The Intel® Rising Star Faculty Award (RSA) program has selected ten promising early-career academic researchers who lead some of the most important technology research of our time. The chosen faculty members work with disruptive technologies that have the potential to advance the future of computing in fields encompassing computer science, electrical engineering, computer engineering, material science, and chemical engineering.
The program recognizes community members who are doing exceptional work in the field and facilitates long-term collaborative relationships with senior technical leaders at Intel. Recipients of this award are also distinguished for exemplifying innovative teaching methods and increasing the participation of women and underrepresented minorities in computer science and engineering.
The key technology areas under investigation by selected faculty include cybersecurity, hardware security, nanotechnology, semiconductor device technologies, neuromorphic computing, machine learning/artificial intelligence, and memory management.
This year’s winners include esteemed faculty at the following institutions:
- Carnegie Mellon University
- University of Illinois at Urbana-Champaign
- Arizona State University
- Stanford University
- University of Texas at Austin
- Cornell University
- University of Pennsylvania
- Oregon State University
- Georgia Institute of Technology
- Indian Institute of Science
The RSA winners for 2021 are:
Arkaprava Basu
Assistant Professor of Computer Science and Automation
Indian Institute of Science
Dr. Arkaprava Basu, assistant professor at the Department of Computer Science and Automation at the Indian Institute of Science, runs the Computer Systems Lab and conducts computer architecture research, including architecture, memory, software, and security. Arkaprava’s work focuses on memory management across the operating system and the computer architecture boundary for both GPUs and CPUs, including enhancing the reliability of GPU software and some aspects of security. Arkaprava plans to focus on hardware/software co-design for easier and broader adoption of disruptive hardware and software technologies. In addition, he plans to focus on low-overhead secure non-volatile memory (NVM), exploring the synergy between accelerators and NVM, tools to enhance GPU software reliability, and enriching serverless computing ecosystems.
Priyanka Raina
Assistant Professor of Electrical Engineering
Stanford University
Dr. Priyanka Raina, assistant professor from the Department of Electrical Engineering at Stanford University, received her Ph.D. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (MIT). Her recent research includes designing efficient and scalable systems for machine learning using both conventional silicon CMOS technology and emerging memory technologies such as resistive RAM (RRAM). In addition, Priyanka is working to improve the design methodology of hardware-software systems with domain-specific accelerators. Her efforts are intended to create more programmable accelerators and evolve these systems in an agile manner, which is the goal of Stanford’s Agile Hardware (AHA) Center that Priyanka leads.
Kelsey Stoerzinger
Assistant Professor of Chemical Engineering
Oregon State University
Dr. Kelsey Stoerzinger, assistant professor at Oregon State University, studies the link between a materials’ electronic structure and their interaction with light, surface reactivity, and their ability to transfer charge to molecules in an environment or a given chemical reaction. Kelsey’s approaches include spectroscopy (x-ray, vibrational), electrochemistry, and heterogeneous catalysis. She plans to develop design principles for materials interaction with light and applied potential, including the transference of this energy to change bonding arrangements or generate charge carriers subsequently transferred to nearby molecules in chemical reactions. Kelsey received a National Science Foundation CAREER award, a Doctoral New Investigator award from the American Chemical Society (ACS) Petroleum Research Fund, the CIBA Young Scientist Travel award from the ACS, and the Coatings Young Investigator Award from MDPI.
Jean Anne Incorvia
Assistant Professor of Engineering
The University of Texas at Austin
Dr. Jean Anne Incorvia is an assistant professor at the Electrical and Computer Engineering Department of the Cockrell School of Engineering at the University of Texas at Austin. She is an expert in nanoelectronics and has significantly advanced magnetic-material-based devices for computation. Her Ph.D. at Harvard and MIT, and postdoctoral work at Stanford, established her as one of the top experts in magnetic tunnel junction-based computation. Jean Anne’s research focus areas include memory and architecture. At UT Austin, Jean has extended this work to include memory such as novel magnetic random-access memory (MRAM) and in-memory computing and neuromorphic computing, artificial intelligence, and machine learning. Her research focuses on the design, fabrication, and testing in-memory and neuromorphic computing devices and circuits using emerging materials.
Ivan Sanchez Esqueda
Assistant Professor of Electrical, Computer, and Energy Engineering
Arizona State University
Dr. Ivan Sanchez Esqueda is an assistant professor at the School of Electrical, Computer, and Energy Engineering at Arizona State University. His research agenda includes studying nanoelectronic technologies, focusing on exploring and discovering new device functions in nanostructures for disruptive computing technologies and non von Neumann systems. His work explores the use of two-dimensional (2D) van der Waals (vdW) materials to develop novel resistive-switching non-volatile memory (NVM), memristors, as well as charge and spin-based field-effect transistors. His research agenda also explores novel spin-based devices based on high spin-orbit coupling (SOC) and spin-proximity effects in vdW heterostructures. This work will emphasize building blocks for next-generation spintronics/spin-orbitronics and spin-based memory for neuromorphic computing systems.
Chris Fletcher
Assistant Professor of Computer Science
The University of Illinois at Urbana-Champaign
Dr. Chris Fletcher, assistant professor at the Department of Computer Science at the Grainger College of Engineering, develops low-overhead, principled defenses to microarchitectural attacks and the discovery of next-generation microarchitectural vulnerabilities before they hit the market. Chris plans to take on some of the major open questions in more secure processor design, looking across theory and practice from attacks and defenses. His research aims to fundamentally change the hardware security landscape and enable more secure processor design that blocks broad classes of attacks, empowering the industry to break the seemingly never-ending attack/patch cycle. The research also has the potential to anticipate even exotic hardware zero-day vulnerabilities before processors ship, stopping microarchitectural attacks seen on deployed systems today.
Christina Lee Yu
Assistant Professor of Operations Research and Information Engineering
Cornell University
Dr. Christina Lee Yu, assistant professor at the School of Operations Research and Information Engineering, joined Cornell after a one-year postdoctoral at Microsoft Research New England. Yu’s research is at the interface of modern statistics and machine-learning algorithms for high-dimensional data analysis and sequential decision making. Her accomplishments include (1) designing scalable algorithms with optimal theoretical guarantees for statistical inference with noisy high dimensional data, (2) provably reducing memory and data requirements of reinforcement learning algorithms by using adaptive discretization to exploit structure, (3) proposing simple policies for sequential multi-objective fair resource allocation. Her research bridges theory and practice in a way that has led to fundamental developments in theoretical understanding and resulted in relevant and impactful practical algorithms that open new possibilities for machine learning to aid better decision making. She is a recipient of an Honorable Mention for the INFORMS George B. Dantzig Dissertation Award and the Woman in Information Theory Society co-chair.
Deep Jariwala
Assistant Professor of Electrical and Systems Engineering
University of Pennsylvania
Dr. Deep Jariwala is an assistant professor who teaches at the Department of Electrical and Systems Engineering at the University of Pennsylvania. His expertise in nanoelectronics and novel computing includes computing and memory devices using novel materials such as carbon nanotubes and two-dimensional (2D) semiconductors. Dr. Jariwala’s research has focused on new devices and materials for electronics, specifically for logic and memory devices and photonic materials, and studying fundamental light-matter interactions for photodetectors, lasers, and optical modulators. His research group is looking towards advancing memory, memory-based computing, and low-power logic. He has received several professional awards, including the Army Research Office Young Investigator Award, the IEEE Philadelphia/Delaware Valley Young Engineer of the year, Invitee to Frontiers of Engineering Conference of the National Academy of Engineering, Forbes Magazine 30 Scientists Under 30, as well as TMS Frontiers of Materials Award.
Diyi Yang
Assistant Professor of Interactive Computing
Georgia Institute of Technology
Dr. Diyi Yang is an assistant professor who teaches at the School of Interactive Computing at Georgia Institute of Technology and is affiliated with the Machine Learning Center at Georgia Tech (The Georgia Institute of Technology). Her areas of research include natural language processing, machine learning, and computational social science. She focuses on the social aspects of human language via building methods for NLP and ML and leveraging theories in social sciences to develop systems to facilitate human-human and human-machine communication. Diyi aims to build novel ML algorithms for low-resource languages to increase participation from global communities. She also plans to focus on socially aware language understanding and generation and responsible language technologies for social good.
Giulia Fanti
Assistant Professor of Electrical and Computer Engineering
Carnegie Mellon University
Dr. Giulia Fanti is an assistant professor at the Electrical and Computer Engineering Department at Carnegie Mellon University. She studies systems that enable cooperation in limited-trust environments, with applications to some of the most pressing problems facing society today (e.g., cybercrime, financial inclusion, and climate change). A major technical challenge in her work stems from its inherently multidisciplinary nature, drawing on distributed systems, networking, machine learning, security, privacy, and information theory. Giulia’s recent awards include the 2021 Sloan Research Fellowship, a JP Morgan Chase Faculty Award, a 2020 Young Investigator award from the U.S. Air Force Research Lab, and a 2020 Google Faculty Award. She is also a founding co-director of CMU’s new CyLab-Africa initiative, an academic center for improving the security and resilience of Africa’s financial technologies and infrastructure.