation, has been accepted for publication at the 2024 International Conference on Learning Representations (ICLR). It focuses on computationally efficient LLM fine-tuning, and reduces the FLOPs of LLM fine-tuning by 30% and improves the model accuracy by 4%, compared to LoRA. Check our preprint here.
December 2023: The preprint of our recent work on runtime modality adaptation for embodied AI has been made publicly available on arXiv. This is the first work that allows multimodal LLMs to elastically switch between input data modalities at runtime, for embodied AI applications such as autonomous navigation. Our basic technical approach is to use fully trainable projectors to adaptively connect the unimodal data encoders being used to a flexible set of last LLM blocks. In this way, we can flexibly adjust the amount of LLM blocks being connected to balance between accuracy of runtime fine-tuning cost, and optimize the efficiency of cross-modal interaction by controlling the amount of information being injected in each connection. Our implementations on NVidia Jetson AGX Orin demonstrate short modality adaptation delays of few minutes with mainstream LLMs, 3.7x fine-tuning FLOPs reduction, and 4% accuracy improvements on multimodal QA tasks. Check the source codes of our work here.
October 2023: Since 2020, our integrated AI and sensing systems for smart pulmonary telemedicine, namely PTEase, have been applied to and tested on more than 400 patients with various pulmonary diseases at the Children's Hospital of Pittsburgh, for remote disease diagnosis, evaluation and management, and have particularly helped families in various minority groups with limited access to healthcare. Please see the table for demographics of involved human subjects. By applying on-device AI models and ML algorithms on patient data collected on smartphones, we can achieve 75% accuracy on diagnosing pulmonary diseases in diverse patient groups and 11%-15% errors in estimating lung function indices. Check our recent paper for details. Currently, we are in ongoing processes of commercializing these techniques and clinical studies at larger populations, by applying for FDA 510(k) clearances on medical device use and licensing our techniques to both US and international companies. Check this website for latest news and this page for more details on our research of integrated AI and sensing systems for smart health.
September 2023: Two preprints of our recent works on on-device AI have been made publicly available on arXiv. The first work, Towards Green AI in Fine-Tuning Large Language Models via Adaptive Backpropagation, extends our prior work of ElasticTrainer (published at ACM MobiSys 2023) to Large Language Models (LLMs) and facilitates computationally efficient LLM fine-tuning towards green AI. It can reduce the fine-tuning FLOPs by extra 30% compared to existing techniques such as LoRA, without noticeable accuracy loss. With the same amount of FLOPs reduction, it can provide 4% model accuracy improvement compared to LoRA. The second work, Tackling the Unlimited Staleness in Federated Learning with Intertwined Data and Device Heterogeneities, targets a FL problem motivated by practical system settings, where data samples in certain classes or with particular features may only be produced from some slow clients. Our work leverages gradient inversion to move the staleness of model updates from these slow clients, and can improve the trained model accuracy by 20% and speed up the training progress by 35%, compared to existing techniques in asynchronous FL. The source codes have been publicly available at the Pitt ISL webpage.
April 2023: Our paper, ElasticTrainer: Speeding Up On-Device Training with Runtime Elastic Tensor Selection, has been accepted for publication at the 2023 ACM Conference on Mobile Systems, Applications, and Services (MobiSys). This paper presents the first on-device AI technique that achieves full elasticity of on-device training on resource-constrained mobile and embedded devices. By leveraging the principle of eXplainable AI (XAI) and evaluating the importance of different tensors in training, we allow fully flexible adaptation of the trainable neural network portion at runtime, according to the current training needs and online data patterns, to minimize the training cost without accuracy loss.
April 2023: Our paper, PTEase: Objective Airway Examination for Pulmonary Telemedicine using Commodity Smartphones, has been accepted for publication at the 2023 ACM Conference on Mobile Systems, Applications, and Services (MobiSys). This is the first mobile health system that turns a commodity smartphone into a fully functional pulmonary examination device to measure the internal physiological conditions of human airways, such as airway caliber, obstruction and possible inflammation. Information about these airway conditions could provide vital clues for precise and objective pulmonary disease evaluation.
Oct 2022: Our paper, AiFi: AI-Enabled WiFi Interference Cancellation with Commodity PHY-Layer Information, has been accepted for publication at the 2022 ACM Conference on Embedded Networked Sensor Systems (SenSys). This is the first work that applies on-device AI techniques to interference cancellation in WiFi networks and enables generalizable interference cancellation on commodity WiFi devices without any extra RF hardware. By using neural network models to mimic WiFi network's PHY-layer operation, AiFi can be generally applied to different types of interference signals ranging from concurrent WiFi transmissions, ZigBee/Bluetooth to wireless baby monitors or even microwave oven, and improves the MAC-layer frame reception rate by 18x.
Aug 2022: Our paper, AgileNN: Real-Time Neural Network Inference on Extremely Weak Devices: Agile Offloading with Explainable AI, has been accepted for publication at the 2022 ACM Int'l Conference on Mobile Computing and Networking (MobiCom). This is the first work that achieves real-time inference (<20ms) of mainstream neural network models (e.g., ImageNet) on extremely weak MCUs (e.g., STM32 series with <1MB of memory), without impairing the inference accuracy. The usage of eXplainable AI (XAI) techniques allows >6x improvement of feature compressibility during offloading and >8x reduction of the local device's resource consumption!
May 2022: Our paper, TransFi: Emulating Custom Wireless Physical Layer from Commodity WiFi, has been accepted for publication at the 2022 ACM Int'l Conference on Mobile Systems, Applications and Services (MobiSys). This is the first work that realizes fine-grained signal emulation and allows commodity WiFi devices to emulate custom wireless physical layer, including but not limited to, custom PHY-layer preambles and new ways of agile spectrum usage. It could also improve the performance of cross-technology communication and many other wireless applications by up to 50x, enabling high-speed data communication on par with commodity WiFi! Watch the teaser video here for details.
January 2022: Our paper, RAScatter: Achieving Energy-Efficient Backscatter Readers via AI-Assisted Power Adaptation, has been accepted for publication at the 2022 ACM/IEEE Conference on Internet of Things Design and Implementation (IoTDI).
January 2022: Our paper, FaceListener: Recognizing Human Facial Expressions via Acoustic Sensing on Commodity Smartphones, has been accepted for publication at the 2022 ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).
November 2021: Our paper, Eavesdropping User Credentials via GPU Side Channels on Smartphones, has been accepted for publication at the 2022 ACM Int'l Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS). This is one of the few works that demonstrate critical security vulnerabilities of mainstream GPUs (QualComm Adreno GPU on Snapdragon SoCs) on smartphones, which allow an unprivileged attacker to eavesdrop the user's sensitive credentials such as app username and password. This attack has been acknowledged by Google and has been incorporated by Google in its future Android security updates. Check our demo video here!
September 2021: I will be serving as the Demo Co-chair of IPSN 2022, part of the CPS-IoT Week 2022 being held in Milan, Italy, May 2022. Please consider submitting your work! The submission deadline will be in March 2022.
March 2021: Our paper, MyoMonitor: Evaluating Muscle Fatigue with Commodity Smartphones, have been published at the Elsevier Smart Health Journal. This is the first work that uses commodity smartphones to evaluate humans' muscle conditions. This is collaborative work with UPMC and Department of Orthopaedic Surgery at Pitt School of Medicine.
August 2020:Our paper, SpiroSonic: Monitoring Human Lung Function via Acoustic Sensing on Commodity Smartphones, has been accepted for publication at the 2020 International Conference on Mobile Computing and Networking (MobiCom). This is the first work that allows commodity smartphones to be used as a portable spirometer and provide accuracy lung function test results on par with clinical-grade spirometers. This is a collaborative work with the Children's Hospital of Pittsburgh, and could also potentially contribute to in-home evaluation of COVID-19 risks by allowing convenient out-of-clinic lung function evaluation. Watch our presentation video here for details.
May 2020: We have been exploiting the power of modern mobile computing technologies to fight again COVID-19. Our new project of using commodity smartphones for early-stage COVID-19 diagnosis has been funded by NSF, and was reported by several news media internationally. [WGN TV, Daily Mail, News Medical, Medical Express, Pittsburgh Post-Gazette]
March 2020: Our paper, MagHacker: Eavesdropping on Stylus Pen Writing via Magnetic Sensing from Commodity Mobile Devices, has been accepted for publication at the 2020 ACM International Conference on Mobile Systems, Applications and Services (MobiSys).
December 2019: Our paper, StarLego: Enabling Custom Physical-Layer Wireless over Commodity Devices, has been accepted for publication at the 2020 International Workshop on Mobile Computing Systems and Applications (HotMobile).
September 2019: Our paper, EasyPass: Combating IoT Delay with Multiple Access Wireless Side Channels, has been accepted for publication at the 2019 Int'l Conference on emerging Networking EXperiments and Technologies (CoNEXT), and received the Best Paper Award at the conference.
August 2019: I am invited to serve on the TPC of HotMobile 2020.
January 2019: Our paper, DeltaVR: Achieving High-Performance Mobile VR Dynamics through Pixel Reuse, has been accepted for publication at the 2019 International Conference on Information Processing in Sensor Networks (IPSN), and will be presented during the CPSWeek 2019.
December 2018: Our paper, The Computing Landscape of the 21 Century, a collaborative work with Mahadev Satyanarayanan and Brandon Lucia at Carnegie Mellon University, has been accepted for publication at the 2019 International Workshop on Mobile Computing Systems and Applications (HotMobile). This paper envisions the evolvement of computing systems in the future decades. Check it here.
November 2018: Our paper, Enabling Cross-Technology Coexistence for Extremely Weak Wireless Devices, has been accepted for publication at the 2019 IEEE Conference on Computer Communications (INFOCOM).
August 2018: Our paper, Reducing Event Latency and Power Consumption in Mobile Devices by Using a Kernel-Level Display Server, has been accepted for publication at IEEE Transactions on Mobile Computing.
July 2018: Our paper, MUVR: Supporting Multi-User Mobile Virtual Reality with Resource Constrained Edge Cloud, has been accepted for publication at the 3rd ACM/IEEE Symposium on Edge Computing (SEC).
March 2018: I received a new NSF research grant on studying the usage of E-Bikes and its impact on environmental sustainability. Check here for more details.
January 2018: Our paper, Continuous WIreless Link Rates for Internet of Things, has been accepted for publication at the 2018 International Conference on Information Processing in Sensor Networks (IPSN), and will be presented during the CPSWeek 2018.
September 2017: I officially started working at University of Pittsburgh as an Associate Professor.
April 2017: I am one of the four recipients of the University of Tennessee's highest honor to junior faculty - the Chancellor's Award for Professional Promise in Research and Creative Achievement.
November 2016: Our paper, Interconnecting Heterogeneous Devices in the Personal Mobile Cloud, has been accepted for publication at the 2017 IEEE Conference on Computer Communications (INFOCOM).
October 2016: I received a new NSF research grant on reducing the mobile devices' power consumption on graphical user interface. Check here for more details.
July 2016: Our paper, Scheduling Dynamic Wireless Networks with Limited Operations, has been accepted for publication at the 24th IEEE International Conference on Network Protocols (ICNP), 2016.
June 2016: Our paper, Minimizing Context Migration in Mobile Code Offload, has been accepted for publication by IEEE Transactions on Mobile Computing.
April 2016: Our paper, Supporting Real-Time Wireless Traffic through a High-Throughput Side Channel, has been accepted for publication at the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 2016.
March 2016: I won the prestigious NSF CAREER Award with the topic of "Interconnected Mobile Computing in Wireless Networks". Check the project summary here.
February 2016: Our paper, Accurate Power Quality Monitoring in Microgrids, has been accepted for publication at the 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), 2016.
November 2015: Two papers have been accepted for publication at the 2016 IEEE Conference on Computer Communications (INFOCOM).
September 2015: New research projects on tactical mobile networking, mobile cloud computing, and edge cloud networks have started. Check the related project webpages for more details.
August 2015: Our paper, Energy-Efficient Computation Offloading in Cellular Networks, has been accepted for publication at the 23rd IEEE International Conference on Network Protocols (ICNP), 2015.
May 2015: Two papers have been accepted to IEEE Transactions on Mobile Computing. Check here.
May 2015: I visited several top Chinese universities this summer including Tsinghua University, Nanjing University and Wuhan University, and presented our research on mobile cloud computing.
April 2015: Two papers have been accepted to IEEE Transactions on Mobile Computing. Check here.
April 2015: I gave an invited talk at the Department of Electrical and Computer Engineering of Virginia Tech. The talk topic is "Exploiting System Dynamics in Mobile Cloud Computing".
March 2015: Our paper, A Computation Offloading Framework For Soft Real-time Embedded Systems, has been accepted for publication at the 2015 Euromicro Conference on Real-Time Systems (ECRTS).
February 2015: I will serve as the Symposium Chair of Cloud Computing and Big Data track of the Int'l Conference on Computing, Networking and Communications (ICNC), 2016. Consider submitting your work by July 5, 2015.
November 2014: Our paper, Code Offload with Least Context Migration in the Mobile Cloud, has ben accepted for publication at IEEE INFOCOM, 2015.
August 2014: Our paper, Rebuilding the Tower of Babel: Towards Cross-System Malware Information Sharing, has been accepted for publication at the 2014 ACM International Conference on Information and Knowledge Management (CIKM).
July 2014: Our paper, Power Grid Frequency Monitoring Over Mobile Platforms, has been accepted for publication at the 2014 IEEE International Conference on Smart Grid Communications (SmartGridComm).
June 2014: Our paper, On Exploiting Dynamic Execution Patterns for Workload Offloading in Mobile Cloud Applications, has been accepted for publication at the 2014 IEEE International Conference on Network Protocols (ICNP).
June 2014: Two papers have been accepted for publication at the 2014 Military Communication Conference (MILCOM).
May 2014: The journal version of our INFOCOM 2014 paper, Forwarding Redundancy in Opportunistic Mobile Networks: Investigation, Elimination, and Exploitation, has been accepted to the IEEE Transactions on Mobile Computing.
Nov 2013: Two papers have been accepted for publication at IEEE INFOCOM, 2014.
Feb 2013: Our paper, On Exploiting Transient Social Contact Patterns for Data Forwarding in Delay Tolerant Networks, has been spotlighted in the January issue of the IEEE Transactions on Mobile Computing.
Jan 2013: Our paper, Coopeartive Caching for Efficient Data Access in Disruption Tolerant Networks, has been accepted to the IEEE Transactions on Mobile Computing.
Dec 2012: Our paper, An Incentive Framework for Cellular Traffic Offloading, has been accepted to the IEEE Transactions on Mobile Computing.
Nov 2012: Our paper, Wakeup Scheduling for Energy-Efficient Communication in Opportunistic Mobile Networks, has been accepted for publication at IEEE INFOCOM, 2013.