Ramesh Govindan

About

Ramesh Govindan holds the Northrop Grumman Chair in Electrical and Computer Engineering and is a Professor of Computer Science and Electrical and Computer Engineering at USC. The page lists him among the faculty members of the Thomas Lord Department of Computer Science at USC Viterbi School of Engineering. However, the provided text does not include any detailed information about his research focus, background, or key contributions.

Research topics

• Computer Science
• Artificial Intelligence
• Computer Security
• Distributed computing
• Computer network
• Algorithm
• Telecommunications
• Real-time computing
• Simulation
• Computer vision

Selected publications

• New Frontiers in IoT: Networking, Systems, Reliability, and Security Challenges

  IEEE Internet of Things Journal · 2020 · 64 citations

  The field of IoT has blossomed and is positively influencing many application domains. In this article, we bring out the unique challenges this field poses to research in computer systems and networking. The unique challenges arise from the unique characteristics of IoT systems such as the diversity of application domains where they are used and the increasingly demanding protocols they are being called upon to run (such as video and LIDAR processing) on constrained resources (on-node and networ…

  DOI

• AutoCast

  2022 · 51 citations

  Senior authorCorresponding

  Autonomous vehicles use 3D sensors for perception. Cooperative perception enables vehicles to share sensor readings with each other to improve safety. Prior work in cooperative perception scales poorly even with infrastructure support. AUTOCAST1 enables scalable infrastructure-less cooperative perception using direct vehicle-to-vehicle communication. It carefully determines which objects to share based on positional relationships between traffic participants, and the time evolution of their traj…

  PublisherOA PDFDOI

• CarMap: Fast 3D Feature Map Updates for Automobiles

  Networked Systems Design and Implementation · 2020 · 28 citations

  Senior authorCorresponding

• Effective Routing and Scheduling Strategies for Fault-Tolerant Time-Sensitive Networking

  IEEE Internet of Things Journal · 2023-10-31 · 22 citations

  articleSenior author

  Time-sensitive networking (TSN) Task Group of the IEEE proposed the frame replication and elimination for reliability (FRER) technique to guarantee reliable transmissions in TSN for the emerging Industrial Internet of Things (IIoT). FRER is a technique that manages the replication and elimination of frames of a stream sent through multiple paths as member streams. However, the standard does not specify how to find and select the multiple paths to send the replicated member streams on, nor how th…

  PublisherDOI

• RECAP: 3D Traffic Reconstruction

  2024-12-04 · 5 citations

  articleOpen accessSenior author

  On-vehicle 3D sensing technologies, such as LiDARs and stereo cameras, enable a novel capability, 3D traffic reconstruction. This produces a volumetric video consisting of a sequence of 3D frames capturing the time evolution of road traffic. 3D traffic reconstruction can help trained investigators reconstruct the scene of an accident. In this paper, we describe the design and implementation of RECAP, a system that continuously and opportunistically produces 3D traffic reconstructions from multip…

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: CNS Core: Medium: Network-Enabled Cooperative Perception for Future Autonomous Vehicles

  NSF · $900k · 2020–2026

• NetSE: Medium: Collaborative Research: Green Edge Networks

  NSF · $600k · 2009–2013

• CPS: Synergy: Collaborative Research: Harnessing the Automotive Infoverse

  NSF · $467k · 2013–2019

Frequent coauthors

• Deborah Estrin

  Cornell University

  95 shared

• Hang Qiu

  University of California, Riverside

  46 shared

• Jeongyeup Paek

  Chung-Ang University

  45 shared

• Gaurav S. Sukhatme

  45 shared

• Scott Shenker

  University of California, Berkeley

  44 shared

• Marcos A. M. Vieira

  Universidade Federal de Minas Gerais

  38 shared

• Krishna Chintalapudi

  Microsoft (United States)

  36 shared

• John Heidemann

  33 shared

Labs

• Artificial Intelligence, Machine Learning, Privacy/FATEPI

Education

• Ph.D., Computer Science

  University of Southern California

  1995

• M.S., Computer Science

  University of Southern California

  1991

• B.S., Electrical and Electronics Engineering

  University of Madras

  1988

Awards & honors

• 2014 Indian Institute of Technology Distinguished Alumnus Aw…
• 2014 Institution of Electrical and Electronics Engineers Fel…
• 2014 Internet Research Task Force (IRTF) Applied Networking…
• 2011 Association of Computing Machinery Fellow of the ACM
• 2008 IEEE Symposium on Information Processing in Sensor Netw…

Similar researchers at University of Southern California

• Jonathan Gratchh-82
• Muhao Chenh-74
• Ewa Deelmanh-73