Zhenzhou (Tom) Qi
Ph.D. Student at Duke University
Duke University
Biography
Tom (戚振周) is a forth-year Ph.D. candidate in department of Electrical and Computer Engineering at Duke University advised by Professor Tingjun Chen. Tom’s research interests include vRAN; Heterogeneous Computing; Wireless networks with a focus on 5G, millimeter-wave communications, massive MIMO, and edge cloud computing; Computer Networks. He works in the Duke FuNCtions Lab, which works on next-generation wireless networks and systems.
Download my resumé.
Interests
- vRAN
- Heterogeneous Computing
- Wireless Network
- Computer Network
Education
-
PhD in Electrical and Computer Engineering, Present
Duke University
-
MEng in Electrical and Computer Engineering, 2021
Cornell University
-
BSc in Electrical and Computer Engineering, 2020
Rutgers University
Honors & Awards
Duke Graduate School Conference Travel Award
Duke ECE Conference Travel Fellowship
MWW-2023 Travel Grant
ACM SIGMOBILE Student Community Grant
ACM SIGMOBILE Student Community Grant
Class of 2020 graduation with highest honor (Summa Cum Laude)
Top 5% in ECE
School of Engineering, ECE Capstone Design
Dean’s List
Fall & Spring 2016 - 2020
Math Honor Session
Calc II & Multi Calc
Academic Experience
Teaching Assistant - ECE655L
Duke University
- Teaching Assistant for Full Stack IoT Systems
Teaching Assistant - ECE556
Duke University
- Teaching Assistant for Wireless Networking and Mobile Computing
Research Assistant
Duke University
- Facilitating Open-Access Millimeter-wave and Massive MIMO Research in the COSMOS and ORBIT Testbeds
- Spectrum Sensing & Management for CBRS
Research Assistant
Cornell University
Front-end and back-end development for multiple sclerosis lesion segmentation (MulS) challenge
Research Assistant
Rutgers University
- Investigating the Biological Impacts of Radio Spectrum Transmissions
- Smart Sweet Spot of Your Home Stereos
- Low-Power, Low-Latency, IoT Communications Systems Coexistence with C-RAN
Professional Experience
Wireless R&D RF SYS Internship
Qualcomm
- RF SYS Team
- Performed detailed profiling for software and hardware mmWave Radar processing pipeline. Optimized the software DSP stage by 500 times and the FW processing by 2 times.
- Built real‑time visualization for Range Doppler Information for mmWave Radars
- Built dataset collection pipeline and constructed gesture dataset for mmWave Radars
- Built static and real‑time Deep‑Learning based gesture recognition model for mmWave radars
- Integrate the real‑time Deep‑Learning gesture recognition model to volume control applications for users to interact with the phone.
Engineering Ambassador
School of Engineering, Rutgers University
- Provide campus tours, sit on student panels, participate in Engagement events
- Serve as a representative to share the mission and vision
Learning Assistant (Physics IIA Lab & Recitation)
Learning Center at Rutgers University
- Practice communications skills and leadership skills
- Address students’ problems and grade pre-recitation exercises
Treasurer
Society of Asian Scientists and Engineers (SASE)
- Participate in Professional, cultural events and community services
- Handle budgets of the organization
Professional Service
International Conference on Mechanics, Electronics, Automation and Automatic Control (MEAAC'24, Reviewer)
MEAAC
IEEE International Conference on Parallel and Distributed Systems (ICPADS, TPC member for Wireless Sensing & Mobile Computing Track 2022)
IEEE ICPADS
Projects
*
Publications
(2024).
Demo: Savannah: A Real‑time Programmable mmWave Baseband Processing Framework.
In MobiCom'24 Demo (To appear).
(2024).
Savannah: Efficient mmWave Baseband Processing with Minimal and Heterogeneous Resources.
In MobiCom'24 (To appear).
(2024).
Mambas: Maneuvering Analog Multi-User Beamforming using an Array of Subarrays in mmWave Networks.
In MobiCom'24 (To appear).
(2024).
MadRadar: A Black-Box Physical Layer Attack Framework on mmWave Automotive FMCW Radars.
In NDSS'24.
(2023).
Field Trial of Coexistence and Simultaneous Switching of Real-Time Fiber Sensing and Coherent 400 GbE in a Dense Urban Environment.
In JIT'23.
(2023).
Programmable Millimeter-Wave MIMO Radios with Real-Time Baseband Processing.
In ACM WiNTECH’23.
(2023).
Field Trial of Coexistence and Simultaneous Switching of Real-time Fiber Sensing and 400GbE Supporting DCI and 5G Mobile Services.
In IEEE OFC'23.
(2020).
Investigating the biological impacts of radio transmissions.
In ACM SenSys’20.
(2018).
Low-Power, Low-Latency, IoT Communications Systems Coexistence with C-RAN.
In ACM SenSys’18.
Outside of Work
Contact
- zhenzhou.qi@duke.edu
- 732 322 2498
- 534 Research Dr, Durham, NC 27705
- Floor 4, Room 427