Research

Seeking candidates across two research directions: 1) NTN Communication Systems, Protocols & AI: Developing and adapting 5G/6G and O-RAN architectures, protocols, and software stacks for satellite networks, addressing NTN-specific challenges such as long propagation delays, Doppler effects, timing synchronization, satellite mobility, dynamic topology, and handover management. Research also includes AI-driven network optimization, RAN Intelligent Controllers (RIC), and xApps/rApps. Strong programming skills (C/C++/Python), hands-on experience with wireless protocols, 3GPP NR-NTN, or O-RAN systems, and familiarity with AI/ML are highly desirable. 2) NTN Radio Units & Wireless Hardware: Designing next-generation radio units, RF front ends, and PHY-layer implementations for satellite communications, including beamforming, MIMO, and FPGA/SDR platforms. Strong background in RF design, wireless communications, signal processing, or FPGA implementation is preferred.

This methodology complements broader AI accelerator and computing-systems research. Seeking candidates interested in developing AI-driven methodologies for next-generation chip design and automation. Research directions include leveraging large language models (LLMs), agentic and multi-agent AI, reinforcement learning (RL), and foundation models for design space exploration, RTL generation, power, performance, and area (PPA) optimization, formal verification, physical design, and hardware security. Candidates should have a strong foundation in chip design, VLSI, EDA, along with solid AI/ML expertise, particularly hands-on experience with LLMs and reinforcement learning.

Seeking candidates interested in developing next-generation computing and networking infrastructure for AI systems. Research directions include custom AI accelerators, ASICs, chiplet-based architectures, in-memory and neuromorphic computing, emerging memories and back-end-of-line (BEOL) integration, CMOS+X technologies, silicon photonics, heterogeneous integration, advanced packaging and 3D integration, high-performance interconnects, AI networking, and distributed AI computing. Particular emphasis is placed on scalable, energy-efficient, and resilient AI infrastructure for data centers, edge, and aerospace applications, including space-based AI infrastructure, orbital data centers, radiation-tolerant computing, and autonomous onboard computing. Ideal candidates have a strong background in electrical engineering, computer engineering, or computer science, with hands-on experience in one or more of ASIC design flows, analog/mixed-signal circuits, emerging devices and memories, VLSI, computer architecture, networking, distributed systems, or hardware-software co-design.

Seeking candidates interested in developing next-generation AI models that enable intelligent agents to perceive, reason, learn, plan, and act in complex physical environments. Research directions include vision-language-action (VLA) models, vision-language models (VLMs), multimodal world models, embodied foundation models, spatial and embodied reasoning, reinforcement learning, imitation learning, long-horizon planning, recursive self-improvement and self-evolving AI agents, continual learning, sim-to-real transfer, and resilient collective intelligence. Ideal candidates have a strong background in artificial intelligence or computer science, with hands-on experience in deep learning, foundation models, reinforcement learning, or multi-agent systems. Familiarity with world models, VLA/VLM architectures, reasoning, or self-improving AI systems is highly desirable.

Seeking candidates interested in advancing hardware security, AI model security, and the trustworthiness of AI systems. Research directions include hardware security challenges such as side-channel attacks, fault injection attacks, hardware Trojans, and vulnerabilities in AI accelerators and computing platforms, as well as AI model security threats including adversarial attacks, model extraction, data poisoning, backdoors, prompt injection, and model privacy. We are particularly interested in developing novel security mechanisms, secure AI inference, and resilient defenses across hardware and AI software stacks. Ideal candidates have a strong background in hardware security, computer security, computer architecture, or machine learning, with hands-on experience in hardware security or AI/ML security.

Seeking candidates interested in developing next-generation intelligent aerospace systems for mission-critical applications, spanning satellites, CubeSats, UAVs, autonomous aerial platforms, and space robotics. Research directions include onboard AI and edge computing, autonomous navigation and control, multi-agent coordination, resilient communications, cybersecurity, and reliable operation in contested, degraded, or GPS-denied environments. We particularly value multidisciplinary candidates who can connect the dots across AI, robotics, aerospace engineering, embedded systems, communications, and security to develop integrated, real-world solutions. Ideal candidates have a background in aerospace, electrical, computer, or mechanical engineering, or robotics, with hands-on experience in CubeSat/SmallSat development, UAVs and quadcopters, avionics, embedded systems, flight control, CAD, 3D printing, rapid prototyping, or system integration and testing. Candidates with demonstrated experience designing, building, and testing complex systems, including veterans and individuals with (defense) R&D or aerospace industry backgrounds, are particularly encouraged to apply. We also welcome active-duty military officers and government professionals seeking PhD opportunities through service-sponsored or government-funded graduate education programs, including (but not limited to) those affiliated with the U.S. Space Force, Air Force, Army, and other defense organizations.