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paluuuk/README.md

Paluk Gupta

Software Engineer · AI Infrastructure & Platforms · Singapore

I build backend services, cloud-platform automation, data pipelines, and applied machine-learning systems. My work spans AI infrastructure at Dell Technologies, data engineering at EY Singapore, and computer-vision research with NTU / RRIS.

Selected engineering work

Project Technical focus What is public
Exoskeleton terrain perception Stereo depth, inpainting, point-cloud processing, seven-class CNN inference Research and camera-integration code
Beehive Flutter/Firebase mobile product for students and alumni across Singapore universities Product and engineering overview; production code private
Deal Preflight Acquisition due diligence, deterministic deal calculations, evidence tracking, versioned reports Product workflow and engineering overview; production code private
Aerial road segmentation PyTorch U-Net, EfficientNet encoder, Dice + BCE objective, validation checkpointing Guided notebook experiment and implementation notes
SenSync Flutter caregiver-support prototype and offline WESAD stress classification Mobile prototype and separate ML experiments
Satellite classification Four-band imagery, linear softmax baseline, Keras CNN Experimental notebook with documented data and evaluation scope

Tools I work with

  • Backend and platforms: Python, Go, REST APIs, microservices, Docker, Kubernetes, Azure.
  • AI and data: LLM-assisted workflows, computer vision, TensorFlow/Keras, PyTorch, scikit-learn, SQL, ETL/ELT.
  • Product engineering: Flutter, Dart, Firebase, mobile applications.

The project READMEs distinguish completed implementations, research experiments, and production products whose source remains private.

Background

B.Eng. Aerospace Engineering, Nanyang Technological University. Former President, SEDS Singapore.

LinkedIn

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  1. Vision-based-Terrain-Recognition-for-Lower-Limb-Exoskeletons Vision-based-Terrain-Recognition-for-Lower-Limb-Exoskeletons Public

    Research pipeline for exoskeleton terrain perception: stereo depth, inpainting, point-cloud normalization, and seven-class CNN inference.

    Python 1

  2. beehive beehive Public

    Flutter/Firebase mobile product for students and alumni across Singapore universities. Public engineering showcase; production source code is private.

  3. deal-preflight deal-preflight Public

    Buyer-side due diligence for online-business acquisitions: deterministic deal math, evidence tracking, and versioned reports. Public product showcase; source code is private.

  4. Aerial-Image-Segmentation Aerial-Image-Segmentation Public

    PyTorch U-Net road segmentation with an EfficientNet encoder, paired augmentations, Dice+BCE loss, validation checkpointing, and mask inference.

    Jupyter Notebook

  5. SenSync SenSync Public

    Forked from ISHITA006/SenSync

    Flutter caregiver-support prototype with Firebase, health/location features, and a separate WESAD Random Forest stress-classification experiment.

    Jupyter Notebook 1

  6. Satellite_Image_Classification Satellite_Image_Classification Public

    Four-band satellite land-cover classification: linear softmax baseline and Keras CNN, with explicit preprocessing and validation scope.

    Jupyter Notebook