Kian Farooghi

M.Sc. in Control Systems | Machine Learning Researcher

K.N Toosi - Tehran, Iran

Email Phone Website

About Me

I am a results-driven Electrical Engineer with a Master's in Control Systems, specializing in reinforcement learning and data-driven control. I have proven hands-on coding experience in an industrial setting and have published research on algorithm development for Forex trading. I am seeking a PhD opportunity to further explore machine learning applications.

Research Interests

Reinforcement Learning Deep Learning System Identification Robotics

Education

M.Sc. in Electrical Engineering (Control)

K. N. Toosi University of Technology, Tehran, Iran | Sep 2021 – 2023
GPA: 4.0/4.0 (18.68/20)

Thesis: Forex Market Trading Strategy Based on Deep Reinforcement Learning

B.Sc. in Electrical Engineering (Control)

University of Tabriz, Tabriz, Iran | Sep 2016 – Jul 2021
GPA: 3.4/4.0 (16.58/20)

Publications

Determining the Most Lucrative Currency to Mine in Cryptocurrency Mining Farms

Kian Farooghi, Hamid Nemati, Hamid Khaloozadeh | Submitted

Using heuristic optimization and deep learning for financial time series forecasting in cryptocurrency mining and blockchain applications.

Heuristic Optimization Deep Learning Financial Time Series Cryptocurrency Blockchain

Cooperative Multi-Agent Deep Reinforcement Learning for Forex Algorithmic Trading

Kian Farooghi, Hamid Khaloozadeh | International Conference on Computational Intelligence and Applications (ICCIA), 2024

Implementation of Proximal Policy Optimization for multi-agent systems in algorithmic trading.

Deep Reinforcement Learning Multi-Agent Systems PPO Algorithmic Trading Forex

Deep Learning for Bitcoin Price Prediction: The Power of Transformers and Time2Vec

Reza Lak, Kian Farooghi, Hamid Khaloozadeh | First International Conference on Computer, Electricity, Mechanics and Engineering Sciences

Leveraging transformer architectures and Time2Vec for cryptocurrency price prediction.

Transformers Attention Time2Vec Bitcoin

Tabular Dyna-Q Algorithm for Online Calculation of LQR Gains

Kian Farooghi, Mahdieh Samadi, Hamid Khaloozadeh | International Conference on Electrical Engineering and Technology (ICEET), 2023

A simulation study on reinforcement learning approaches for optimal control and data-driven control systems.

Reinforcement Learning Dyna-Q Q-Learning Optimal Control LQR

Professional Experience

Embedded & C# Software Engineer

Sedna Organization | Jun 2023 - Present
  • Designed and deployed comprehensive C# GUI for BLDC motor drive testing with integrated real-time data acquisition and analysis pipelines, adopted by 10+ engineers and technicians to accelerate and standardize experimental workflows
  • Implemented distributed control framework using socket programming with role-based remote access, enabling secure multi-client motor operation and monitoring across network
  • Refactored ARM Cortex-M4 (Artery F413) firmware architecture for sensorless BLDC motor drives, redesigning code structure to improve maintainability, modularity, and debugging efficiency
  • Optimized motor control algorithms and execution paths, achieving 33% faster response time and 11% reduction in execution time through systematic firmware performance tuning
  • Generalized firmware architecture across product line by replacing hard-coded configurations with dynamic Modbus-based parameter system, enabling real-time tuning of 50+ parameters including floating-point values
  • Developed microcontroller-based auto-tuning algorithm for PI controllers in BLDC motors, recognized by Iranian government as qualifying research project (equivalent to completing military service requirement)
  • Project Repository: GUI Interface on GitHub

Lead Software Engineer

Agrin Company | Jan 2025 - Mar 2025
  • Led team of 3 programmers to develop multi-camera surveillance platform for long-term timelapse monitoring of skyscraper construction projects
  • Designed and implemented real-time panoramic stitching algorithm, combining dual-row camera feeds into seamless wide-angle view for comprehensive site coverage
  • Developed robust TCP/IP streaming pipeline ensuring continuous transmission of stitched and raw frames to central servers with minimal latency
  • Coordinated integration of motorized camera modules, image processing, and UI control systems, employing Python for orchestration and C for performance-critical components

Teaching Experience

K.N.TU | Spring 2024 (35+ students) & Spring 2023 (45+ students)

Head Teaching Assistant - Reinforcement Learning

Proposed homework questions and solved assigned problems in online class groups.

K.N.TU | Spring 2023 (45+ students)

Teaching Assistant - Multivariable Control

Designed and graded homework and quizzes.

K.N.TU | Fall 2022 (45+ students)

Head Teaching Assistant - Python Programming

Graded homework and quizzes; recorded screen while coding example questions.

K.N.TU | Fall 2022 (45+ students)

Teaching Assistant - Game Theory

Designed and graded homework assignments.

Faradars Institute (Online) | Fall 2021

Instructor - C-Sharp Web Scraping Course

Recorded a full programming course and designed questions based on video concepts.

Academic Projects

Heliostat Position Control in a Solar Power Plant using RL

Spring 2024

Python programming for training an agent to change heliostat positions to maximize power plant efficiency.

Deep RL Ping-Pong Player Agent

Spring 2023

Trained an agent using PyTorch to play ping-pong using visual input from the playground.

Dynamic Relative Gain Analysis

Fall 2022

MATLAB simulation for RGA calculation as part of Multivariable Control course with Dr. Ali Khaki Sedigh.

LQG Controller Design for Airplane System

Spring 2022

Implemented LQG controller using MATLAB and Simulink for Optimal Control course with Dr. Hamid Khaloozadeh.

Robust H∞ Control for Networked Systems

Fall 2021

Developed robust H∞ control strategy for Networked Control Systems (NCSs) with uncertainties in communication and system for Robust Control course with Dr. Mahsan Tavakoli-Kakhki.

Technical Skills

Programming Languages:
Python, MATLAB, C (ARM/STM32), C# (.NET/WPF), Bascom, SQL, Arduino
Platforms & Libraries:
PyTorch, Pandas, PyQt5, Selenium (C# and Python), BeautifulSoup, SQL Server Management Studio (SSMS), SQL Server, MySQL
Software:
Simulink, Proteus
Networking & Protocols:
Modbus, CAN, TCP/IP, UDP
Core Competencies:
Reinforcement Learning, Deep Learning, Heuristic Optimization Methods, Control Systems, Embedded Systems, Real-time Systems

Languages

  • English (TOEFL iBT: 109/120)
  • Kurdish (Native)
  • Persian (Bilingual)

Certifications & Honors

🏆 National Merit Recognition 2025

Microcontroller-based PI controller auto-tuning for next-generation water coolers developed for Sedna company. Approved as an alternative to compulsory military service by the Iranian government.

Certifications

  • SQL For Data Science
  • Supervised Machine Learning

References

Dr. Hamid Khaloozadeh

Department of Electrical Engineering

Khaje Nasir University of Technology

h_khaloozadeh@kntu.ac.ir

Hamid Nemati

Department of Computing Science

Umeå University

Researcher at WASP

hamid.nemati@umu.se

Dr. Amirhossain Nikoofard

Department of Electrical Engineering

Khaje Nasir University of Technology

a.nikoofard@kntu.ac.ir