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Amit P. AI, Machine Learning and Computer Vision Platforms

My name is Amit P. and I have over 6 years of experience in the tech industry. I specialize in the following technologies: Artificial Neural Network, Deep Neural Network, PyTorch, Computer Vision, Deep Learning, etc.. I hold a degree in Bachelor of Engineering (BEng), . Some of the notable projects I've worked on include: Object Detection Networks Paper Replication from Scratch using PyTorch, FPGA-Optimized NAS for Image Classification for Real-time Efficiency, Machine Learning Algorithm Implementations, Shakespeare: GPT from Scratch, LungVision: Identifying Pulmonary Disease through X-rays & DL, etc.. I am based in Kathmandu, Nepal. I've successfully completed 8 projects while developing at Softaims.

I am a business-driven professional; my technical decisions are consistently guided by the principle of maximizing business value and achieving measurable ROI for the client. I view technical expertise as a tool for creating competitive advantages and solving commercial problems, not just as a technical exercise.

I actively participate in defining key performance indicators (KPIs) and ensuring that the features I build directly contribute to improving those metrics. My commitment to Softaims is to deliver solutions that are not only technically excellent but also strategically impactful.

I maintain a strong focus on the end-goal: delivering a product that solves a genuine market need. I am committed to a development cycle that is fast, focused, and aligned with the ultimate success of the client's business.

Main technologies

  • AI, Machine Learning and Computer Vision Platforms

    6 years

  • Artificial Neural Network

    3 Years

  • Deep Neural Network

    2 Years

  • PyTorch

    3 Years

Additional skills

Direct hire

Potentially possible

Previous Company

LogicTronix

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Experience Highlights

Object Detection Networks Paper Replication from Scratch using PyTorch

I replicated the papers for YOLOv2, YOLOv4, YOLOv4-Tiny, and YOLOv6-Small, focusing on implementing their core architectural innovations, such as anchor boxes, multi-scale training, and hardware-frien

FPGA-Optimized NAS for Image Classification for Real-time Efficiency

We optimized CNNs for real-time efficiency on FPGAs, addressing the challenge of balancing computational performance with hardware constraints. We used an evolutionary algorithm to explore 300 millio

Machine Learning Algorithm Implementations

Implemented various machine learning algorithms across different datasets, reporting insights in an IEEE paper. Key projects included: • Decision Tree Classifier for counterfeit banknote detection.

Shakespeare: GPT from Scratch

BigramLanguageModel that spits texts like Shakespeare. Implemented Transformer architecture and GPT from scratch and trained it on Tiny Shakespeare

LungVision: Identifying Pulmonary Disease through X-rays & DL

The project aimed to develop an accurate system for detecting pulmonary diseases, specifically tuberculosis (TB) and pneumonia, using chest X-ray images. To achieve this we trained ResNet and Incept

Education

  • Insitute of Engineering, Tribhuvan University

    Bachelor of Engineering (BEng) in Computer science

    2019-01-01-2024-01-01

  • Fusemachine AI School

    in Artificial Intelligence

    2024-01-01-2024-01-01

Languages

  • English (Fluent)✓
  • Nepali (Native or Bilingual)