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e030_Khushi_ PandeEP
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e030_Khushi_ Pande

@e030_khushi_pande

Electronics and telecommunication engineering undergraduate at Team Aryans Racing, who designed embedded vehicle data acquisition systems for real-time performance monitoring.

India
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What I'm looking for

I'm seeking an entry-level engineering opportunity where I can apply circuit design, embedded programming, simulation, and debugging skills in a product-focused environment.

At Team Aryans Racing, I designed and implemented embedded data acquisition systems for real-time vehicle performance monitoring, integrating sensors through SPI, I2C, and UART.

I assembled and tested prototype hardware, debugging circuits and wiring to support reliable data capture under real-world conditions. I also applied automobile engineering fundamentals to sensor placement and data logging strategy.

For the Vehicle Data Acquisition Systems project, I developed an RPM and speed logger with UART data transfer and an I2C-based acceleration measurement setup.

I'm currently developing a vision-based hazard and person detection system for a search-and-rescue rover. I trained and evaluated a YOLO11n model on a custom six-class dataset, achieving 0.45 mAP@0.50 on the validation set, and am working on GUI integration and inference benchmarking.

Experience

Work history, roles, and key accomplishments

Education

Degrees, certifications, and relevant coursework

GS

Government College of Engineering, Chhatrapati Sambhajinagar

B.Tech, Electronics & Telecommunication Engineering

2023 -

Grade: 8.43 CGPA

Pursuing a B.Tech in Electronics & Telecommunication Engineering with a CGPA of 8.43.

JA

Jawahar Navodaya Vidyalaya, Amravati

SSC and HSC, General Studies

2015 - 2022

Grade: SSC: 93%, HSC: 94.5%

Completed secondary and higher secondary education with 93% in SSC and 94.5% in HSC.

NI

NVIDIA Deep Learning Institute

Certificate, Deep Learning

Completed the NVIDIA Deep Learning Institute course on Getting Started with Deep Learning.

NI

NVIDIA Deep Learning Institute

Certificate, Data Science

Completed the NVIDIA Deep Learning Institute course on Accelerating End-to-End Data Science Workflows.

Tech stack

Software and tools used professionally

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