Portrait of Kashyap Sureshchandra Patel
M.Sc. Data Science · DAU (DA-IICT)

Kashyap
Sureshchandra Patel

Data Science student focused on LLMs, GNNs and QML.

M.Sc. in Data Science — DAU (DA-IICT)

Jul 2025 — Present
  • Current CGPA: 8.41 / 10

B.Tech in Computer Engineering — CHARUSAT

Jul 2020 — May 2024
  • Final CGPA: 8.42 / 10
  • Final Percentage: 82.36%
  • Class: First Class with Distinction

Higher Secondary (Class 12) — K. D. Ambani Reliance Foundation School

2019 — 2020
  • Board: CBSE
  • Stream: Science (PCM)
  • Percentage: 83.40%

Secondary (Class 10) — K. D. Ambani Reliance Foundation School

2017 — 2018
  • Board: CBSE
  • Subjects: English, Hindi, Social Science, Science, Mathematics
  • Percentage: 88.00%

Trainee Software Engineer — Surekha Technologies

Ahmedabad · Jan 2024 — Apr 2024 · 4 months · On-site
  • Developed proficiency in HTML, CSS, JavaScript, and jQuery.
  • Built responsive web interfaces and layouts.
  • Strengthened ReactJS skills for dynamic user interfaces and SPAs.
  • Received training in Liferay frontend development for customizable web portals.

Summer Research Intern — CHARUSAT

May 2023 — Jun 2023 · 2 months · Remote
  • Reviewed studies on deep learning for Parkinson’s disease prediction.
  • Processed raw datasets and converted DICOM images to JPEG.
  • Explored CNN-based approaches for medical image analysis.
  • View certificate

Web Development Intern — Motorola Solutions

May 2022 — Jul 2022 · 3 months · Remote
  • Studied MVC architecture and its relevance in production systems.
  • Gained practical exposure to full-stack web development.
  • Worked with MEAN and PEAN stacks for single-page applications.
  • View certificate

Fintech Essentials

GIFT IFI · Issued Jun 2026

Deep Learning

NPTEL · Issued May 2025

Introduction to Large Language Models (LLMs)

NPTEL · Issued May 2025

ReactJS

HCL GUVI · Issued Jun 2023

Motorola Certified Associate

Motorola Solutions · Issued Nov 2022

Bloch–Wasserstein Generative Adversarial Network for Quantum State Learning

IEEE International Conference on Quantum Computing and Engineering (Quantum Week 2026) - QML Track · Accepted
  • Authors: Bhavin Makwana, Kashyap Patel, Manjunath Joshi
  • Introduces a hybrid quantum–classical Wasserstein GAN for learning pure and mixed quantum states directly in generalized Bloch space.
  • Avoids computationally expensive semidefinite programming and matrix-exponential regularization used by earlier quantum Wasserstein GAN approaches.
  • View Code ↗
Quantum Machine Learning Quantum GAN Wasserstein GAN Quantum State Learning PyTorch

Custom Version Control System: JSON Snapshot vs. Git-Style Object Database

GitHub ↗
PythonData StructuresDAGOOP
  • Designed two custom version control systems inspired by Git internals.
  • Compared JSON snapshot storage with content-addressed blob/tree/commit objects.
  • Analyzed commit speed, checkout speed, space efficiency, and deduplication.

Relational Database Design for Research Collaboration Analysis (arXiv)

GitHub ↗
PostgreSQLSQLAlchemyPandas
  • Designed a normalized relational database for analyzing research collaboration.
  • Modeled authors, papers, categories, and versions.
  • Created analytical SQL queries and views for co-authorship and publication growth.

Flipkart Discount Rate Prediction

GitHub ↗
Machine LearningPandasScikit-LearnLightGBMXGBoost
  • Built an end-to-end ML pipeline using 300,000+ scraped e-commerce pages.
  • Performed category extraction, text normalization, feature engineering, and EDA.
  • Built preprocessing pipelines with scaling, target encoding, and TF-IDF.
  • Tuned Random Forest achieved RMSE 10.73 and R² = 0.69.

Generative Adversarial Network (GAN) From Scratch

GitHub ↗
Deep LearningPyTorchGAN
  • Implemented generator-discriminator adversarial training from scratch.
  • Designed fully connected networks for image synthesis.
  • Studied mode collapse, vanishing gradients, convergence behavior, and generated samples.