Dušan Grković

dusangrkovic2002@gmail.com | +38163514327

https://github.com/Grkila

Professional Summary

Fourth-year Control Systems Engineering student with a passion for robotics, embedded systems, and automation. Proficient in control algorithms, microcontroller programming, and computer vision, demonstrated through projects like robot manipulator simulations and IoT-based automation systems. Strong leadership and teamwork skills, developed as head organizer of events and HR team lead at EESTEC LC Novi Sad (2022–2023).

Education

Bachelor of Science in Control Systems Engineering
Faculty of Technical Sciences in Novi Sad, Novi Sad, Serbia
Relevant Coursework: Robotics, Embedded Systems, Industrial Automation, Signal Processing, Machine Learning
Academic Achievements: Consistently high academic record

Harvard CS50: Introduction to Computer Science
Online Certification, Completed 2022
Mastered foundational computer science concepts, including algorithms, data structures, and software development.

Altium education PCB basic design course
Online Certification, Completed 2025
Mastered foundational PCB design concepts including schematics design, PCB layout, routing skills and PCB manufacturing

NVIDIA Certificate of Competency: Fundamentals of Deep Learning
Online Certification, Completed June 25, 2024
Demonstrated competence in the core principles and practices of deep learning.

Technical Skills

Key Projects and Achievements

Robotics and Control Systems

Two-Joint Robot Manipulator Simulation

Technologies: MATLAB, Simulink, LabVIEW, FPGA

  • Developed software-in-the-loop (SIL) and hardware-in-the-loop (HIL) simulations, comparing PID, SMC, and Fuzzy control algorithms for optimized robotic arm performance.

Bluetooth-Controlled Rover

Technologies: ESP32, STM32, ESP-NOW, BLDC Motors

  • Designed a rover using ESP32 and STM32-based BLDC drivers with traction control, leveraging ESP-NOW for robust wireless communication.

Siemens PLC Programming

Technologies: Siemens TIA Portal, Ladder Logic

  • Completed practical projects applying Ladder Logic for industrial automation, demonstrating proficiency in PLC-based control.

Robotic Grasping System with Adaptive Force Control

Technologies: XMC4700, Arduino IDE, BLDC Motors, Fuzzy Logic, PID Control

  • Developed a complete smart robotic grasping system from concept to execution in a fast-paced, 24-hour team challenge.
  • Implemented a discrete PID controller to precisely manage the system's core control loop and motor actuation.
  • Designed and integrated a fuzzy logic inference engine for real-time PID gain tuning, enabling the system to intelligently adapt its grip force.
  • Engineered an algorithm to infer object hardness by processing real-time data from the hand's force sensors, providing the critical input for the adaptive grip.

Embedded Systems

Servo motor from cheap DC motor based on arduino

Technologies: Arduino, C, PWM

  • Engineered a low-cost servo controller using a brushed motor and Arduino Uno, achieving precise motion control.

Wi-Fi AC Remote with ESP8266

Technologies: ESP8266, C++

  • Built a remote control system with integrated temperature and humidity sensors, enabling smart home automation.

Bare-Metal Modbus Protocol

Technologies: Intel 8051, C, Modbus RTU

  • Implemented Modbus communication on an Intel 8051 microcontroller, ensuring reliable data exchange in resource-constrained environments.

Computer Vision and Machine Learning

OpenCV Parking Space Detection

Technologies: Python, OpenCV, Flask

  • Created a web application using OpenCV to detect available parking spaces in real-time, optimizing urban mobility.

Machine Learning Diabetes Prediction

Technologies: Python, Scikit-learn, Pandas

  • Developed a predictive model using machine learning to identify diabetes risk, achieving high accuracy on test datasets.

Stock Technical Indicator Calculation with MATLAB

Technologies: Matlab

  • This project provides a MATLAB script for calculating a range of financial technical indicators from stock market data. The script processes, normalizes, and structures this data into features and targets, designed to aid in market analysis or the development of predictive trading models.

Signal Processing and Software Development

Android Sensor Fusion Interface

Technologies: Android Studio, Java, Bluetooth

  • Designed an Android app for sensor fusion, interfacing with a microcontroller via Bluetooth for real-time data processing.

Noise Cancellation Analysis

Technologies: MATLAB, Signal Processing

  • Compared FFT-based noise cancellation in MATLAB with analog filter designs, evaluating performance trade-offs.

Edge Detection Filter in C

Technologies: C, Image Processing

  • Implemented an efficient image processing algorithm for edge detection, optimized for performance.

High-Frequency Derivatives Trading System

Technologies: Algorithmic Trading, WebSocket, JSON, JavaScript, Derivatives (Futures & Options)

  • Collaborated in a team of four to design and build a high-frequency trading system from the ground up during the intensive 24-hour AlgoTrade 2025 hackathon.
  • Engineered the system to execute strategies on futures and options by interfacing with a real-time, JSON-based WebSocket API.
  • Achieved a critical low-latency advantage by deploying the trading logic on a collocated Raspberry Pi for near-instant order execution.
  • Successfully managed a $1,000,000 virtual portfolio, applying robust risk management principles to maximize profit in a competitive simulated market.

Data Recovery for JPEG Images

Technologies: C, File Systems

  • Wrote a C program to recover JPEG images from raw binary dumps, demonstrating low-level data manipulation.

Leadership and Extracurricular Activities

Languages