Embedded Files
Brief Introduction
Brief Introduction
My curiosity for electrical systems began while working with my father in his mechanic shop. Watching him disassemble complex machinery and hearing his explanations of how parts functioned inspired me to pursue engineering. This hands-on upbringing shaped my problem-solving mindset and fueled my passion for repairing electronics and understanding the mechanics behind modern technology.
Technical Skills
Technical Skills
AI & Data Science:
Computer Vision, Transfer Learning, Data Augmentation, Model Evaluation, NumPy, Pandas, Matplotlib/Seaborn, Scikit-Learn, PyTorch
Embedded & Hardware:
Oscilloscope, Logic Analyzer, Multimeter, Function Generator, PID Tuning, Feedback Control Systems, UART, I2C, PWM, GPIO Configuration
FPGA & Digital Design:
SystemVerilog, Xilinx Vivado, Digital Signal Processing (DSP), Timing Analysis
Industry/Manufacturing:
Root Cause Analysis, Cleanroom Protocols, Semiconductor Manufacturing
Career Objective
Career Objective
Electrical Engineer & Master’s Candidate (M.S. EE)
Specialized in Embedded Systems, FPGA Design, and Computer Vision. I combine strong academic foundations in signal processing with 5+ years of high-precision industry experience at Intel. I am seeking a role where I can leverage my expertise in hardware-software integration to design robust, innovative electronic systems.
Academic Projects
Academic Projects
Description: Developed a fine-grained vehicle classification system using OpenAI’s CLIP model. Achieved 85% accuracy in distinguishing specific car generations and parts by engineering a hierarchical classification logic and a custom data pipeline.
Tech Stack: Python, PyTorch, OpenAI CLIP, Pandas, Scikit-Learn.
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