My single-page CV

Education

  • Georgia Institute of Technology
    Ph.D., Computer Science | Aug. 14 – Aug. 21
    Adviser: Hyesoon Kim, HPArch
    Thesis: Deploying Deep Neural Networks in Edge with Distribution
    GPA: 4.00/4.00

  • Georgia Institute of Technology
    M.Sc., Computer Science | Aug. 14 – May. 18
    Computing System Specialization
    GPA: 4.00/4.00

  • Sharif University of Technology
    B.Sc., Electrical Engineering | Sept. 9 – Aug. 14
    Major in Digital Systems
    Major GPA: 4.00/4.00

Experience

  • Applied Machine Learning Researcher
    Rain | Mar. 23 – Present

  • Machine Learning Researcher, Advanced Systems Technology Team
    SK hynix | Feb. 21 – Feb. 23

  • Research Assistant, HPArch
    Georgia Tech | Feb. 15 – Aug. 21

  • Instructor, Advanced Computer Organization CS4290
    Georgia Tech | May. 20 – Aug. 20

  • Instructor, Advanced Computer Organization CS4290
    Georgia Tech | May. 19 – Aug. 19

  • SWE Intern, Video Understanding Team
    Google | May. 18 – Aug. 18

  • Coordinator and Administrator, Microprocessor Systems Lab,
    Sharif University of Technology | May 13 – May 14

Honors

  • Best Paper Nominee, IISWC’21 (Nov. 21)
  • DAC’20 Young Fellow Participant & Research Video Awardee (Aug. 20)
  • Best Paper Nominee, IISWC’19 (Nov. 18)
  • Ranked 3rd, Sharif University - B.Sc. in Electrical Engineering (Sept. 9 – Aug. 14)
  • Silver Medal Winner of 3rd IOAA (International Olympiad on Astrophysics) (Oct. 9)
  • Gold Medal Winner in National Astrophysics Olympiad, Iran (Aug. 8)
  • Silver Medal Winner in National Astrophysics Olympiad, Iran (Aug. 7)
  • National Physics Olympiad Finalist, Iran (Feb. 8)

Mentoring & Teaching Experience

Skills/Expertise

Core Expertise

  • Applied Machine Learning & Deep Neural Networks
  • Edge AI & Internet of Things (IoT)
  • Computer Architecture
  • In/Near Memory Computation & 3D-Stacked Architectures
  • CPU and GPU Microarchitecture & Optimizations
  • Robotics, Drones & Autonomous Vehicles
  • Desing-Space Exploration for Hardware Accelerators
  • Hardware/Software Co-Design for Machine Learning
  • Hardware Optimized for Sparsity (ML and Scientific Computation)
  • Hardware for Recommendation Systems
  • Hardware for Large Language Models & Transformers
  • AI Hardware Development & Optimization
  • Distributed Computing & Parallelization Techniques
  • FPGA Development and Deployment (Verilog & HDL)
  • High-Performance Computing (HPC), Graph Processing & GPUs
  • Video Understanding & Computer Vision
  • Patent Development & Intellectual Property Strategy
  • Public Speaking & Technical Communication
  • Production Hardware Profiling for Competitive Analysis

Technical Skills

  • Languages: C, C++, Python, Bash, Verilog, TCL, HLS, MATLAB, CUDA
  • Frameworks: PyTorch, TensorFlow, TensorRT, TensorFlow Lite, ONNX, Keras
  • Tools & Platforms: Vivado, ModelSim, Docker, Git, Jupyter Notebooks, Linux, Windows, ROS
  • Data & Visualization: Pandas, NumPy/SciPy, Matplotlib/Seaborn, Plotly, OpenGL
  • Edge AI & IoT: NVIDIA Jetsons, Raspberry Pi, Arduino, ARM, Qualcomm
  • HDL & HPC: UVM, CUDA/OpenCL, MPI, OpenMP