About me

Hi! I'm Pranay, Computer Science Engineering Student at Delhi Technological University. I build robust, scalable systems and architect Full-Stack Machine Learning applications. From High Performance Low-Level Systems to Distributed High-Level Design, my focus is on execution and efficiency.

An inherent characteristic of mine is a deep intolerance for stagnation. I actively seek out complex challenges to enhance my skills, drive innovation and push for continual progress in everything I do.

Current Engineering Focus:
Agentic Architecture, Distributed Design, Core Systems & HPC(C++/Rust)

Technical Proficiencies:
- Programming Languages: Python, C/C++, Rust, Java
- Machine Learning: Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow (Keras), OpenCV, Ultralytics YOLOv8, Transformers, Hugging Face, LlamaIndex, NLTK, NetworkX, PyTesseract
- Systems & Tools: Git, AWS, Docker, Google OAuth2, NextJS, Vercel, Bash Shell Scripts, Linux - Database Technologies: MongoDB, MySQL, AWS S3, Redis, Neo4j
- Web Development: JavaScript, React, Express, Node.js, FastAPI, RESTful APIs, GraphQL

Computer Science Fundamentals:
System Design (HLD, LLD), Operating Systems, Computer Architecture & Organization, Compiler Design, Distributed Systems, Parallel Computing, Computer Networks, Database Management, Object-Oriented Programming

Beyond the Terminal, you’ll find me immersed in literature, music, or playing classics on the piano.

Download Resume

Engineering Competencies

  • design icon

    Machine Learning Architecture

    Implementing end-to-end ML pipelines, from RAG-driven semantic search to real-time computer vision. Optimizing for heavy inference speed and high concurrency using PyTorch and YOLO architectures.

  • Web development icon

    High-Performance Execution

    Designing bare-metal optimized algorithms and memory-safe data structures in C/C++ and Rust to achieve deterministic execution, minimize computational overhead, and ensure microsecond latency.

  • database icon

    Distributed Systems Design

    Engineering decoupled, fault-tolerant enterprise systems utilizing Domain-Driven Design (DDD) to sustain high-throughput environments and strict network reliability constraints.

  • Machine Learning & AI

    Backend Microservices

    Building robust, scalable API architectures using FastAPI, Node.js, and Java, supported by optimized relational and NoSQL database integrations for seamless data transactions.

Testimonials

  • Daniel lewis

    John Doe

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    Jessica miller

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    Emily evans

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    Henry william

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  • Daniel lewis

    John Doe

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  • Jessica miller

    Jessica miller

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  • Emily evans

    Emily evans

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  • Henry william

    Henry william

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Daniel lewis
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John Doe

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Resume

Education

  1. Delhi Technological University (Formerly DCE)

    2023 — 2027 (Ongoing)

    B.Tech in Computer Science Engineering

  2. Narayana Academy & Sant Gyaneshwar Model School - Delhi

    2021 — 2023

    XII Grade - CBSE : Science Stream with Mathematics, Physics, and Chemistry.

  3. Hans Raj Model School - Punjabi Bagh, Delhi

    2009 — 2021

    X Grade - CBSE

Experience

  1. Machine Learning Intern @ Defence Research and Development Organisation (DRDO)

    Jun 2025 — Jul 2025

    Technologies: Python, Pandas, NumPy, NLTK, Scikit-learn, Node2Vec, K-Means, Fuzzy C-Means, FuzzyWuzzy, FastAPI, SQLite, Tortoise ORM
    - Led 3+ Agile sprints for end-to-end design and development of the Python Microservice for entity recommendation, adapting to feedback and evolving scopes, ensuring seamless integration with FastAPI, SQLite, and Tortoise ORM to support high-concurrency data transactions.
    - Engineered a hybrid engine with K-Means, Fuzzy C-Means, Node2Vec graph embeddings, and TF-IDF-enhanced fuzzy sets, applying robust NLP to achieve high system accuracy and 530ms average inference latency in a high-volume request environment.
    - Produced comprehensive documentation and standards-driven RESTful APIs, facilitating reliable and seamless integration across a microservice architecture. Maintained 100% deployment success and zero rollbacks throughout the development cycle.

  2. Cybersecurity Awareness Lead Volunteer - Extension Outreach DTU

    Aug 2023 — Dec 2023

    - Organized and conducted a cybersecurity awareness seminar within the college campus. Led live demonstrations of real-world cyber threats, phishing tactics, and data theft techniques to promote broader awareness.
    - Collaborated with a team to design and deliver interactive sessions across hostels, classrooms, and common areas. Engaged students and staff using practical examples and simulations to emphasize safe digital practices.

Achievements & Certifications

  1. Generative Adversarial Networks (GANs) Specialization by DeepLearning.AI

    2025 — 2026

    Engineered PyTorch-based GAN architectures (StyleGAN, CycleGAN, Pix2Pix) for high-fidelity image synthesis and style transfer. Applied architectural regularization techniques to stabilize discriminator training and mitigate mode collapse.

  2. Competitive Programming and DSA : LeetCode & CodeForces

    2024 — 2026

    Executed algorithmic problem-solving across 250+ competitive programming challenges in Python and Java. Optimized data structure selection to enforce strict time-space complexity bounds and ensure deterministic execution.

  3. Deep Learning Specialization by DeepLearning.AI

    2024 — 2025

    Architected and trained deep neural networks—spanning CNNs, RNNs, and LSTMs—focusing on gradient descent optimization, hyperparameter tuning, and efficient forward-pass inference for complex data modeling.

  4. 2nd Place, Adobe DevCraft Hackathon (InvictusDTU)

    2023 — 2024

    Engineered a high-precision Naive Bayes document classification model achieving 95%+ accuracy. Optimized the algorithmic architecture to minimize misclassification and drastically reduce latency in automated document processing pipelines.

  5. Machine Learning Specialization by DeepLearning.AI & Stanford

    2023 — 2024

    Implemented foundational supervised and unsupervised learning algorithms (Regression, Clustering, Ensembles). Executed rigorous model evaluation and validation protocols to ensure predictive accuracy and deployment readiness.

Skills

  • Core Computer Science Fundamentals - OOPS, CN, OS, CSAO, etc
  • Languages : Java, Python, C/C++, Rust
  • Machine Learning : CV, NLP, LLMs, RAG, GANs, RL
  • MERN Full-Stack Web Development
  • Database Management System Technologies
  • System Design - HLD, LLD

Projects

Contact

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