Yashswi Shukla

FINAL-YEAR COMPUTER SCIENCE UNDERGRADUATE AT BENNETT UNIVERSITY

I'm an AI engineer who builds from the ground up data pipelines, realtime systems, deployed products. With a foundation in Computer Vision and NLP, a published IEEE research paper, and hands on experience in a Founder's Office, I don't just train models
— I ship systems that work in the real world.

About and Engineering Philosophy

I Build AI Systems That Can Be Used, Not Just Presented

I am most energized by applied AI problems where model quality, latency, and usability all matter at the same time. My approach is to break a problem into system components: data handling, model choice, evaluation, deployment constraints, and product integration.

I care about engineering tradeoffs. Instead of optimizing only for model novelty, I focus on whether a system is reliable in real scenarios and whether it creates measurable value for users.

Problem First

Start from a concrete user pain point and define success criteria before model selection.

Metrics Driven

Track system behavior with clear evaluation metrics and iterate based on data, not assumptions.

Build End to End

From prototype to deployable app, I work across modeling, backend logic, and product execution.

Technical Stack

Tools I Use to Build and Ship AI Products

Core AI and ML

PyTorch TensorFlow Keras Scikit-learn NumPy Pandas

Computer Vision

OpenCV MediaPipe Image Enhancement Face Detection Noise Reduction

NLP

Transformers BART spaCy Text Summarization Prompt Engineering

Backend and App Development

Python Streamlit Node.js Express.js JavaScript REST API Integration

Tools

Git GitHub Jupyter VS Code Postman EmailJS

Languages

Python Java C C++

Experience

Skillcase | Founder's Office Internship

Startup execution across product ownership, system building, and day-to-day cross-functional delivery.

Product and Operations Intern

July 2025 - Feb 2026

Product Ownership

  • Owned requirement translation for mobile app and web platform versions.
  • Prioritized feature rollout across V1 to V3 with founder and developer alignment.
  • Validated deliverables through structured UAT and release readiness checks.

System Building

  • Supported end-to-end launch of a learning app used by active students and teachers.
  • Drove regression testing, bug reporting, and post-release issue tracking loops.
  • Helped shape mobile-first web updates for usability and reliability improvements.

Cross-Functional Execution

  • Acted as communication bridge between founders, developers, and operations teams.
  • Managed scheduling and student workflows for live class operations.
  • Created educational social content to support growth and brand engagement.

Research

Enhancing Face Detection in Low-Light Conditions

Published work focused on denoising strategies for robust face detection in low-illumination scene at ICCSAI-2025 Conference.

Research Question

How do different denoising techniques affect face detection quality when images are degraded by low-light noise?

Method

Benchmarked Median, Non-Local Means, Wavelet, and DnCNN methods using PSNR, SSIM, and MSE on low-light datasets.

Key Finding

DnCNN delivered best restoration quality with PSNR up to 32.45, improving downstream face detection robustness.

Projects

Additional Systems and Prototypes

KholiPoll

Campus communication platform prototype with event feeds, feedback loops, and role-aware access.

Stack: Python, Streamlit, Data Processing

Story Visualizer

AI-assisted storytelling interface that combines narrative flow and visual presentation in an interactive app.

Stack: Python, Streamlit, PIL

Currently Building

Active AI Engineering Work

In Progress

Low-Light Vision Evaluation Harness

Expanding robustness benchmarks with repeatable experiments across noise profiles and denoising configurations.

In Progress

NLP Summarization API Version

Converting the Narrative pipeline into an API-first service with cleaner modular interfaces and test coverage.

Exploring

AI Product Telemetry

Designing lightweight monitoring for prompt quality, user flow drop-off, and inference latency in AI apps.

Contact

Hiring for AI or ML Roles?

I am looking for full-time AI Engineer and Machine Learning Engineer opportunities where I can contribute across model development and system implementation.

  • yashswishukla@gmail.com
  • +91 8368528828
  • Gautam Buddha Nagar, Uttar Pradesh