BRIEF BIO

I joined Carnegie Mellon University in 2003 as a Systems Faculty with the Electrical and Computer Engineering Department and the Information Networking Institute. I was previously a Research Staff Member with Motorola's Broadband Communications Division in San Diego, CA, where I was involved in the H.264 video-compression standardization activity. I received a Motorola Outstanding Performance award in 2002 in recognition of my contributions to global standardization activities. Prior to this, I received my Ph.D. in March 2000 from the University of California, Santa Barbara and my B.Tech. degree from IIT Bombay in 1994.

RESEARCH

My research interests span wireless sensor networks, embedded systems, signal processing and security. I have also recently become interested in the application of statistical techniques and machine-learning algorithms to computer system problems, particularly in the area of failure diagnosis. My current research projects include the following:

• Sluice: A resource-sensitive security enhancement to code-update protocols in wireless sensor networks using asymmetric cryptographic primitives such as digital signatures
• Castor: A security enhancement to code update protocols in wireless sensor networks that exploits lightweight symmetric cryptographic primitives that might be more suited to resource-constrained embedded systems.
• Sherlock: Failure diagnosis (or root-cause analysis) in distributed systems through the application of statistical anomaly-detection algorithms, machine-learning techniques such as clustering, etc.

I am fortunate to work with talented students such as Patrick Lanigan, Soila Pertet and Donnie Kim. I am also affiliated with the Center for Sensed Critical Infrastructure Research (CenSCIR) at CMU.

RECENT PUBLICATIONS

• Castor: Secure Code Updates in Sensor Networks using Symmetric Cryptosystems, Donnie H. Kim, Rajeev Gandhi, and Priya Narasimhan, To be presented at Real-Time Systems Symposium (RTSS), Tucson, AZ, December 2007
• Exploring Symmetric Cryptography for Secure Network Reprogramming, Donnie H. Kim, Rajeev Gandhi, and Priya Narasimhan, Workshop on Wireless Ad-hoc and Sensor Networks (WWASN), Toronto, Canada (June 2007)
• Fingerpointing Correlated Failures in Replicated Systems , Soila M. Pertet, Rajeev Gandhi, Priya Narasimhan, USENIX Workshop on Tackling Computer Systems Problems with Machine Learning Techniques (SysML), Cambridge, MA (April 2007)
• Sluice: Secure Dissemination of Code Updates in Sensor Networks, Patrick E. Lanigan, Rajeev Gandhi, Priya Narasimhan, International Conference on Distributed Computing Systems (ICDCS), Lisbon, Portugal (July 2006)
• Undergraduate Embedded System Education at Carnegie Mellon, Koopman, P., H. Choset, R. Gandhi, B. Krogh, D. Marculescu, P. Narasimhan, J. Paul, R. Rajkumar, D. Siewiorek, A. Smailagic, P. Steenkiste, D. Thomas, C. Wang, ACM Transactions on Embedded Computing Systems, vol 4, no. 3, September 2005.
• Group Communication: Helping or Hindering Failure Diagnosis?, Soila M. Pertet, Rajeev Gandhi, Priya Narasimhan, Technical Report CMU-PDL-06-107, Parallel Data Laboratory, Carnegie Mellon University, July 2006.

The list of all my publications can be found here.

TEACHING

I teach the Fundamentals of Embedded Systems (18-342/14-642) course at Carnegie Mellon University. This practical, hands-on course introduces students to the basic building-blocks and the underlying scientific principles of embedded systems. The course covers both the hardware and software aspects of embedded processor architectures, along with operating system fundamentals, such as virtual memory, concurrency, task scheduling and synchronization. Through a series of laboratory projects involving state-of-the-art processors, students learn to understand implementation details and to write assembly-language and C programs that implement core embedded OS functionality, and that control/debug features such as timers, interrupts, serial communications, flash memory, device drivers and other components used in typical embedded applications. Relevant topics, such as optimization, profiling, and real-time operating systems are also covered.

PATENTS

• Co-inventor, Frequency coefficient scanning paths for coding digital video content. United States Patent: 7088867. August 2006.
• Co-inventor, Macroblock level adaptive frame/field coding for digital video content. United States Patent: 6980596. December 2005.