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Computer Science

D-Index
33
Citations
6773
World Ranking
12457
National Ranking
5053

Overview

Haris Vikalo is affiliated with The University of Texas at Austin in the United States. Their research primarily spans the fields of computer science, engineering, and biochemistry, genetics, and molecular biology, with a notable concentration in artificial intelligence, computer networks and communications, and molecular biology.

Their academic output includes numerous papers focusing on privacy-preserving technologies, stochastic gradient optimization techniques, distributed control in multi-agent systems, genomics and phylogenetic studies, traffic prediction and management, radar systems and signal processing, and recommender systems.

Frequent co-authors include Abolfazl Hashemi, Ziqi Ke, Mónica Ribero, Yiyue Chen, and Shorya Consul. Vikalo's work is regularly published in venues such as arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence, IEEE Transactions on Automatic Control, bioRxiv (Cold Spring Harbor Laboratory), and IEEE Journal of Selected Topics in Signal Processing.

Selected recent papers include:

  • Real-Time Radio Technology and Modulation Classification via an LSTM Auto-Encoder, 2021, IEEE Transactions on Wireless Communications
  • Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better, 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints, 2022, IEEE Journal of Selected Topics in Signal Processing
  • Federating recommendations using differentially private prototypes, 2022, Pattern Recognition
  • On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Federated Learning, 2021, IEEE Transactions on Parallel and Distributed Systems

Best Publications

  • On the sphere-decoding algorithm I. Expected complexity

    B. Hassibi;H. Vikalo

  • Iterative decoding for MIMO channels via modified sphere decoding

    H. Vikalo;B. Hassibi;T. Kailath

  • Greedy sensor selection: Leveraging submodularity

    Manohar Shamaiah;Siddhartha Banerjee;Haris Vikalo

  • On the sphere-decoding algorithm II. Generalizations, second-order statistics, and applications to communications

    H. Vikalo;B. Hassibi

  • Beam tracking for mobile millimeter wave communication systems

    Vutha Va;Haris Vikalo;Robert W. Heath

  • Rate maximization in multi-antenna broadcast channels with linear preprocessing

    M. Stojnic;H. Vikalo;B. Hassibi

  • On the expected complexity of sphere decoding

    B. Hassibi;H. Vikalo

  • Recovering Sparse Signals Using Sparse Measurement Matrices in Compressed DNA Microarrays

    F. Parvaresh;H. Vikalo;S. Misra;B. Hassibi

  • Real-Time Radio Technology and Modulation Classification via an LSTM Auto-Encoder

    Ziqi Ke;Haris Vikalo

  • On the expected complexity of integer least-squares problems

    Babak Hassibi;Haris Vikalo

  • Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better

    Unknown

  • Energy efficient design of portable wireless systems

    T. Simunic;H. Vikalo;P. Glynn;G. De Micheli

  • Maximum-likelihood sequence detection of multiple antenna systems over dispersive channels via sphere decoding

    Haris Vikalo;Babak Hassibi

  • SDhaP: haplotype assembly for diploids and polyploids via semi-definite programming

    Shreepriya Das;Haris Vikalo

  • MIMO receive algorithms

    Thomas Kailath;Haris Vikalo;Babak Hassibi

  • Communication-Efficient Federated Learning via Optimal Client Sampling

    Monica Ribero;Haris Vikalo

  • Sphere-constrained ML detection for frequency-selective channels

    H. Vikalo;B. Hassibi;U. Mitra

  • On the capacity of frequency- selective channels in training-based transmission schemes

    H. Vikalo;B. Hassibi;B. Hochwald;T. Kailath

  • Multiplexed identification, quantification and genotyping of infectious agents using a semiconductor biochip

    Arjang Hassibi;Arun Manickam;Rituraj Singh;Sara Bolouki

  • Optimal training for frequency-selective fading channels

    H. Vikalo;B. Hassibi;B. Hochwald;T. Kailath

  • Efficient joint maximum-likelihood channel estimation and signal detection

    H. Vikalo;B. Hassibi;P. Stoica

Frequent Co-Authors

Babak Hassibi
Babak Hassibi California Institute of Technology
Ufuk Topcu
Ufuk Topcu The University of Texas at Austin
Sriram Vishwanath
Sriram Vishwanath The University of Texas at Austin
Thomas Kailath
Thomas Kailath Stanford University
Gustavo de Veciana
Gustavo de Veciana The University of Texas at Austin
José Luis Riechmann
José Luis Riechmann Institució Catalana de Recerca i Estudis Avançats
François Baccelli
François Baccelli French Institute for Research in Computer Science and Automation - INRIA
Urbashi Mitra
Urbashi Mitra University of Southern California
Ahmed H. Tewfik
Ahmed H. Tewfik The University of Texas at Austin
Sujay Sanghavi
Sujay Sanghavi The University of Texas at Austin

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