Heterogeneous Materials and Devices for Energy-Efficient Electronics
Our lab at UC Berkeley EECS will officially launch in January 2026.
Interested in joining us? Please follow the details here. Also, check out our Latest Updates
Asir Intisar Khan
Assistant Professor (Incoming),
Electrical Engineering and Computer Sciences,
UC Berkeley
Email: asir@berkeley.edu
I am an incoming Assistant Professor in the Electrical Engineering and Computer Sciences (EECS) department at the University of California, Berkeley, starting in January 2026. Currently, as a postdoctoral scholar in the same department, I am establishing my independent research group.
I earned my Ph.D. (2023) and M.S. in Electrical Engineering from Stanford University. My research focuses on advancing energy-efficient electronics through atomic-scale engineering of heterogeneous materials and nanodevices to address fundamental energy and latency limits of traditional materials, devices, and architectures. My interdisciplinary work has been recognized with honors, including the 2022 IEEE-EDS Ph.D. Fellowship, 2022 MRS Gold Graduate Award, and 2023 AVS Russell & Sigurd Varian Award, along with several best paper and presentation awards at the 2022 IEEE VLSI Symposium, MRS Fall Meeting, 2023 SRC TECHCON, and 2023 AVS Symposium. I previously held research internships at TSMC and IBM T.J. Watson Research Center. Outside of my research, I enjoy traveling, coffee chats, playing tennis, and occasional board games.
AI Khan Lab - Research Vision
With the growth of data-driven artificial intelligence (AI), energy-efficient electronics are critical to addressing global challenges in sustainability, healthcare, and the Internet of Things (IoT). Emerging technologies such as on-chip edge computing and 3D integration of logic and memory hold promise for radically improved performance and efficiency. However, realizing this potential requires breakthroughs in materials, transport phenomena, device architectures, and thermal management.
Our group will focus on the development of low-power electronic devices by engineering heterogeneous device platforms and transformative materials, with a particular emphasis on controlling charge, heat, and spin transport at their interfaces. We are especially excited to contribute to next-generation AI hardware on both rigid and flexible substrates, and to explore novel interconnects and new thermal strategies for energy-efficient, 3D-integrated electronic systems. We are also highly interested in leveraging AI/ML for accelerated design of experiments, materials discovery, and physics-informed modeling, to enhance our understanding and optimization of materials and devices at multiple scales. These efforts and innovations will complement software and circuit design efforts, driving collaboration and multiplying energy-efficiency gains across computing hardware.
Interested in joining us? (Follow the details here)
We enjoy working across boundaries—combining materials synthesis, transport physics, device engineering, nanofabrication, and system-level integration. We are building a highly interdisciplinary group and encourage innovative ideas, versatile viewpoints, and skills. We welcome interest from highly motivated and innovative graduate students, postdoctoral researchers, and undergraduates with backgrounds in Electrical Engineering, Materials Science and Engineering, Mechanical Engineering, Applied Physics, and Computer Engineering.
Research at AI Khan Lab
