TechRxiv

Parham Hadikhani

0000-0002-4832-4368

Computing and Processing; Robotics and Control Systems

I am a computer science Ph.D. student researching computer vision. I have been working on various domains such as routing protocols in wireless sensor networks, analyzing social media, applying unsupervised methods in computer vision, transferring knowledge in signal processing, and application of deep learning in chem informatics with the specialization in unsupervised deep learning, reinforcement learning, evolutionary algorithms, and artificial intelligence. Currently, I am working on 6 projects simultaneously including unsupervised human activity recognition, unsupervised deep clustering for image clustering, heart disease risk calculator using symbolic regression, unsupervised fault diagnosis, invention of a new evolutionary algorithm inspired by nature, and application of deep learning in scaffold decoration for drug discovery. My additional expertise and teaching interests are object-oriented programming, software engineering, and database systems.

Publications

  • https://scholar.google.com/citations?user=QK0TbcoAAAAJ&hl=en
  • An energy-aware and load balanced distributed geographic routing algorithm for wireless sensor networks with dynamic hole
  • Flexible Multi-Objective Particle Swarm Optimization Clustering with Game Theory to Address Human Activity Recognition Fully Unsupervised
  • Flexible Multi-Objective Particle Swarm Optimization Clustering with Game Theory to Address Human Activity Discovery Fully Unsupervised
  • Automatic Deep Sparse Multi-Trial Vector-based Differential Evolution Clustering with Manifold Learning and Incremental Technique
  • Human Activity Discovery with Automatic Multi-objective Particle Swarm Optimization Clustering with Gaussian Mutation and Game Theory
  • Human Activity Discovery with Automatic Multi-objective Particle Swarm Optimization Clustering with Gaussian Mutation and Game Theory
  • Human Activity Discovery with Automatic Multi-objective Particle Swarm Optimization Clustering with Gaussian Mutation and Game Theory
  • Human Activity Discovery with Automatic Multi-Objective Particle Swarm Optimization Clustering with Gaussian Mutation and Game Theory
  • A Novel Skeleton-Based Human Activity Discovery Using Particle Swarm Optimization With Gaussian Mutation

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