Kooshan Maleki

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Hello! I’m Kooshan Maleki, a senior undergraduate student in Computer Engineering at Amirkabir University of Technology . I’m deeply passionate about weaving together quantum computing, machine learning, and robotics to tackle real-world challenges—from building more efficient autonomous systems to enhancing medical diagnostics with advanced algorithms. I love discovering new ways to bridge theory and practice, collaborating across disciplines, and pushing the boundaries of what emerging technologies can achieve.

Location: Tehran, Iran

Education

B.Sc. in Computer Engineering

Institution: Amirkabir University of Technology (2021 – Present)

GPA: 19.00/20, ranked 4th among over 100 students.

Diploma

Institution: Allameh Helli High School (NODET) (2017 – 2021)

GPA: 19.40/20

Research Experience

Advisors: Prof. Farrokh Janabi-Sharif (Toronto Metropolitan University), Prof. Negar Ashari (Amirkabir University of Technology)

  • Investigating quantum algorithms (HHL) to enhance robotic pathfinding and decision-making.
  • Implementing quantum phase estimation & Hamiltonian simulation for navigation.
  • Analyzing scalability and efficiency in dynamic, complex environments.
  • Exploring hybrid quantum-classical approaches for real-time applications.

Industrial Experience

Website: https://mfp.co.ir

  • Developed a machine vision system for heart ultrasound images using OpenCV and ML.
  • Collaborated with Shahid Rajaei Hospital to gather real-world medical data.
  • Built interactive UIs with PySide6 & Matplotlib, visualizing ultrasound data.

Selected Projects

Teaching Experience

  • Special Topics in Quantum Computing (Grad, Head TA) Spring 2025
  • Microprocessors and Assembly (Head TA) Spring 2025
  • Computer Networks Fall 2024, Spring 2025
  • Applied Linear Algebra Fall 2024
  • Computer Architecture Spring 2024, Spring 2025
  • Algorithm Design Spring 2023
  • Logic Circuits Spring 2023

Trained students for the Iranian Physics Olympiad, focusing on deep conceptual understanding.

Certifications and Specialized Courses

Institution: The Coding School

  • Studied quantum computing fundamentals: qubits, superposition, entanglement.
  • Implemented Deutsch-Jozsa algorithm on quantum simulators.
QubitXQubit Certificate Preview

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Institution: Stanford University (Coursera)

  • Focus on regression, classification, and regularization.
  • Hands-on projects with Scikit-Learn.
Supervised ML Certificate

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Institution: Stanford University (Coursera)

  • Mastered neural network architectures and deep learning optimization.
  • Built models using TensorFlow & Keras for classification tasks.
NN & DL Certificate

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Honors and Awards

Skills and Competencies

Languages