Computer Systems & Engineering

The Ken Kennedy Institute brings together the Rice community to foster innovations in computing and data science. Check out the list below to learn about how Rice University faculty are applying data and computation to Computer Systems & Engineering.

 

  • Professor Athanasios Antoulas’ research focuses on large-scale dynamical systems, approximation, computation, and linear algebra. One of his projects focuses on the approximation of large-scale dynamical systems, seeking to develop reduced models for LTI systems through low rank approximation of certain system Grammians. The approach has high potential for addressing two fundamental difficulties with existing dimension reduction techniques, central to the potential development of robust and widely applicable software.
  • Professor Joseph Cavallaro’s research is in special-purpose VLSI processor architectures. Advances in VLSI technology have made possible the implementation of special-purpose processors for signal processing, computer graphics, and robotics. Many of these applications involve a core group of matrix computations that can be efficiently performed on parallel arrays of functional units. In particular, important numerical algorithms for wireless communication systems can greatly benefit from enhanced parallel architectures and high-speed computer arithmetic. These algorithms and their efficient mapping to low-power architectures are studied on DSP, ASIC, and Application-specific Instruction Processors (ASIP).
  • Professor Taiyun Chi leads research in the areas of Computer engineering, RF/millimeter-wave/terahertz integrated circuits, integrated bio-sensors and bio-actuators. Taking advantage of the rapid development of silicon technologies (CMOS and SiGe BiCMOS), Dr Chi’s team have been developing innovative circuit topologies and system architectures and pushing the fundamental limitations in fully integrated and self-contained electronic systems.
  • Professor Caleb Kemere’s research interests include realtime neural engineering, interacting with memory, deep brain stimulation, neural interface technologies, and open source tools. In one project, Dr. Kemere’s team is seeking to develop systems that translate ongoing neural activity into information and use this to manipulate the hippocampal circuit in real-time. One potential application is  to build systems that will, for example, allow us to selectively inhibit the recall or long-term storage of traumatic episodes.
  • Professor Yingyan Lin leads the Efficient and Intelligent Computing (EIC) Lab at Rice, which focuses on embedded machine learning and aims to develop techniques towards green AI and ubiquitous machine learning powered intelligence. She addresses the unprecedented challenge of improving the energy/time efficiency in powerful machine learning systems by following three research directions: 1) Pioneered research in efficient deep learning (DL) training algorithms, 2) Originated new efficient DL inference/training accelerators, and 3) The first-of-their-kind automated tools for efficient DL solutions.
  • Professor Ray Simar’s research interests include RISC-V, TinyML (machine learning on microcontrollers), motion sensors, benchmarking methodology for embedded microprocessors, instruction encoding for code-size reduction, dual-mode hands-on microprocessor lab development, analysis of COVID-19 case patterns, as well as a number of growing topics supporting his VIP (Vertically Integrated Projects) team of undergraduate and graduate students.  He is a member of the Embench team, developing a new suite of industry benchmarks for embedded processing.
  • Professor Peter Varman’s research interests are: Computer Architecture, including storage systems, memory architectures, virtualization; Computer Systems, including resource allocation, scheduling, performance evaluation; High-end Computing, including parallel architectures, parallel IO, parallel algorithms. In one project, Parallel I/O, he seeks to develop scheduling and resource management algorithms for parallel I/O systems, including issues related to prefetching and caching, on-line scheduling, fair service for multiple users, and deadline-constrained real-time parallel I/O. The techniques are being applied to VBR video retrieval and database applications handling large numbers of concurrent, interacting I/Os.
  • Professor Kaiyuan Yang leads the Secure and Intelligent Micro-Systems (SIMS) Lab. His research interests lie in the area of digital and mixed-signal solid-state circuits, VLSI and integrated microsystem designs, with applications in security, artificial intelligence, bioelectronics, and internet of everything. His lab seeks to innovate analog/digital/mixed-signal circuit and system designs to push the limits of energy efficiency and performance in miniaturized microsystems. He is also interested in addressing pressing system challenges on security and machine learning from a hardware perspective, which will be explored through cross-layer (devices, circuits, architecture, and algorithm) design and optimizations.
  • Professor Rahman Doost-Mohammady’s research interests include wireless systems and networking and embedded reconfigurable computing. Additionally, he is the technical lead for the RENEW project at Rice where we are building an open-source reconfigurable research testbed for massive MIMO.
  • Professor Edward Knightly is the Sheafor-Lindsay Professor of Electrical and Computer Engineering. His research interests are design and in-the-field demonstration of new mobile and wireless networks and systems, including mission-driven autonomous drone networks, wireless security, and networked spectrum access in UHF, 60 GHz, THz, and visible light. He leads the Rice Networks Group. The group’s projects include deployment, operation, and management of a large-scale urban wireless network in a Houston under-resourced community. His group developed the first multi-user beam-forming WLAN system that demonstrates a key performance feature now provided by Wi-Fi since the 802.11ac amendment.
  • Professor Ashutosh Sabharwal is the Sheafor-Lindsay Professor and depart chair of Electrical and Computer Engineering. He currently works in two research areas, wireless and health. His wireless research spans fundamental theory and experimental systems. He is the founder of WARP project (warp.rice.edu), an open-source project which is now in use at more than 125 research groups worldwide, and have been used by more than 500 research articles. His health research is at the intersection of engineering, behavioral sciences and medicine, and he established Scalable Health Labs. Scalable Health Labs’ mission to develop methods to uncover behavior-biology causal pathways, with a specific focus in three areas: bio-behavioral sensing, mobile bio-imaging, and data science methodologies.
  • Professor Santiago Segarra is the W. M. Rice Trustee Assistant Professor in the Department of Electrical and Computer Engineering. His research interests include Network Theory, Data Analysis, Machine Learning, and Graph Signal Processing. Examples of his research include (in Network Theory) proposing a network topology effective in recovering brain, social, financial and urban transportation networks using synthetic and real-world signals, and (in Machine Learning) developing Neural Network architectures for electricity consumption forecasting.
  • Professor Ashok Veeraraghavan’s research areas include Computational Imaging, compressive sensing for imaging, signal processing and computer vision. Data Science, and Neuroengineering. He is co-developer of FlatCam, a thin sensor chip with a mask that replaces lenses in a traditional camera. Making it practical are the sophisticated computer algorithms that process what the sensor detects and converts the sensor measurements into images and videos. FlatCams may find use in security or disaster-relief applications and as flexible, foldable, wearable cameras, and even disposable cameras. His team has also developed FlatScope, a flat microscope and software system that can decode and trigger neurons on the surface of the brain.
  • Professor Ang Chen’s research interest lies in designing secure, efficient, and reliable networked systems. One direction he has been working on is Programmable In-network Security (Poise), rethinking how future networks should support security architecturally. Another direction he is looking at is network support for data-intensive applications, which aims to optimize the interaction between data-processing tasks and the underlying network. In addition, he is working to make large-scale systems more reliable, where we develop new primitives for failure prevention, diagnosis, and repair.
  • Professor Alan Cox’s research interests include parallel processing, computer architecture, distributed systems, concurrent programming, and performance evaluation. Some of his influential works include Gd-wheel: a cost-aware replacement policy for key-value stores, Predictive parallelization: Taming tail latencies in web search, Plinko: Building provably resilient forwarding tables, PAST: Scalable Ethernet for data centers, and SpecTLB: a mechanism for speculative address translation.
  • Professor Scott Cutler is a Professor in the Practice who came to Rice University in 2001 after a long industrial career culminating as Vice President and Chief Technology Officer of Compaq Computer’s PC Group. He has esearch interests in smart devices and in particular speech enabled digital assistants like the Amazon Echo  and Google Home. His main goal at Rice is to support student growth and administrative efforts that improve student life; the most important of which was the creation of Schedule Planner which is used by virtually all Rice undergraduates to plan their academic schedules.
  • Professor Nathan Dautenhahn's research identifies fundamental abstraction gaps and closes them with cross-layer solutions. He is most interested in building trustworthy systems software, where a single exploit could compromise the whole system. His research in operating system security has applied two key approaches: decompose systems in ways that enhance trustworthiness and harden them to attack.
  • Professor David Johnson’s research interests are generally in the areas of network protocols, distributed systems, and operating systems, particularly in the interactions between these areas. Professor Johnson founded and is leading the Monarch (MObile Networking ARCHitectures) research group at Rice developing adaptive networking protocols and architectures to allow truly seamless wireless and mobile networking. He was one of the main designers of the IETF Mobile IP protocol standard for IPv4, the current version of IP in use in the Internet today, and is the primary designer of Mobile IP for IPv6.
  • Professor Eugene Ng’s current research interest lies in developing new network models, network architectures, and holistic networked systems that enable a robust and manageable global networked infrastructure for the future. He leads the BOLD (Big data and Optical Lightpaths Driven) Lab, investigating creative use of high-performance, low-power optical networking devices to invent a transformative computing infrastructure for solving big data problems.
  • Professor Scott Rixner’s research spans virtualization, operating systems, and computer architecture, with a specific focus on memory systems and networking. His work has led to 11 patents and has been implemented within several open source systems. He is also well versed in the internals of the Python programming language, as he has developed Python interpreters for both embedded systems and web browsers.
  • Professor Dan Wallach’s research interests include mobile code, wireless and smartphone security, and the security of electronic voting systems. He manages Rice’s Computer Security Lab, with wide collaborations, as computer security issues have broad impact well beyond traditional computer science. The Computer Security Lab has been named by the National Security Agency and the Department of Homeland Security jointly a National Center of Academic Excellence in Information Assurance Research.