World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
11776
World Ranking
6097
National Ranking
2743

Electronics and Electrical Engineering

D-Index
45
Citations
10894
World Ranking
3480
National Ranking
1284

Research.com Recognitions

  • 2014 - IEEE Fellow For contributions to the modeling, design, and analysis of wireless networks

Overview

Sanjay Shakkottai is affiliated with The University of Texas at Austin in the United States. Their primary areas of research span Computer Science and Decision Sciences, with a significant focus on subfields including Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications, Electrical and Electronic Engineering, and Computer Vision and Pattern Recognition.

The scientist's research topics cover a range of advanced areas such as:

  • Advanced Bandit Algorithms Research
  • Reinforcement Learning in Robotics
  • Optimization and Search Problems
  • Domain Adaptation and Few-Shot Learning
  • Stochastic Gradient Optimization Techniques
  • Machine Learning and Algorithms
  • Smart Grid Energy Management

Among recent published papers are:

  • "Exploiting Shared Representations for Personalized Federated Learning", 2021, arXiv (Cornell University)
  • "FedAvg with Fine Tuning: Local Updates Lead to Representation Learning", 2022, arXiv (Cornell University)
  • "A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants", 2021, arXiv (Cornell University)
  • "Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex Envelopes", 2020, arXiv (Cornell University)
  • "Task-Robust Model-Agnostic Meta-Learning", 2020, arXiv (Cornell University)

Frequent co-authors in their research include:

  • Constantine Caramanis
  • Aryan Mokhtari
  • Karthikeyan Shanmugam
  • Daniel Vial
  • R. Srikant

Shakkottai's body of work is often published in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the ACM on Measurement and Analysis of Computing Systems
  • ACM SIGMETRICS Performance Evaluation Review
  • Operations Research
  • IEEE Transactions on Automatic Control

Recognition for contributions to the field includes being named an IEEE Fellow in 2014, cited specifically for work in modeling, design, and analysis of wireless networks.

Best Publications

  • Cross-layer design for wireless networks

    S. Shakkottai;T.S. Rappaport;P.C. Karlsson

  • Unreliable sensor grids: coverage, connectivity and diameter

    Sanjay Shakkottai;R. Srikant;Ness B. Shroff

  • Unreliable sensor grids: coverage, connectivity and diameter

    S. Shakkottai;R. Srikant;N. Shroff

  • FlashLinQ: a synchronous distributed scheduler for peer-to-peer ad hoc networks

    Xinzhou Wu;Saurabha Tavildar;Sanjay Shakkottai;Tom Richardson

  • Scheduling algorithms for a mixture of real-time and non-real-time data in HDR

    Sanjay Shakkottai;Sanjay Shakkottai;Alexander L. Stolyar

  • Hop-by-hop congestion control over a wireless multi-hop network

    Yung Yi;S. Shakkottai

  • Hop-by-hop congestion control over a wireless multi-hop network

    Yung Yi;Sanjay Shakkottai

  • Scheduling for multiple flows sharing a time-varying channel: the exponential rule

    Unknown

  • On combining shortest-path and back-pressure routing over multihop wireless networks

    Lei Ying;Sanjay Shakkottai;Aneesh Reddy;Shihuan Liu

  • Scheduling real-time traffic with deadlines over a wireless channel

    Sanjay Shakkottai;R. Srikant

  • Rethinking information theory for mobile ad hoc networks

    J. Andrews;S. Shakkottai;R. Heath;N. Jindal

  • Joint Scheduling of URLLC and eMBB Traffic in 5G Wireless Networks

    Arjun Anand;Gustavo de Veciana;Sanjay Shakkottai

  • FlashLinQ: A synchronous distributed scheduler for peer-to-peer ad hoc networks

    Xinzhou Wu;Saurabh Tavildar;Sanjay Shakkottai;Tom Richardson

  • On Combining Shortest-Path and Back-Pressure Routing Over Multihop Wireless Networks

    L. Ying;S. Shakkottai;A. Reddy

  • Joint Scheduling of URLLC and eMBB Traffic in 5G Wireless Networks

    Arjun Anand;Gustavo De Veciana;Sanjay Shakkottai

  • On the design of device-to-device autonomous discovery

    Francois Baccelli;Nilesh Khude;Rajiv Laroia;Junyi Li

  • Pathwise optimality of the exponential scheduling rule for wireless channels

    Sanjay Shakkottai;R. Srikant;Alexander L. Stolyar

  • Effective Capacity and QoS for Wireless Scheduling

    S. Shakkottai

  • How good are deterministic fluid models of Internet congestion control

    S. Shakkottai;R. Srikant

  • On Wireless Scheduling With Partial Channel-State Information

    A. Gopalan;C. Caramanis;S. Shakkottai

  • Min-cost Selfish Multicast with Network Coding

    S. Bhadra;S. Shakkottai;P. Gupta

Frequent Co-Authors

Sujay Sanghavi
Sujay Sanghavi The University of Texas at Austin
Constantine Caramanis
Constantine Caramanis The University of Texas at Austin
R. Srikant
R. Srikant University of Illinois at Urbana-Champaign
Xinzhou Wu
Xinzhou Wu Qualcomm (United States)
Junyi Li
Junyi Li Qualcomm (United States)
Lei Ying
Lei Ying University of Michigan–Ann Arbor
Tom Richardson
Tom Richardson Qualcomm (United States)
Yung Yi
Yung Yi Korea Advanced Institute of Science and Technology
Alexandros G. Dimakis
Alexandros G. Dimakis The University of Texas at Austin

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