Columbia, South Carolina, United States
I am a computer systems researcher working at the intersection of wireless networking, sensing, mobile systems, and applied machine learning, with a focus on next-generation wireless systems, multimodal sensing, and autonomous systems applications. I am currently a first-year PhD student in Electrical & Computer Engineering at The University of Texas at Austin, where I work in the GENESYS Lab under Prof. Kaushik Chowdhury. My current research focuses on applied machine learning for wireless systems, including deep learning for spectrum sensing, spectrum sharing, RF fingerprinting, cybersecurity, and real-time learning for spectrum access in NextG architectures. I am also interested in multimodal sensor fusion across RF sensors, LiDAR, cameras, and radar for situational assessment, digital twins, and autonomous vehicles, as well as networked robotics for coordinated communication, computation, and control in unmanned autonomous aerial systems. I recently completed my M.S. in Computer Science, specializing in Computing Systems, at Georgia Tech, where I conducted research under Prof. Ashutosh Dhekne in the WiSciTech Lab on ultra-wideband communications, localization, and sensing-driven applications. Prior to Georgia Tech, I completed my B.S. in Computer Science with a minor in Mathematics from the University of South Carolina Honors College, graduating in three years. As an undergraduate researcher, I worked in the SyReX Lab under Prof. Sanjib Sur on NextG/5G mmWave networks, drone-based wireless surveying, machine-learning-driven picocell deployment, and point-cloud reconstruction using drone-based mmWave systems. I also worked in the HeRC Lab under Prof. Jason Bakos on FPGA-based smart sensing and embedded systems. I am an NSF Graduate Research Fellow and Cockrell School of Engineering Graduate Fellow. During Summer 2027 I am seeking PhD research internships in industry research labs, technology companies, and federal organizations. Please reach out. Research interests: Wireless systems, applied machine learning, sensing, networking, embedded systems, autonomous systems, and applied systems research. Learn more about my work at www.rahulbulusu.com/
Teaching Assistant for CS 3251: Computer Networking I, taught by Prof. Ashutosh Dhekne. • Helped students understand core computer networking concepts including TCP/IP, routing, congestion control, MAC protocols, and wireless networking fundamentals. • Held weekly office hours and assisted students with networking assignments, labs, and exam preparation. • Helped grade homework, projects, and exams, and provided detailed technical feedback. • Mentored students on debugging networked systems and understanding protocol-level behavior.
Advisor: Prof. Ashutosh Dhekne • Designed and developed a wireless sensing system using ultra-wideband (UWB) and millimeter-wave (mmWave) technologies to detect ice–water state transitions in packaged food, resulting in a published ACM HotMobile poster, IEEE Sensors Letters paper and a provisional patent application. • Leading the design of a UWB-based lane-level localization and car guidance system to improve positioning accuracy beyond GPS, enabling assisted parking and advanced driver guidance applications. • Investigating novel UWB medium access control mechanisms, including distance-aware and position-based MAC designs (e.g., DDMA), to support scalable sensor–actuator networks. • Developed a practical low-power digital backscatter system for IoT environmental sensing, targeting sub-100 µW operation and long-range deployments. • Conducted system prototyping, experimental evaluation, and real-world testing across wireless sensing and communication platforms.
Teaching Assistant for CS 8803 (Fall 2024 & Fall 2025 semesters): Special Topics – Mobile Computing and IoT, taught by Prof. Ashutosh Dhekne. • Led weekly office hours and mentored 50+ graduate and senior undergraduate students on wireless sensing, localization, GPS, drones, motion tracking, acoustics, and IoT systems. • Assisted with the design, grading, and evaluation of assignments, projects, and exams. • Guided semester-long group projects focused on real-world mobile and IoT applications, integrating sensing, localization, and embedded systems. • Provided technical mentorship on system design, experimental evaluation, and debugging of sensor-driven applications.
Advisor: Prof. Sanjib Sur Conducted research on 5G/NextG/mmWave network deployment and reliability in outdoor environments as part of the SyReX Lab. • Developed and implemented a drone-based control system for autonomous flight operations while synchronizing data capture from onboard sensors and mmWave radios. • Collected large-scale multimodal datasets including visual data, depth information, and mmWave reflections across diverse outdoor environments. • Designed and built a machine learning model to analyze 5G signal propagation, enabling data-driven optimization of picocell placement for improved coverage and reliability. • Investigated outdoor point-cloud reconstruction using drone-mounted millimeter-wave systems, leveraging FMCW radar principles and the CFAR detection algorithm. • Selected as a participant in the National Science Foundation Research Experience for Undergraduates (NSF REU) program during Summer 2022, Fall 2022, and Spring 2023. Awards and Recognition: •Place, Discover USC 2023 •Magellan Scholar •Best Poster Runner-Up, ACM HotMobile 2022
Advisor: Prof. Jason D. Bakos • Conducted a research project focused on FPGA-based smart sensor systems integrating real-time machine learning for online structural state estimation from vibration signals. - Designed and implemented signal-processing and learning pipelines in MATLAB for vibration-based sensing applications. - Developed a standalone forward-pass implementation of LSTM neural networks, enabling inference on resource-constrained embedded platforms. - Explored hardware–software co-design considerations for deploying machine learning models on FPGAs for real-time sensing. - Completed this project in fulfillment of the South Carolina Honors College Beyond the Classroom requirement. • (Internet-of-Things Design – CSCE 317): Prototyped and evaluated two course project ideas for an upcoming Internet-of-Things Design course. Established communication between an ATmega-based application processor and two auxiliary processors controlling an LCD display and WiFi interface. Built a functional weather station that displays sensor data on an attached display and relays the data to network peers. - Learned hardware/software co-design and gained hands-on experience with laboratory bench equipment, including oscilloscopes, logic analyzers, and programmable power supplies. - Worked with SPI, I2C, and UART communication protocols. • Designed, built, and evaluated a system to control temperature inside a computer enclosure using an Arduino Uno microcontroller, temperature sensor, power MOSFET, fan, and 12V power supply. - Programmed a closed-loop proportional–integral–derivative (PID) controller to regulate fan speed using a pulse-width modulated control signal. - Gained hands-on experience in hardware/software co-design and C/C++ programming. - Tested the system in a server enclosure.
Advisor: Prof. Jason O’Kane • Participated in a summer research internship introducing computer science fundamentals and programming in Python. • Designed and implemented three interactive games in Python, applying basic software design and problem-solving concepts. • Gained hands-on experience working in a Linux-based development environment, including navigating the command line and managing files. • Applied Python programming to practical, real-world scenarios through guided projects and exercises. • Collaborated and communicated effectively with students and mentors from diverse academic and technical backgrounds.