Low-Power Wireless Communications & Identification (Going Batteryless)
Team Members: (Left to Right) Christopher Saetia (Mentor), Astin Chang, Abhik Mojumdar, Michael Wallace, Saanvika Chanda, Asmita Malakar
Advisor: Greg Durgin
Radio-frequency identification (RFID) tags are low cost (cents per tag) and are often battery-less, consuming only micro-watts of power. Their simplicity allows them to perform simple tasks, such as providing an ID, well. But their low-cost and low-power design makes this technology attractive solution for scalable and robust wireless and sensing networks. This project will examine the next generation of RFID design to meet the complex needs of these networks. The project research can extend to devising extended use cases of RFID tags for sensing, new ways to characterize and test RFID behavior, or novel designs of these low-power tags and communications.
Team Members: (Left to Right) Ved Priyadarshi, Siddardh Budamagunta, Taehoon Kim, Yho Han Kim, Ada Gurkas, Md. Nahid Haque Shazon (Mentor)
Advisor: Greg Durgin
Radio-frequency identification (RFID) tags are low cost (cents per tag) and are often battery-less, consuming only micro-watts of power. Their simplicity allows them to perform simple tasks, such as providing an ID, well. But their low-cost and low-power design makes this technology attractive solution for scalable and robust wireless and sensing networks. This project will examine the next generation of RFID design to meet the complex needs of these networks. The project research can extend to devising extended use cases of RFID tags for sensing, new ways to characterize and test RFID behavior, or novel designs of these low-power tags and communications.
Towards Energy-efficient and compact
SOT-MRAM
Team Members: (Left to Right) Ved Priyadarshi, Siddardh Budamagunta, Taehoon Kim, Yho Han Kim, Ada Gurkas, Md. Nahid Haque Shazon (Mentor)
Advisor: Azad Naeemi
This project will investigate how applying a descending triangular current pulse influences the switching behavior of two-terminal spin–orbit torque magnetic random-access memory (SOT-MRAM) devices. The primary focus will be on how the required out-of-plane spin Hall angle (ζ_z) changes when using such pulse shapes compared to conventional constant or rectangular pulses. Device-level simulations will be used to quantify improvements or trade-offs in switching time and energy consumption. The study will also explore scaling effects, examining how ζ_z and switching performance vary with device dimensions. By understanding these relationships, the project aims to identify design and operation strategies for more energy-efficient and scalable SOT-MRAM.
Unifying the ASHES Analog Computing Toolflow
Team Members: (Left to Right) Pranav Mathews (Mentor) , Ava Thai, Alexander Feng , Oliver Lee , Maithreyi Bharathi, Joseph Shackelford , Catherine Lacey (Mentor)
Advisor: Jennifer Hasler
Tools have proven to be necessary for practically designing and building large, complex electronic systems. Analog computing has lagged behind the current trend of digital computers largely because analog has no comparable toolflow. Our lab developed ASHES, a toolflow for building analog computing ASICs or programming Field Programmable Analog Arrays (FPAAs). This project involves unifying the user front-end to enable reuse of code between FPAA programming and ASIC generation and unifying the backend of the FPAA flow between ashes (our new version) and the old version.
GT Phone Home: Measuring Starlink NTN and Terrestrial Coexistence
Team Members: (Left to Right) Cameron Matson (Mentor), Ryan Elchahal, Advaith Pillai, Shreya Iyer, Aamir Syed, Mia Villavicencio
Advisor: Karthikeyan Sundaresan
Satellites are envisioned to play a major role in future mobile networks as what is called “Non-Terrestrial Networking”. T-Mobile has just announced the ability to send and recieve text messages via satellite using SpaceX’s Starlink constellation over T-Mobile’s spectrum. In this project we will go out into the field to collect RF and networking measurements using phones, a real Starlink terminal, and Software defined radios. There are many open questions about how NTNs and traditional networks will coexist. In particular we will explore the feasibility of using LEO satellites for positioning, navigation, and timing (PNT) in conjunction with terrestrial networks.
Robot Mobile Manipulation
Team Members: (Left to Right) Jing-Chen Peng (Mentor), Shrey Agarwal, Sijuola Samaye, Po Cheng Chen, Sola Ishibashi
Advisor: Patricio Vela
This project involves programming a mobile robot to drive around an unstructured environment and manipulate objects to complete tasks, combining classical robotics stacks with state-of-the-art vision language models to perform language-conditioned mobile manipulation.
Convergence criteria and design of SPICE plausible compact modeling framework
Team Members: (Left to Right) Jay Sonawane (Mentor), Vansh Dhawan, Vedang Dugar, Saumya Agarwal, May Ming
Advisor: Shimeng Yu
Compact models are very important for understanding circuit and system level implementations in hardware. However, the more physical or complex a comapct model is, the difficulty of convergence in large circuit or array level simulations hinder understanding of certain physical behaviors in device to circuit implications. This project focuses on designing, implementing, and testing convergence-friendly compact models in Verilog-A, both physics-based and machine-learning-based.
Enriching the world of High Level Synthesis: extended construction for HLSFactory
Team Members: (Left to Right) Callie Hao (Faculty Advisor), Stefan Abi-Karam (Mentor), Justin Zhou, Tanmay Shukla, Kaushik Chandana, Jay Imperatori, Hanqiu Chen (Mentor, not pictured)
Advisor: Callie Hao
We are interested in building large-scale digital design datasets for AI applications in chip design. Mainly, the project focuses on curating high-level synthesis (HLS) designs from the academic community to integrate into our previous hardware design dataset effort, HLSFactory. Time allowing, we are also interested in creating more synthetic HLS designs using LLMs, as well as new cases for benchmarking LLMs on HLS design.
Pilot Beam Array for Long-Range Wireless Power Transfer
Team Members: (Left to Right) Amira Malave, Yufei Li, Carter Atkinson, Kaitlyn Graves (Mentor), Daniel May
Advisor: Greg Durgin
Radiative wireless power transfer (WPT) enables the delivery of electrical energy using electromagnetic waves, eliminating the need for wired connections. A pilot beam from the rectenna can be used to guide the power-beaming array to maintain high collection efficiency, but this comes at a cost of additional power consumption at the receiver. This project aims to investigate the use of a pilot beam array to maximize net harvested energy while maintaining long-distance power transfer.
Design, Fabrication, and Measurement of 3D-Printed and Machine Learning-Assisted Microwave Lens Structures
Team Members: (Left to Right) Sonny Lee (Mentor), Hamza Waraich, Sitong Li, Ryosuke Shibuya, Swathi Padmanabhan, Carol Li
Advisor: Nima Ghalichechian
Realization of lens for the mmWave band for ultra-high-speed, low-latency 5G communication involves high computational and fabrication efforts. This project aims to develop mmWave lens technologies, such as Fresnel lenses and radomes using low-cost additive 3D-printing techniques. Additionally, the project intends to use a machine learning (ML) framework trained on large datasets for designing lens structures to reduce the computational expense of full-wave electromagnetic simulations. The project involves design, simulation, programming, 3D printing, and measurements. Fabrication will be performed at GT Makerspace facility. At the end of this project unique and unconventional lens shapes that effectively radiate and function in the mmWave band are expected.
Synthesizing Field Programmable Analog Array (FPAA) in SKY130nm process
Team Members: (Left to Right) Praveen Raj Ayyappan (Mentor), Cyr Kamga, Shahir Latif, William Sasadu, Peter Rice, Prerana Gunda (Mentor)
Advisor: Jennifer Hasler
FPAAs serve as a critical platform for both implementing foundational analog circuit concepts and exploring large-scale analog architectures in hardware. Developing the next-generation FPAA in the Sky130nm process node allows for architectural improvements and a higher density of on-chip devices and circuits than previous versions. Leveraging our lab’s Analog Synthesis Tool (ASHES) and analog standard cells, this project will synthesize this advanced FPAA in the Sky130nm process.
Robot Autonomous Mapping and Inspection
Team Members: (Left to Right) Esteban Cecilio, Ana Sofia Suberviola, Nathaniel Dyer, Carlos Escoto Rivera, Priyavi Singh, Yanwei Du (Mentor)
Advisor: Patricio Vela
This project focuses on developing an autonomous robot capable of exploring and mapping an unknown environment while building a navigable route graph. The robot should autonomously explore the space, build a map, and execute inspection tasks (e.g., navigating to waypoints, checking predefined zones). A key focus is self-assessment, the robot should benchmark its own inspection reliability, detecting failures (e.g., missed areas, localization drift) and quantifying accuracy (e.g., pose error, coverage efficiency).
Design, Modeling, and Synthesis of Emerging Amorphous Oxide Semiconductor-based Memories & Systems
Team Members: (Left to Right) Jana Alzahid, Zixuan Pan, Faaiq Waqar (Mentor), Richard Kang, Andrew Fang
Advisor: Shimeng Yu
This project focuses on developing an autonomous robot capable of exploring and mapping an unknown environment while building a navigable route graph. The robot should autonomously explore the space, build a map, and execute inspection tasks (e.g., navigating to waypoints, checking predefined zones). A key focus is self-assessment, the robot should benchmark its own inspection reliability, detecting failures (e.g., missed areas, localization drift) and quantifying accuracy (e.g., pose error, coverage efficiency).
360-Degree Beamsteering with Rotman Lenses
Team Members: (Left to Right) Arnav Sharma, Thawin Serivivatanavongse, Krishiv Aggarwal, Mansi Bhardwaj, Nicholas Garber (Mentor)
Advisor: Andrew Peterson
Future cellular networks will rely on multibeam beamforming to achieve high data rates in dense environments. The project aims to develop a cost-effective, non-focal, Rotman-like lens for future cellular base stations. The project will mainly focus on the optical design of a lens using numerical optimization, PCB design for the lens, and a design for the antenna array.
Probing and Visualization Framework for 2.5D/3D Chiplet System Simulation
Team Members: (Left to Right) Ifeanyichukwu Ezegbo, Davin Aoyama, Ameen Shaikh, Changrui Li, Danish Baig (Volunteer mentor), Jiho Kim (Mentor)
Advisor: Callie Hao
As 2.5D and 3D chiplet technologies are reshaping system design and computer architect’s role, we’re developing a cutting-edge 2.5D/3D chiplet simulator for design space exploration on future architectures with built-in probing and visualization tools. This lets us “peek inside” complex multi-chip designs, trace how data flows, and quickly spot performance or communication issues.
Safe Quadruped Navigation with Reinforcement Learning and Gaussian Splatting
Team Members:
Advisor: Glen Chou
This project explores the fusion of advanced scene representation with reinforcement learning (RL) for safe quadruped navigation. Emerging techniques like 3D Gaussian Splatting now allow for the rapid creation of high-fidelity, photorealistic 3D scenes from simple video captures. We propose leveraging these captured environments within the NVIDIA Isaac Sim platform as a training ground for an RL agent. The core objective is to develop a control policy that enables a quadruped robot to navigate these complex, realistic digital twins while explicitly prioritizing safety and obstacle avoidance. This approach aims to create a robust pipeline for translating real-world spaces into simulation to train more intelligent and safer robotic agents.