Petrolo, Y. Lin, and E. Knightly, “ASTRO: Autonomous, Sensing, and Tetherless netwoRked drOnes,” in Proceedings of ACM DroNet 2018, Munich, Germany, June 2018.
Boubrima and E. Knightly, “Robust Mission Planning of UAV Networks for Environmental Sensing,” to appear in Proceedings of ACM DroNet 2020, June 2020.
Zhambyl Shaikhanov, “Fine-Time-Measurement to Approach, Localize, and Track RF Targets via Drone Networks.” MS Thesis, March 2020.
Sampaolo, S. Csutak, P. Patimisco, M. Giglio, G. Menduni, V. Passaro, F.K. Tittel, M. Deffenbaugh, V. Spagnolo, “Methane, ethane and propane detection using a compact quartz enhanced photoacoustic sensors and a single interband cascade laser”, Sens. Act. B Chem. 282, 952-960 (2019).
Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019).
Elefante, M. Giglio, A. Sampaolo, G. Menduni, P. Patimisco, V. M.N. Passaro, H. Wu, H. Rossmadl, V. Mackowiak, A. Cable, F.K. Tittel, L. Dong and V. Spagnolo, “Dual-Gas Quartz-Enhanced Photoacoustic Sensor for Simultaneous Detection of Methane/Nitrous Oxide and Water Vapor”, Anal. Chem. 91, 12866-12873 (2019).
Giglio, A. Elefante, P. Patimisco, A. Sampaolo, F. Sgobba, H. Rossmadl, V. Mackowiak, H. Wu, F.K. Tittel, L. Dong, V. Spagnolo, “Quartz-enhanced photoacoustic sensor for ethylene detection implementing optimized custom tuning fork-based spectrophone”, Optics Express 27, 4271-4280 (2019).
Sgobba, G. Menduni , S. Dello Russo, A. Sampaolo, P. Patimisco, M. Giglio, E. Ranieri, V.M.N. Passaro, F.K. Tittel and V. Spagnolo, “Quartz-Enhanced Photoacoustic Detection of Ethane in the Near-IR Exploiting a Highly Performant Spectrophone”, Appl. Sci. 10, 2447 (2020).
Giglio, A. Zifarelli, A. Sampaolo, G. Menduni, A. Elefante, R. Blanchard, C. Pfluegl, M.F. Witinski, D. Vakhshoori, H. Wu, V.M.N. Passaro, P. Patimisco, F.K. Tittel, L. Dong, V. Spagnolo, “Broadband detection of methane and nitrous oxide using a distributed feedback quantum cascade laser array and quartz-enhanced photoacoustic sensing”, Photoacoustics 17, 100159 (2020).
A. Sampaolo, S. Csutak, P. Patimisco, M. Giglio, G. Menduni, V. Passaro, F.K. Tittel, M. Deffenbaugh, V. Spagnolo, “Methane, ethane and propane detection using a compact quartz enhanced photoacoustic sensors and a single interband cascade laser”, Sens. Act. B Chem. 282, 952-960 (2019)
Shaikhanov, A. Boubrima, and E. Knightly, “Autonomous Drone Networks for Sensing, Localizing and Approaching RF Targets,” in Proceedings of IEEE Vehicular Networking Conference (VNC), December 2020.
Fu, Yonggan; Guo, Han; Li, Meng; Yang, Xin; Ding, Yining; Chandra, Vikas; and Lin, Yingyan, “CPT: Efficient Deep Neural Network Training via Cyclic Precision,” In proceedings International Conference on Learning Representations (ICLR 2021), (Spotlight paper: ~ Top 3%).
Petrolo, Z. Shaikhanov, Y. Lin, and E. Knightly, “ASTRO: a System for Off-Grid Networked Drone Sensing Missions”, ACM Transactions on Internet of Things (in press).
Boubrima and E. Knightly, “Robust Environmental Sensing using UAVs”, ACM Transactions on Internet of Things (in press).
Cheng Wan, Youjie Li, Ang Li, Nam Sung Kim, and Yingyan Lin, “BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling”, Fifth Conference on Machine Learning and Systems (MLSys 2022)
Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, and Yingyan Lin, “PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication”, The Tenth International Conference on Learning Representations (ICLR 2022) arXiv:2203.10428v1
Haoran You, Tong Geng, Yongan Zhang, Ang Li, and Yingyan Lin, “GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design”, 28th IEEE International Symposium on High-Performance Computer Architecture (HPCA 2022) arXiv:2112.11594v2
Zhambyl Shaikhanov, Ahmed Boubrima, and Edward W. Knightly. “FALCON: a Networked Drone System for Sensing, Localizing, and Approaching RF targets.” IEEE Internet of Things Journal (IEEE IoT 2022) DOI 10.1109/JIOT.2022.3152380
Data Set – The team expects to continue to generate more data sets in order to better describe baseline BTEX air pollution levels.
Z. Shaikhanov, S. Badran, J. Jornet, D. Mittleman, and E. Knightly, “Remotely Positioned MetaSurface-Drone Attack,” in Proceedings of ACM HotMobile, February 2023. (BEST DEMO AWARD).
T. Rice, D. Pandey, D. Ramirez, and E. Knightly, “Experimental Evaluation of AoA Estimation for UAV to Massive MIMO,” in Proceedings of IEEE MILCOM 2023.
Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Cheng Wan, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin, “DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks”, Thirty-ninth International Conference on Machine Learning (ICML 2022).
Haoran You, Baopu Li, Zhanyi Sun, Xu Ouyang, Yingyan Lin, “SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning”, The 2022 European Conference on Computer Vision (ECCV 2022) 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XI.