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Computer Science

D-Index
37
Citations
5341
World Ranking
10834
National Ranking
4511

Research.com Recognitions

  • 2021 - IEEE Fellow For contributions to machine learning based cybersecurity for critical infrastructures
  • 2019 - Anthony J. Hornfeck Service Award

Overview

Milos Manic is affiliated with Virginia Commonwealth University in the United States and has a research focus that spans multiple subfields within computer science and engineering. Their work primarily intersects areas such as artificial intelligence, control and systems engineering, and computer networks and communications.

The main fields of study for Manic include:

  • Computer Science
  • Engineering

Their subfields of study cover:

  • Artificial Intelligence
  • Control and Systems Engineering
  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition

The core topics of their research work focus on:

  • Anomaly Detection Techniques and Applications
  • Network Security and Intrusion Detection
  • Smart Grid Security and Resilience
  • Explainable Artificial Intelligence (XAI)
  • EEG and Brain-Computer Interfaces
  • Advanced Memory and Neural Computing
  • Neural Networks and Applications

Manic has contributed to recent papers including:

  • "ResNet Autoencoders for Unsupervised Feature Learning From High-Dimensional Data: Deep Models Resistant to Performance Degradation" (2021, IEEE Access)
  • "An Artificial Intelligence Approach for Real-Time Tuning of Weighting Factors in FCS-MPC for Power Converters" (2021, IEEE Transactions on Industrial Electronics)
  • "Explainable Unsupervised Machine Learning for Cyber-Physical Systems" (2021, IEEE Access)
  • "Anomaly Detection in Critical-Infrastructures using Autoencoders: A Survey" (2022, IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society)
  • "IECON 2023: 49th Annual Conference of the IEEE Industrial Electronics Society" (2023, IEEE Industrial Electronics Magazine)

Frequent co-authors in their work include:

  • Daniel Marino
  • Chathurika S. Wickramasinghe
  • Daswin De Silva
  • Craig Rieger
  • Harindra S. Mavikumbure

Their publications often appear in venues such as:

  • IEEE Access
  • IEEE Industrial Electronics Magazine
  • Applied System Innovation
  • arXiv (Cornell University)
  • Energies

Manic has been recognized with awards including:

  • IEEE Fellow in 2021, for contributions to machine learning based cybersecurity for critical infrastructures
  • Anthony J. Hornfeck Service Award in 2019

Best Publications

  • Building energy load forecasting using Deep Neural Networks

    Daniel L. Marino;Kasun Amarasinghe;Milos Manic

  • Deep neural networks for energy load forecasting

    Kasun Amarasinghe;Daniel L. Marino;Milos Manic

  • CIMS: a framework for infrastructure interdependency modeling and analysis

    Donald D. Dudenhoeffer;May R. Permann;Milos Manic

  • Neural Network based Intrusion Detection System for critical infrastructures

    Ondrej Linda;Todd Vollmer;Milos Manic

  • Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions

    Bishnu P. Bhattarai;Sumit Paudyal;Yusheng Luo;Manish Mohanpurkar

  • Building Energy Management Systems: The Age of Intelligent and Adaptive Buildings

    Milos Manic;Dumidu Wijayasekara;Kasun Amarasinghe;Juan J. Rodriguez-Andina

  • General Type-2 Fuzzy C-Means Algorithm for Uncertain Fuzzy Clustering

    O. Linda;M. Manic

  • Uncertainty-Robust Design of Interval Type-2 Fuzzy Logic Controller for Delta Parallel Robot

    O. Linda;M. Manic

  • Mining Building Energy Management System Data Using Fuzzy Anomaly Detection and Linguistic Descriptions

    Dumidu Wijayasekara;Ondrej Linda;Milos Manic;Craig G. Rieger

  • An Adversarial Approach for Explainable AI in Intrusion Detection Systems

    Daniel L. Marino;Chathurika S. Wickramasinghe;Milos Manic

  • Network traffic monitoring devices and monitoring systems, and associated methods

    Kurt Derr;Milos Manic

  • Intelligent Buildings of the Future: Cyberaware, Deep Learning Powered, and Human Interacting

    Milos Manic;Kasun Amarasinghe;Juan J. Rodriguez-Andina;Craig Rieger

  • Toward Explainable Deep Neural Network Based Anomaly Detection

    Kasun Amarasinghe;Kevin Kenney;Milos Manic

  • Multi-robot, multi-target Particle Swarm Optimization search in noisy wireless environments

    Kurt Derr;Milos Manic

  • Interval Type-2 fuzzy voter design for fault tolerant systems

    Ondrej Linda;Milos Manic

  • Generalization of Deep Learning for Cyber-Physical System Security: A Survey

    Chathurika S. Wickramasinghe;Daniel L. Marino;Kasun Amarasinghe;Milos Manic

  • Deep Learning and Reconfigurable Platforms in the Internet of Things: Challenges and Opportunities in Algorithms and Hardware

    Roberto Fernandez Molanes;Kasun Amarasinghe;Juan Rodriguez-Andina;Milos Manic

  • Cyber-Physical System Security With Deceptive Virtual Hosts for Industrial Control Networks

    Todd Vollmer;Milos Manic

  • Fuzzy logic based anomaly detection for embedded network security cyber sensor

    Ondrej Linda;Milos Manic;Todd Vollmer;Jason Wright

  • Self-Organizing Fuzzy Haptic Teleoperation of Mobile Robot Using Sparse Sonar Data

    O. Linda;M. Manic

  • Wireless Sensor Networks—Node Localization for Various Industry Problems

    Kurt Derr;Milos Manic

  • Vulnerability identification and classification via text mining bug databases

    Dumidu Wijayasekara;Milos Manic;Miles McQueen

  • ResNet Autoencoders for Unsupervised Feature Learning From High-Dimensional Data: Deep Models Resistant to Performance Degradation

    Chathurika S. Wickramasinghe;Daniel L. Marino;Milos Manic

Frequent Co-Authors

Bogdan M. Wilamowski
Bogdan M. Wilamowski Auburn University
Enrique Herrera-Viedma
Enrique Herrera-Viedma University of Granada
Hui Yu
Hui Yu University of Portsmouth
Lucia Lo Bello
Lucia Lo Bello University of Catania
Xinghuo Yu
Xinghuo Yu RMIT University
Oscar Lucia
Oscar Lucia University of Zaragoza
Aldo Boglietti
Aldo Boglietti Polytechnic University of Turin
Sergio Vazquez
Sergio Vazquez University of Seville
Huijun Gao
Huijun Gao Harbin Institute of Technology
Leopoldo G. Franquelo
Leopoldo G. Franquelo University of Seville

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