My research covers a broad range of topics in hardware and software design, optimization and verification. The following are my main focus, however please refer to my Google Scholar profile for a more complete list of my research topics.

  • Rumor Detection: VRoC: Variational Autoencoder-aided Multi-task Rumor Classifier Based on Text
  • Intelligent Task Scheduling for Cloud and Data Centers: H2O-Cloud: A Resource and Quality of Service-Aware Task Scheduling Framework for Warehouse-Scale Data Centers - A Hierarchical Hybrid DRL (Deep Reinforcement Learning) based Approach
  • An Intelligent Design, Optimization and Verification Framework in Superconducting Technologies. The optimization includes clock gating. The verificaiton flow includes deep reinforcement learning to identify the faulty states and neural networks to identify the source of design errors. It also includes a simple clock network verification
  • Secure Manycore System-on-Chip: S4oC: A Self-optimizing, Self-adapting Secure System-on-Chip Design Framework to Tackle Unknown Threats--A Network Theoretic, Learning Approach
  • Prediction-Based Fast Thermoelectric Generator Reconfiguration for Energy Harvesting from Vehicle Radiators
  • SpRRAM: A Predefined Sparsity Based Memristive Neuromorphic Circuit for Low Power Application
  • Normalization and dropout for stochastic computing-based deep convolutional neural networks
  • TEI-power: Temperature Effect Inversion–Aware Dynamic Thermal Management
  • Ph.D. Studies : Those interested, please send an email to Include your C.V. and highlight your prior academic achievements, especially those related to mathematics and algorithms (your undergraduate academic rank, nation-wide award, etc.)

    Directed Research : Graduate EE790/EE590 and undergraduate EE490.

    Shahin Nazarian's ResearchGate

    Shahin Nazarian's Google Scholar

    Shahin Nazarian's IEEE Author Page