MUADH ABDULLATEEF OLAMILEKAN

About

A dynamic and results-oriented Data Scientist and AI/ML Engineer with a profound passion for data and artificial intelligence, adept at solving complex real-world problems through innovative research and engineering. Leveraging a strong foundation in Computer Science and an ongoing Master's in Financial Engineering, I combine rigorous academic knowledge with hands-on project experience in Deep Learning, Computer Vision, NLP, and LLMs to drive high-impact solutions.

Education

World Quant University

Remote
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Masters Financial Engineering

KIIT University

Bhubaneswar, Odisha, India
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B.Tech. Computer Science and Communications Engineering Grade: 7.81/10 (First Class)

International Open University

Remote
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B.A. Arabic Language and Linguistics Grade: 3.11/4 (Second class upper)

Work

Insurtech

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Software Engineer

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Summary

Mainly focusing on backend systems.

Highlights

Implemented an automated airtime and data vending system (Autotopup) to streamline customer purchases, improving transaction speed and reliability.

Integrated payment and recharge automation, reducing manual intervention and enhancing customer satisfaction.

Increased efficiency and revenue by offering seamless top-up services at point of sale

Cognigent AI

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Machine Learning/AI Engineer

Lagos, Nigeria

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Summary

Developed automated workflows to ease business operations.

The Sparks Foundation

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Data Science Intern

Remote

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Summary

Engaged in data science research and development, focusing on practical applications of machine learning algorithms.

Highlights

Executed data analysis tasks and built machine learning prototypes, demonstrating proficiency in Python and relevant libraries.

Participated in research-oriented projects, contributing to the development of data-driven solutions and insights.

Collaborated with team members to refine methodologies and present findings, fostering a strong learning environment.

Oasis Infobyte

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Data Science Intern

Remote

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Summary

Contributed to data science projects, applying machine learning techniques to extract insights and build predictive models.

Highlights

Developed and implemented machine learning models for specific data analysis tasks, enhancing predictive capabilities.

Assisted in data cleaning, preprocessing, and visualization, ensuring data quality and interpretability for project stakeholders.

Gained practical experience in data science workflows, from problem definition to model deployment, under mentorship.

Upwork

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Freelance Digital Marketing Assistant

Remote

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Summary

Supported client digital marketing initiatives by leveraging analytical tools and platforms to enhance campaign performance and achieve business objectives.

Highlights

Managed diverse digital marketing campaigns, utilizing data-driven insights to optimize content and targeting strategies for various clients.

Implemented SEO best practices and content strategies, contributing to improved online visibility and organic traffic for client websites.

Collaborated with clients to understand marketing goals, translating requirements into actionable digital strategies and reporting on key performance indicators.

Interests

Data Science

Machine Learning

Deep Learning

Computer Vision

Large Language Models (LLMs)

Finance

Skills

Programming Languages

Python, C/C++.

Data Science Libraries & Frameworks

Pandas, NumPy, SciPy, TensorFlow, PyTorch, OpenCV, Seaborn, Matplotlib.

Machine Learning

Linear Regression, Logistic Regression, Decision Trees, Random Forests, XGBoost, SVM, K-Means, KNN, Deep Learning, Neural Networks.

Computer Vision

YOLO, Mask R-CNN, Haar Cascades, KCF, CSRT, Image Processing, Object Detection, Segmentation, Tracking.

Natural Language Processing (NLP) & LLMs

Langchain, Langgraph, SmolAgent, CrewAI, LlamaIndex, n8n, Large Language Models (LLMs), Recommender Systems, Fine-tuning (DistilBERT, T5, Longformer), Text Classification, Summarization, Translation.

Deployment

Flask, Django.

BI & Analytics

Power BI, Tableau.

Tools

Git, Selenium, BeautifulSoup, Scrapy.

Technical & Research Writing

Blogs, Reports, Documentation.

AI Agents & Automation

Building AI Agents, Automating Workflows.

Core Knowledge

Python, Django / FastAPI, AI/ML & LLMs, LangChain, APIs & databases.

Certificates

Applied AI Lab

WorldQuant University

Google Data Analytics

Coursera (Google)

Google UI/UX Design

Coursera (Google)

Google IT Support

Coursera (Google)

Data Science with Python

DataCamp

Applied Data Science Lab

WorldQuant University

Data Engineering

DataCamp

Computer Vision

Udemy

Machine Learning Track

DataCamp

TATA Virtual Internship Program

TATA

Publications

A CNN-BERT Multimodal Approach for Improving Web Service Classification

Developed and evaluated a CNN-BERT multimodal approach to significantly improve the accuracy and efficiency of web service classification.

A Comparative Study on Sentiment-Aware Multimodal Personalized Movie Recommender System

ICDAI-2024

Research exploring a novel sentiment-aware multimodal approach to enhance personalized movie recommendation systems, presented at ICDAI-2024.

Web Service Selection Using Hierarchical Graph Transformation

Explored hierarchical graph transformation techniques for optimizing web service selection processes.

Languages

English

Arabic

Projects

Real-time Face Detection System

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Summary

Developed a robust system for real-time face detection using advanced computer vision techniques.

CNN-based Face Recognition System

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Summary

Built a scalable CNN-based model for accurate real-time face identification from various media.

High-Precision Object Tracking System

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Summary

Implemented a system to track multiple objects with high precision in dynamic environments.

Real-Time Face Mask Detector

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Summary

Developed a real-time system for detecting face masks, showcasing expertise in computer vision and classification.

Social Distancing Monitoring Tool

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Summary

Designed a real-time monitoring tool for public health compliance using video streams.

YOLO-based Multi-Object Detection System

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Summary

Built a YOLO-based model for accurate multi-object detection in real-time scenarios.

Image Segmentation Pipeline with Mask R-CNN

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Summary

Created an image segmentation pipeline for both static and dynamic inputs using Mask R-CNN.

American Sign Language (ASL) Recognition Model

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Summary

Developed a deep learning model for recognizing American Sign Language gestures.

Predictive Model for Blood Donation Likelihood

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Summary

Built a binary classifier to predict the likelihood of future blood donations.

Agriculture Yield Prediction System

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Summary

Applied machine learning for optimizing crop yield and feature selection in smart farming.

Cosmetic Ingredient Similarity Analysis

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Summary

Utilized t-SNE and Bokeh to visualize the similarity between cosmetic products based on ingredients.

Context-Aware Book Recommender

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Summary

Developed a recommender system leveraging LLMs to provide context-aware book suggestions.

Customer Outreach Campaign Agent (CrewAI)

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Summary

Created an AI agent using CrewAI to automate and optimize customer outreach campaigns.

Email Sorting & Summarization Agents (LangGraph)

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Summary

Built AI agents with LangGraph for automated email sorting and summarization.

Vision Agent for Image Understanding

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Summary

Developed an AI agent capable of understanding and interpreting image content.

Agentic RAG for QA with LlamaIndex

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Summary

Implemented an agentic Retrieval-Augmented Generation (RAG) system for question-answering using LlamaIndex.

AI Blogging Assistant (CrewAI)

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Summary

Designed an AI assistant using CrewAI to generate blog content.

AI Email Agents (n8n)

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Summary

Built AI-powered email agents using n8n for automated email management.

Multi-Agent Frameworks (SmolAgent)

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Summary

Explored and implemented multi-agent frameworks, specifically SmolAgent, for complex task automation.

Large Language Model Fine-tuning

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Summary

Conducted fine-tuning on various Large Language Models (LLMs) such as DistilBERT, T5, and Longformer for specific applications.

LLM-based Text Processing Suite

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Summary

Developed applications leveraging LLMs for advanced text processing tasks including translation, summarization, and classification.