Short Bio
I received my Bachelor's degree in Mechatronics Engineering from Lovely Professional University in 2022. Throughout my academic journey, I have immersed myself in diverse projects, honing my expertise in electromechanical systems. From integrating hybrid powertrain systems in vehicles to optimizing data acquisition through sensor integration, my experiences have shaped my problem-solving abilities and inspired me to seek solutions to real-world challenges.
In addition to my engineering pursuits, I am deeply committed to promoting experiential learning and practical experience in robotics and AI education. I firmly believe in the power of education to transform lives and nurture curious minds. Thus, I actively advocate for STEAM (Science, Technology, Engineering, Arts, and Mathematics) education, crafting educational robots that empower and inspire the next generation of learners.
My current research endeavors focus on the fascinating world of computer vision and deep learning. By leveraging advanced algorithms such as YOLOv8 and Swin transformers,
Technical Skills & Software
Simulation Software: Proteus, TinkerCad, Simulink, LTspics, Yenka, Mbed
PCB Designing Software: Altium, EasyEDA, KiCAD, Eagle
Mechanical CAD Software: Creo Parametric, SolidWorks, Fusion 360
Programming Language: C, C++, Python, MATLAB, Assembly Language, Verilog
Operating System: Linux(Kali Linux, Parrot OS, Ubuntu), Windows
Version Control: Git, GitHub
Hardware Specialization: STM32, Arduino, Raspberry Pi, FPGA
Machine Learning Skills: SVMs, Decision Tress, Random Forests, Naive Bisayan, Clustering, Regression
Libraries: Numpy, Pandas, SciPy, Scikit-Learn, Keras, OpenCV, PyTorch, Matplotlib, Seaborn
Other tools: Docker, GDB, VMware, Oracle VM VirtualBox, Latex