M..

M. Tayyab Haider

CS at LUMS | AI Researcher & Full-Stack Builder | Vocal Performer

Overview

Computer Science student at LUMS and 100% Merit Scholar with a deep focus on Computer Vision and AI-driven applications. I've built everything from wildlife detection pipelines with 98% accuracy to full-stack AI note-taking tools. Beyond the technical, I'm a seasoned vocal performer and leadership figure in the LUMS Music Society, bringing a unique blend of creative energy and engineering precision to every project.

Lahore, Pakistan

Media Showcase

M. Tayyab Haider - Updated Resume (June 2026)

Latest resume featuring RAG and LlamaIndex projects.

Experience

Oct 2025 – Present

FREELANCE

Vocal Performer

Independent

Performed at paid live events and private functions, managing client communication, scheduling, and on-site coordination.

•Performed at paid live events and private functions, managing client communication, scheduling, and on-site coordination.

•Built a personal performance portfolio through consistent audience engagement and referrals.

Jun 2025 – Present

INTERNSHIP

Research Intern

LUMS Computer Vision & Graphics Lab

Animal Detection in Camera trap Images & Image Deraining

•Developed a deep learning pipeline for wildlife detection in camera trap images using YOLO and U-Net, reducing false positives caused by rain artifacts.

•Built and trained a U-Net model for rain detection and integrated it with a YOLO-based object detection pipeline, achieving 98% rain vs animal classification accuracy.

•Designed a synthetic dataset of 10,000+ rain-degraded images and implemented a CNN-based kernel estimator to improve image recovery from rain deterioration.

Key Achievements

→Achieved 98% rain vs animal classification accuracy.

YOLOU-NetCNNDeep LearningComputer Vision

Project Portfolio

PERSONAL

Present

RAG Wikipedia Chatbot

Built a retrieval-augmented generation chatbot that dynamically fetches and indexes Wikipedia articles using a ReAct agent, grounding every answer in retrieved facts. Implemented the full RAG pipeline: Wikipedia ingestion, document chunking, local HuggingFace embeddings (BAAI/bge-small-en-v1.5), vector indexing, and semantic similarity retrieval. Deployed session-isolated multi-user chat interface with model switching (LLaMA 3 / DeepSeek) via async Python and Chainlit's per-user session management.

PythonRAGLlamaIndexLangchainLLaMA 3DeepSeekChainlitHuggingFace

ACADEMIC

Present

Camouflaged Object Detection (Wildlife Monitoring)

Deep Learning Student

Fine-tuned MegaDetector (MDv6) on COD10k dataset to improve detection on camouflaged wildlife. Evaluated model performance using Intersection over Union (IoU) and qualitative bounding-box visualizations to validate detection improvements.

Deep LearningMegaDetector (MDv6)COD10k dataset

ACADEMIC

Present

LUMS Markaz – Campus E-Commerce Platform

HCI Student

Designed a campus-wide mobile e-commerce platform, addressing unmet student demand for secure on-campus transactions. Validated product decisions through cross-school user research, conducting 100+ surveys and 50+ interviews and app usability tests to refine UX around trust, discoverability, and usability.

Human Computer InteractionUX DesignUser Research

ACADEMIC

Present

Urdu News Article Classification

Machine Learning Student

Scraped and curated 1,000+ Urdu news articles from Geo Urdu, Jang, and Express News across five categories: business, entertainment, sports, science-technology, and world. Cleaned, standardized, and vectorized the text data, then trained logistic regression, multinomial Naïve Bayes, and neural network models for multiclass classification. Achieved a peak test accuracy of 97.4% with the neural network; multinomial Naïve Bayes reached 96.4%, and logistic regression reached 95% test accuracy.

Machine LearningLogistic RegressionMultinomial Naïve BayesNeural NetworksWeb Scraping

PERSONAL

Present

AI Based Note Taking Web Application

Full-stack Developer & Product Visionary

Developed an all-in-one AI note-taking platform to solve the friction of switching between PDFs and external LLMs. Built a seamless workflow where users get real-time AI assistance—including text-to-speech, summarization, and automated quiz generation—directly within their note-taking environment.

ReactPythonMongoDBVercelAPI

Education

2022 – 2026

B.Sc. Computer Science

Lahore University of Management SciencesSpecialization in Computer Science

Relevant Coursework

Introduction to Artificial IntelligenceMachine LearningDeep LearningSoftware EngineeringHuman Computer InteractionDatabasesCoding for Careers

Impact & Recognition

Awards

The City School · 2020

Merit Scholarship (100%)

Awarded for A levels

Governance & Advisory

LUMS Music SocietySep 2023 – Jun 2025

Director & Event Head | Electronics Category

BOARD MEMBER

Led the Design Department for the LUMS Music Society, overseeing promotional strategy and content creation for major campus events.

Led a 14-member design team and handled electronics-category operations for a 3-day LUMS music festival, coordinating participants, judges, volunteers, and logistics.

Built a scalable design workflow and onboarding process that improved collaboration, enabled contributors of different skill levels to participate, and kept deliverables on schedule.

Key Impact

→

Updated leadership responsibilities and team size for LUMS Music Society

Vision & Goals

Core Drivers

What are my motivations

Delivering products to clients at speed

Building and iterating in fast-paced environments

Skills & Interests

Python

TECHNICAL

Leadership

TECHNICAL

Team Management

TECHNICAL

PyTorch

TECHNICAL

Jupyter Notebook

TOOL

React

TECHNICAL

C++

TECHNICAL

Figma

TOOL

Canva

TOOL

MongoDB

TECHNICAL

Microsoft Excel

TOOL

Vercel

TOOL

STATA

TOOL

LlamaIndex

TECHNICAL

Langchain

TECHNICAL

RAG

TECHNICAL

Areas of Expertise

Coordination and Logistics

Ownership

Communication

Time Management

Problem Solving

Let's Connect

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