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Computer Science

D-Index
39
Citations
4822
World Ranking
9900
National Ranking
4158

Overview

Kumara Sastry is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research primarily spans the field of engineering, with a specific focus on electrical and electronic engineering, artificial intelligence, biomedical engineering, statistical and nonlinear physics, and computational mechanics.

Their work covers a range of topics that include:

  • Advancements in photolithography techniques
  • Model reduction and neural networks
  • Advanced numerical methods in computational mathematics
  • Welding techniques and residual stresses
  • Industrial vision systems and defect detection
  • Electron and X-ray spectroscopy techniques
  • Machine learning and algorithms

Kumara Sastry has published research in several venues, with frequent contributions to:

  • arXiv (Cornell University)
  • Proceedings of the 59th ACM/IEEE Design Automation Conference
  • International Journal of Development Research

Some of the recent papers by Kumara Sastry include:

  • Generic lithography modeling with dual-band optics-inspired neural networks, 2022, Proceedings of the 59th ACM/IEEE Design Automation Conference
  • Large Scale Mask Optimization Via Convolutional Fourier Neural Operator and Litho-Guided Self Training, 2022, arXiv (Cornell University)
  • An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design, 2022, arXiv (Cornell University)
  • Generic Lithography Modeling with Dual-band Optics-Inspired Neural Networks, 2022, arXiv (Cornell University)
  • Classification of colon cancer by using cnn and capsule neural network, 2023, International Journal of Development Research

Kumara Sastry frequently collaborates with several co-authors, many of whom have co-authored four publications with them each. The identified frequent co-authors are:

  • Zongyi Li
  • Saumyadip Mukhopadhyay
  • Anima Anandkumar
  • Brucek Khailany
  • Haoxing Ren

Best Publications

  • Scalable Optimization via Probabilistic Modeling

    Martin Pelikan;Kumara Sastry;Erick Cantu-Paz

  • Scalable optimization via probabilistic modeling : from algorithms to applications

    Martin Pelikan;Kumara Sastry;Erick Cantú-Paz

  • Estimation of heat transfer parameters in a trickle-bed reactor using differential evolution and orthogonal collocation

    B.V Babu;K.K.N Sastry

  • Linkage Learning via Probabilistic Modeling in the Extended Compact Genetic Algorithm (ECGA)

    Georges R. Harik;Fernando G. Lobo;Kumara Sastry

  • Evaluation-Relaxation Schemes for Genetic and Evolutionary Algorithms

    Kumara Sastry;Martin Pelikan;Prasanna Parthasarathy;Ravi Srivastava

  • Scalability of the Bayesian optimization algorithm

    Martin Pelikan;Kumara Sastry;David E. Goldberg

  • Probabilistic Model Building and Competent Genetic Programming

    Kumara Sastry;David E. Goldberg

  • Combating user fatigue in iGAs: partial ordering, support vector machines, and synthetic fitness

    Xavier Llorà;Kumara Sastry;David E. Goldberg;Abhimanyu Gupta

  • Multiobjective hBOA, clustering, and scalability

    Martin Pelikan;Kumara Sastry;David E. Goldberg

  • Using previous models to bias structural learning in the hierarchical boa

    M. W. Hauschild;M. Pelikan;K. Sastry;D. E. Goldberg

  • Don't evaluate, inherit

    Kumara Sastry;David E. Goldberg;Martin Pelikan

  • Dependency structure matrix, genetic algorithms, and effective recombination

    Tian-Li Yu;David E. Goldberg;Kumara Sastry;Claudio F. Lima

  • Bayesian optimization algorithm, decision graphs, and Occam's razor

    Martin Pelikan;David E. Goldberg;Kumara Sastry

  • Fitness inheritance in multi-objective optimization

    Jian-Hung Chen;David E. Goldberg;Shinn-Ying Ho;Kumara Sastry

  • A practical schema theorem for genetic algorithm design and tuning

    David E. Goldberg;Kumara Sastry

  • Fitness Inheritance in the Bayesian Optimization Algorithm

    Martin Pelikan;Kumara Sastry

  • Designing Competent Mutation Operators Via Probabilistic Model Building of Neighborhoods

    Kumara Sastry;David E. Goldberg

  • Tournament selection: stable fitness pressure in XCS

    Martin V. Butz;Kumara Sastry;David E. Goldberg

  • On the supply of building blocks

    David E. Goldberg;Kumara Sastry;Thomas Latoza

  • Multiobjective Estimation of Distribution Algorithms

    Martin Pelikan;Kumara Sastry;David E. Goldberg

  • Genetic and Evolutionary Computation Conference 2008 : GECCO 2008

    Maarten Keijzer;Giuliano Antoniol.;Clare Bates Congdon;Kalyanmoy Deb

Frequent Co-Authors

David E. Goldberg
David E. Goldberg University of Illinois at Urbana-Champaign
Martin Pelikan
Martin Pelikan University of Missouri
Duane D. Johnson
Duane D. Johnson Iowa State University
Pier Luca Lanzi
Pier Luca Lanzi Polytechnic University of Milan
Martin V. Butz
Martin V. Butz University of Tübingen
Hussein A. Abbass
Hussein A. Abbass University of New South Wales
Pascal Bellon
Pascal Bellon University of Illinois at Urbana-Champaign
Erick Cantú-Paz
Erick Cantú-Paz Amazon (United States)
James L. Kennedy
James L. Kennedy Centre for Addiction and Mental Health

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