Publications – ASTRO

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 X.
Boubrima and E. Knightly, “Robust Environmental Sensing using UAVs”, ACM Transactions on Internet of Things (in press).
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).
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%).
A. Boubrima and E. Knightly – “Robust Mission Planning of UAV Networks for Environmental Sensing” – In Proc. of ACM MobiSys – DroNet workshop, June 2020. Best Paper Award.
R. Petrolo, Y. Lin, and E. Knightly – “ASTRO: Autonomous, Sensing, and Tetherless netwoRked drOnes” – In Proc. of ACM MobiSys – DroNet workshop, June 2018.
Zhambyl Shaikhanov, “Fine-Time-Measurement to Approach, Localize, and Track RF Targets via Drone Networks.” MS Thesis, March 2020.
Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Atlas Wang, and Yingyan Lin, “E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings,” Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019).
F. 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).
M. 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).
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).
M. 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).
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).