Assistant Professor
Department of Electrical and Computer Engineering
Carnegie Mellon University

Title: Intelligent Mobile Systems for Equitable Healthcare

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Abstract: Access to even basic medical resources is greatly influenced by factors like an individual’s birth country and zip code. In this talk, I will present my work on designing intelligent mobile systems for equitable healthcare. I will showcase three systems that are not only interesting from a computational standpoint but are also having real-world medical impact. The first system can detect ear infections using only a smartphone and a paper cone. The second system enables low-cost newborn hearing screening using inexpensive earphones. Lastly, I will present an ambient sensing system that employs smart devices to detect emergent and life-threatening medical events such as cardiac arrest. Through these examples, I will demonstrate how new computational and sensing techniques that generalize across hardware and work in real-world environments can help to address pressing societal problems.

Bio: Justin is an assistant professor in the School of Computer Science and Department of Engineering and Computer Engineering at Carnegie Mellon University, where he leads the Mobile Innovations Lab. His group's research focuses on building intelligent mobile and embedded systems for computational health and large-scale environmental sensing. His work on smartphone-based ear infections is now FDA-listed and is available to select early access healthcare systems. His work on new-born hearing screening has led to an international effort
called TUNE with the goal of bringing universal newborn hearing screening across Kenya as well as collaborations with NGOs to deploy this technology. His work on contactless cardiac arrest detection has been licensed to a startup which has recently been acquired by Google. He was also a lead contributor for Covid Safe (now WA Notify), a COVID-19 contact tracing and symptom tracking app, which became part of official efforts by the WA Department of Health to manage the pandemic. He has authored publications in interdisciplinary journals like Nature
Biomedical Engineering, Science Translational Medicine, Nature Communications as well as Computer Science and Engineering venues like MobiSys, MobiCom, SIGCOMM, SIGGRAPH Asia and UIST. His work has been recognized by a SIGMOBILE Doctoral Dissertation Award Runner Up and ACM SIGMOBILE Research Highlights twice.

Assistant Professor
Department of Electrical and Computer Engineering
Cornell University

Title: Designing Magnetic Manipulation at the Nanoscale

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Abstract: Magnetism is capable of manipulation of objects both large and small, near and far, visible and invisible. This talk will focus on two ways in which magnetic devices are being developed for manipulation. More specifically, I will present two examples in which we are using magnetism to design versatile devices with applications to haptics (manipulating tactile surfaces) and communications (manipulating electromagnetic waves). First, we will consider what magnetic features are required to make reconfigurable haptic interfaces, capable of giving the user the sensation that they are feeling what they are seeing on a visual display; and reconfigurable communication systems, capable of tuning their frequency of operation real-time. Here, I will present our self-assembled magnetic nanostructures with large magnetic moment and anisotropy as a potential solution to both applications. For haptic interfaces, true 3D fidelity in a tactile display requires extremely flexible materials that can also be programmed real-time to physically illustrate what is visually displayed on the screen. I will present how our magnetic elastomer composites can be used to achieve such fidelity. For microwave communication systems, high frequency resonances need to be widely tunable to enable adaptive filtering and more interference-resilient communications. I will present how our high magnetic anisotropy materials can provide adaptability of such sharp filters at frequencies in the tens of gigahertz. The projects discussed will illustrate the impact of magnetism on the design of broadly versatile devices to ameliorate both technology and society in the future.

Bio: Amal El-Ghazaly is an assistant professor in the department of electrical and computer engineering at Cornell University and an NSF CAREER award recipient. Her work combines magnetism and ferroelectricity to create tunable, versatile electronic systems for telecommunications, sensing and actuation. Prior to joining Cornell in 2019, she was a postdoctoral research fellow at the University of California Berkeley, where she was awarded the University of California President's Postdoctoral Fellowship in 2017. Her postdoctoral research explored new possibilities for ultrafast all-electrical switching of magnetic nanodots for faster and more energy-efficient computer memories. She earned a Ph.D. in electrical engineering from Stanford University, where she was funded by both NSF and NDSEG graduate research fellowships as well as the Stanford DARE fellowship until her graduation in 2016. Her Ph.D. research focused on radio frequency devices using magnetic and magnetoelectric thin-film composites for tunable wireless communications. She received her B.S. and M.S. degrees in electrical and computer engineering from Carnegie Mellon University in 2011.

Affiliate Scientist
Sandia National Laboratories

Title: Quantum Information Science Enabled by Focused Ion Beams

Abstract: The widespread application of quantum information sciences (QIS) will require fabrication of quantum systems at scale. Solid state based color centers are an interesting platform for QIS, with recent demonstrations of the largest quantum network (three nodes) based on nitrogen vacancy color centers in diamond. While scalability may be achieved with color centers due to them being hosted in a solid state material, an important challenge to overcome is their deterministic fabrication.

In this talk I will present challenges in the deterministic fabrication of color centers and our paths of overcoming these challenges using focused ion beams coupled with in-situ techniques. I will discuss how tailored light irradiation during high-temperature activation annealing can be utilized to dissolve unwanted vacancy clusters to improve the yield of silicon vacancies (SiV) in diamond. The technique uses sub bandgap light irradiation to ionize and destabilize unwanted defect clusters while leaving (SiV) untouched. 

Bio: Michael Titze is a Senior Member of the Technical Staff in the Sandia National Laboratories Ion Beam Laboratory. His research focus is the development of in-situ techniques for the fabrication of quantum devices. Prior to joining Sandia he received his PhD in Physics from Florida International University working on ultrafast spectroscopy and a BSc in Physics from Heinrich Heine Universität Düsseldorf, Germany.

Assistant Professor
Department of Electrical and Computer Engineering
Carnegie Mellon University

 Watch the seminar here.

Associate Professor
Department of Electrical and Computer Engineering
University of California, Santa Barbara

Title: From Hardware to Algorithms: Probabilistic Computing for Machine Learning, Optimization, and Quantum Simulation

Abstract: This talk will highlight probabilistic computers as an emerging paradigm for domain-specific computation. Firmly connected to the widely used Markov Chain Monte Carlo algorithms widely used in physics, statistics, and ML, the talk will show how networks of probabilistic bits, or p-bits, in hardware can deliver improvements in time and energy to solutions for ML, optimization, and quantum simulation.

Probabilistic computers leverage a physics-inspired architecture with sparse connectivity and asynchronous updates, enabling massive parallelism. Digital implementations in single FPGAs show competitive performance against optimized GPUs/TPUs. Recent efforts with a distributed system of multiple FPGAs creates the “illusion” of a single, more powerful system, achieving near-linear speedup with minimal communication overhead.

Beyond digital CMOS, magnetic nanodevices offer intrinsic randomness, replacing thousands of transistors per p-bit and reducing energy per operation. Our ongoing efforts aim to integrate these devices into energy-efficient CMOS+X systems. Comparisons with quantum computers, GPUs/TPUs, and coupled oscillators will illustrate how probabilistic computers combined with tailored algorithms could achieve GPU-like impact and enable new applications.

[1] W. A. Borders, A. Z. Pervaiz, S. Fukami, K. Y. Camsari, H. Ohno, S. Datta, Integer Factorization Using Stochastic Magnetic Tunnel Junctions, Nature, (2019)
[2] N. A. Aadit, A. Grimaldi, M. Carpentieri, L. Theogarajan, J. M. Martinis, G. Finocchio, K. Y. Camsari, Massively Parallel Probabilistic Computing with Sparse Ising Machines, Nature Electronics (2022)
[3] S. Niazi, S. Chowdhury, N. A. Aadit, M. Mohseni, Y. Qin, and K. Y. Camsari. Training deep Boltzmann networks with sparse Ising machines. Nature Electronics (2024)
[4] N. S. Singh, K. Kobayashi, Q. Cao, K. Selcuk, T. Hu, S. Niazi, N. A. Aadit, S. Kanai, H. Ohno, S. Fukami, K. Y. Camsari, “CMOS plus stochastic nanomagnets enabling heterogeneous computers for probabilistic inference and learning,” Nature Communications, (2024).

Bio: Kerem Camsari received his Ph.D. in Electrical and Computer Engineering from Purdue University in 2015 and worked there as a postdoctoral researcher until 2020. He is currently an Associate Professor at the University of California, Santa Barbara. Kerem is a founding member and leads the unconventional computing section of the IEEE Nanotechnology Council’s Technical Committee on Quantum, Neuromorphic, and Unconventional Computing. He has received several honors, including the IEEE Magnetics Society Early Career Award, a Bell Labs Prize, the ONR Young Investigator Award, and the NSF CAREER Award for his work on probabilistic computing. He served as an IEEE Distinguished Lecturer in 2024 and is a senior member of IEEE.

Assistant Professor
Department of Electrical and Computer Engineering
University of Texas at Austin

Title: Terminus: Moving the Center of Cloud Servers to SmartNICs and Beyond

Abstract: Server design has traditionally been processor-centric. Processors received each input and decided whether to process it first or pass it to another component, such as an accelerator or memory, to be processed and/or stored. In public clouds that rent virtual machines to tenants, however, the center of the server is moving from processors to SmartNICs/IPUs/DPUs that implement cloud infrastructure functionality such as triage of IO, virtualization, security, and Quality of Service. SmartNICs are complex systems, requiring programmable components for flexibility, ASICs for performance and efficiency, and software to coordinate and manage. This talk (i) motivates moving the center of cloud servers to SmartNICs, (ii) describes what SmartNICs do and how they do it (iii) discusses the tradeoffs of implementing programmability on cores and FPGAs, and (iv) explores potential future paths for SmartNICs and the functionality they implement.

Bio: Derek Chiou is a Professor in the Electrical and Computer Engineering Department at The University of Texas at Austin and a Partner Architect at Microsoft responsible for future infrastructure offload system architecture. He is a co-founder of the Azure Boost project, Microsoft's SmartNIC effort, and led the Bing FPGA team to first deployment of Bing ranking on FPGAs. He was an assistant and associate professor from 2005 to 2016. Before joining UT in 2005, Dr. Chiou was a system architect at Avici Systems, a manufacturer of terabit core routers. Dr. Chiou received his Ph.D., S.M. and S.B. degrees in Electrical Engineering and Computer Science from MIT.