Divya Shah

Divya Shah

Computer Science Engineer

Portfolio Overview

Divya Shah

Hi, I'm Divya Shah

A passionate Computer Science undergrad from Symbiosis Institute of Technology with a proven record of excellence in AI/ML research, Full-Stack development, and Cybersecurity.

From winning national hackathons and publishing in top journals to interning on Indo-Italy and Government of India-funded research, I thrive at the intersection of technology, innovation, and impact.

Whether it's decoding brain signals into images, building drone-based disaster response systems, or streamlining HR using AI-powered ATS engines, I bring ideas to life with code and curiosity.

A dedicated and innovative Computer Science Engineer with a passion for Artificial Intelligence, Machine Learning, and Full-Stack Development. Experienced in leading research projects, developing robust applications, and contributing to open-source communities. Proven ability to tackle complex challenges and deliver high-impact solutions in collaborative, fast-paced environments. Currently seeking to leverage my skills in a challenging role within the tech industry.

3+

Hackathon Wins & Finalist Positions

2

Research Papers Published

2

Patents Granted

5+

Internships & Research Roles

Work Experience

Product Manager Intern — Tracelink, Pune Jun 2025 – Present

  • Translating business needs into user stories and functional specs.
  • Collaborating with engineering, UX, and QA on Opus supply chain platform.
  • Conducting UX reviews and competitive analysis to support critical decisions.
  • Assisting in sprint planning, bug triaging, and release coordination.

Research Intern — Symbiosis Centre for Applied AI, Pune Jan 2025 – Present

  • Performing exploratory data analysis on primary healthcare datasets.

Junior Research Fellow — SIT, Pune Jun 2024 – Nov 2024

Project: Detection & Mass Screening of Obstructive Sleep Apnea (OSA)

  • Designed a sensor-based sleep mask with real-time monitoring capabilities.
  • Built a full-stack system for real-time data acquisition.
  • Developed AI/ML models to detect abnormal breathing patterns with high accuracy.

Research Intern — Symbiosis Centre for Applied AI, Pune Nov 2023 – Present

Project: Multimodal Uncertainty-aware Paradigm for Object Detection using XAI

  • Worked with University di Milano on ensemble techniques for multi-scale object detection.
  • Modified YOLOv8 for IR and RGB image fusion and open-source contributions.
  • Implemented explainability via Layer-wise Relevance Propagation (LRP).

Research Intern — Symbiosis Centre for Applied AI, Pune Nov 2023 – Jun 2024

Project: Explainable Computer Vision Framework for Drone Imagery

  • Generated synthetic datasets (1600+ images) for scene understanding tasks.
  • Developed and compared 10+ object detection models (YOLOv8-11, RT-DETR).
  • Analyzed datasets using SSIM, PSNR, Entropy & Perceptual Loss metrics.

Business Challenge Analyst Intern — University of Auckland, NZ Jun 2023 – Aug 2023

  • Led strategic analysis to solve operational problems for NZ-based firms.
  • Collaborated across multicultural teams from India, Korea, and Japan.
  • Delivered data-backed solutions with practical business impact.

Full Stack Development Intern — IEEE Bombay Section YP, Pune Dec 2022 – Mar 2023

  • Built web apps using Svelte and Vite focused on speed and scalability.
  • Handled backend integration and system architecture design.
  • Created user-centric UI/UX using Figma to aid design efficiency.

AI & ML Intern — IBM & AICTE NEAT Dec 2022 – Mar 2023

  • Developed an AI-powered mental fitness tracker with research-based insights.
  • Completed specialized IBM courses:
    • Artificial Intelligence Fundamentals
    • Essentials of AI and Cloud
    • Artificial Intelligence in Practice

Education

Symbiosis Institute of Technology, Pune

Nov 2021 – Jun 2025 (Expected)

Bachelor of Technology in Computer Science and Engineering

GPA: 7.1 / 10


Capital College & Research Centre (NEB - Grade 12)

Nov 2019 – Feb 2021

Science Stream

Marks: 84.7%


Radiant Readers’ Academy (NEB - Grade 10)

Aug 2017 – Jul 2018

Marks: 88.7%

Technical Skills

Programming & Development

  • Languages: Python, C, C++, JavaScript, SQL, Java, Dart, R
  • Libraries & Frameworks: TensorFlow, PyTorch, Keras, YOLO, NumPy, Pandas, Matplotlib, Scikit-learn, React.js
  • Full-Stack Development: Web & App Development using React.js, Dart, JavaScript

Tools & Platforms

  • Development Environments: Jupyter Notebooks, Google Colab, VS Code, MATLAB, Hugging Face
  • Version Control: Git
  • Operating Systems: Windows, Linux

Cloud & DevOps

  • Cloud Platforms: Google Cloud Platform (GCP), Microsoft Azure, Amazon Web Services (AWS)
  • CI/CD & Containerization: Jenkins, Docker, Kubernetes, Docker Hub

Language Proficiency

  • Fluent: English, Nepali, , Maithili, Hindi
  • Basic: French, German

Specialized Domains

  • Neural Networks & Deep Learning
  • Computer Vision & Generative AI
  • Full-Stack Development (App & Web)

Academic Projects

B.Tech Project: Image Reconstruction by Decoding EEG Data Jan 2024 – Ongoing

PI: Dr. Rahee Walambe | Team Size: 2

Objective: To reconstruct visual stimuli seen by a subject using only EEG data, leveraging Conditional GANs for image generation and Auto-Encoders for feature extraction on primary EEG data collected from real subjects.

  • Built theoretical frameworks and AI models to analyze EEG signals, improving predictive capabilities.
  • Designed Flask-based backend infrastructure for real-time communication and functionality.
  • Achieved a 28% reduction in MSE, 122% increase in SSIM, and 54% improvement in PSNR through GAN integration.

DevOps Full-Stack Project: Automated Deployment & Monitoring Oct 2024

Team Size: 2

Objective: To design a full-stack Flask-based web application with MongoDB and DevOps features like CI/CD using Jenkins, Docker, Terraform, and ELK stack for deployment and monitoring.

  • Co-led CI/CD pipeline design with rapid, automated deployments via Jenkins & Docker.
  • Developed shopping-cart web app with user auth, product display, and real-time monitoring.
  • Optimized deployment uptime to nearly 100% through strategic infrastructure planning.

Multimodal Uncertainty-Aware Object Detection using XAI Nov 2023 – Present

Team Size: 4

Objective: To improve object detection across modalities (RGB & IR) using explainable AI methods. Integrated DevOps best practices with automated deployment, performance monitoring, and uncertainty modeling.

  • Equally contributed to infrastructure automation, model integration, and deployment strategies.
  • Maintained high system uptime through CI/CD and real-time performance metrics using ELK.

Explainable Computer Vision for Drone Imagery Nov 2023 – Jun 2024

Team Size: 5

Objective: To generate synthetic datasets for disaster scenes using generative models (1600+ images), improving object detection models in data-scarce environments. Benchmarked models with real-world datasets using SSIM, PSNR, Entropy, and Perceptual Loss.

  • Created synthetic datasets to address real-world data limitations in critical scenarios.
  • Developed and evaluated 10+ object detection models (YOLOv8–YOLO11, RT-DETR).
  • Performed deep comparative analysis between real and synthetic data using diverse metrics.

Achievements & Publications

Publications

  • Research Paper: "Urban Small-Scale Hydroponics: A Compact, Smart Home-Based Hydroponics System"
    MethodsX (Vol. 13) • Published: Oct 2024

  • Patent: "AI-Based Antenatal Risk Assessment & Clinical Decision Support System"
    Patent No: 202421067110 • Filed: Sep 2024

  • Patent: "IoT-Based Smart Bag System for Remote Monitoring and Tracking of Delivered Items"
    Patent No: 202421077664 A • Filed: Nov 2024

  • Journal Article: "Next-Gen Midwifery Support: AI-Enhanced App for Pregnancy Risk Assessment"
    Birth Journal (Wiley) • Published: Jul 2024

Submitted

  • Dataset Paper: "SURGE: Synthetic Dataset for Disaster Surveillance and Rescue"
    Submitted to Journal of Big Data • Jan 2025

  • Neuro-AI Research: "From Neural Signals to Images: Generative Reconstruction from EEG"
    Preprint on SSRN (PsychRN Track) • Jan 2025

  • Journal Article: "Temporal Energy Consumption Forecasting and Analysis"
    MethodsX • Submitted: Nov 2024

Achievements

  • 1st PlacePRIMATHON Hackathon 2023
    Led a team of 3 to build an AI/ML-powered Company Properties Allotment Tracker.
    Award: INR 1,00,000 (~$1200)

  • 3rd PlaceIC Hack 2.0 (Healthcare Track), IEEE India Council
    Built "Med-Sync" — unified IoT-AI platform with visual analytics for healthcare.
    Prize: INR 5,000 (~$60) • Nov 2023

  • Grand FinalistPRIMATHON 2.0 Hackathon 2024
    Selected for finals with AI-powered ATS Smart Matching Engine project.
    Hackathon Ongoing • Dec 2024

Certifications & Workshops

Certification Courses

  • Cybersecurity Essentials – Cisco Networking Academy, May 2023
  • Introduction to Cybersecurity – Cisco Networking Academy, May 2023
  • Networking Essentials – Cisco Networking Academy, May 2023
  • Agile Fundamentals (Scrum & Kanban) – Udemy, October 2022
  • Intro to Operating Systems 2: Memory Management – Codio via Coursera, April 2023
  • Distributed Systems – Mind Luster, April 2024
  • Google Agile Project Management – Coursera, October 2022
  • Linux and Data Analytics – VOIS, September 2022
  • Artificial Intelligence & Machine Learning – Advanced – VOIS, September 2022
  • Cloud Computing – Advanced – VOIS, September 2022
  • Cyber Security – Advanced – VOIS, September 2022

Workshops & Participations

  • AI & ML Hands-on Workshop – Successfully completed with qualifying marks at Symbiosis Institute of Technology, Pune (14–16 Sept 2022)
  • Project Exhibition Participant – Organized by CSE Department & CodeX SIT, Symbiosis Institute of Technology, Pune, 21 April 2023