Hello!

I'm Raafi



MSc AI Graduate

With more than a year of experience

LinkedIn Github

Name: Rafi Ahmed

Job Role: AI/ML Engineer

Experience: 1 Year 5 Months

Address: London, United Kingdom

Skills

Python 95%
Machine Learning 75%
Computer Vision 80%
Natural Language Processing 90%
Reinforcement Learning 50%
Amazon Web Services 70%

About

About Me

A MSc Artificial Intelligence graduate from City, University of London, selected for a prestigious Machine Learning in Lung Cancer Research Internship at University related to UK Cancer Research, TracerX. With more than a year of experience in AI and machine learning, I've worked on diverse projects from computer vision to NLP. My journey includes roles at Webomates and ResoluteAI, where I developed and deployed ML models for real-world applications. Proficient in Python, PyTorch, and TensorFlow, I specialize in several AWS cloud services, deep learning, computer vision, and data science. I'm passionate about leveraging AI to solve complex problems and drive innovation in technology. Although, I like working in AI in general, I am primarily inclined towards Research AI ,& Medical AI are my primary Interest.

  • Profile: Data Science, Machine Learning & Artificial Intelligence
  • Domain: Medical, Ecommerce, Research & Customer Services
  • Education: Masters of Science in Artificial Intelligence
  • Frameworks: Pytorch, TensorFlow, Flask
  • Other Skills: AWS, MongoDB, Excel, Git, SQL,Kibana
  • Interest: Sports, Fitness, Reading
  • Language: English, Urdu, Hindi, Marathi

0 +   Projects completed

Github

Resume

Resume

With more than a year of experience in developing and deploying AI solutions. Specializing in machine learning, computer vision, and NLP, I've worked on diverse projects at companies like Webomates and ResoluteAI, honing my skills in Python, PyTorch, and cloud-based AI applications.

Experience


July-Oct 2024

Research Intern (AI / ML)

City, University of London

City, University of London is at the forefront of artificial intelligence research through its CitAI (City St George’s, University of London Artificial Intelligence Research Centre), which serves as the university’s AI Hub for interdisciplinary studies. Additionally, the university boasts the Robin Milner Lab, named after the AI pioneer and Turing Award winner, which facilitates high-performance research in AI.

  • Integrated clinical and phylogenetic data to enhance machine learning models for predicting survival in lung cancer patients.
  • Applied 5 different AI/ML model techniques to improve patient’s survival.
  • Collaborated with a multidisciplinary team including Dr. Robert Noble (Oxford University), Dr. Tillman Weyde (City, University of London),combining expertise in Mathematics and Computer Science to interpret results and refine models based on domain knowledge.
  • Presented findings at weekly research meetings and subsequently submitted results.

Jan-Sept 2023

Artificial Intelligence Trainee

Webomates

Webomates, headquartered in Stamford,US, is a leader in AI-driven software regression testing. Their patented platform leverages AI for test case generation, execution, and maintenance, providing quality assurance and efficiency in software testing.

  • Worked on AI Defect Predictor tool, which has led to an 11x increase in release speed, a 73% reduction in production defects, and a 50% reduction in costs
  • Extensively deployed and monitored Machine Learning models on AWS Elastic Compute Cloud service (EC2)
  • Researched and implemented AWS SQS queues for all API applications, replacing Flask requests, and successfully redeployed all services in production, thereby convincing the team on benefits.
  • Developed a model to detect feature changes in web pages using HTML, logs, and images.
  • Implemented XGBoost for HTML data, CNN for image data, and combined these outputs with a Random Forest model for feature detection.
  • Created a Flask application from scratch that generates and improves test cases for TestOps using the GPT-4
  • Deployed multiple NLP and computer vision models, which are currently operational in production.
  • Authored and published blogs on Artificial Intelligence for the company's official website.
  • Primarily worked with Python, OpenAI API, Flask, AWS, SQL, Jenkins, Kibana and Bitbucket
  • Regularly researched and implemented new techniques for ongoing improvement.

Sep-Dec 2022

Artificial Intelligence Intern

Webomates

Webomates, a global SaaS provider specialising in AI-driven software regression testing, has made significant strides in the industry with their patented technology.

  • Focused on automating manual software testing tasks using AI.
  • Primarily engaged in building APIs, data collection, and exploratory data analysis (EDA).
  • Gained experience with Amazon Web Services (AWS), including AWS Lambda, ECS, and CloudWatch.
  • Developed multiple Python scripts to automatically generate Excel reports utilising AWS Lambda.
Oct 2021-Jan 2022

Machine Learning Engineer Intern

ResoluteAI Software

ResoluteAI is a distinguished AI talent academy that collaborates with enterprises to develop and implement AI capabilities, platforms, and solutions. Their mission is to enhance productivity and profitability through the application of machine vision, data analytics, Natural Language Processing (NLP), and Internet of Things (IoT) technologies.

  • Developed a U-NET Neural Network architecture to detect defects in fabric videos.
  • Responsibilities included converting videos to frames, augmenting, annotating, masking images, and training and testing the model with visualisations.
  • Organised a webinar, instructed, and led a team of interns in image annotation tasks.
  • Focused on extracting regions of interest (ROI), drawing contours around objects in images, and labelling them, utilising Canny algorithm for edge detection.


Education


2023-2024

Master of Science in Artificial Intelligence (MSc AI)

City, University of London

Grade: Merit (68.5)

2019-2021

Bachelor of Science in Information Technology (BSc IT)

University of Mumbai

Grade: 8.5 CGPA

2016-2019

Diploma in Mechanical Engineering

Maharashtra State Board

Grade: Distinction

Download CV

Projects

Projects

Below are my projects related to Artificial Intelligence, Machine Learning, Data Science, and Deep Reinforcement Learning.

New Applications of Machine Learning In Lung Cancer Research

As an internship project in relation to UK Cancer Research and Tracerx , this project employs evolutionary cancer trees, constructed from multi-regional sequencing data, to model the evolutionary relationships among cancer clones. By integrating these trees with machine learning algorithms like linear regression, random forests, support vector machines, and genetic algorithms, this research aims to enhance the prediction of survival rates among cancer patients. The innovative approach not only leverages cutting-edge machine learning techniques but also incorporates robust evolutionary models, offering a comprehensive method to understand and predict cancer progression. This study is grounded in the TRACERx lung cancer data set, ensuring a rich and clinically relevant foundation for predictive analysis.

Image Super Resolution using GANs

The project implements two advanced deep learning models for low resolution to high resolution image - the Super Resolution Residual Network (SRResNet) and the Super-Resolution Generative Adversarial Network (SRGAN). The SRResNet utilizes a deep residual architecture to capture fine details, while the SRGAN takes this further by incorporating adversarial training for even more realistic results. This comprehensive implementation includes scripts for training and evaluation, along with robust utilities for data handling and model management, providing a complete solution for super-resolution tasks.

Chatbot using Seq2Seq & Transformer architecture (Pytorch)

The project employs Seq2Seq and Transformer architectures, enhanced with attention mechanisms to enable the chatbot to conduct coherent and contextually relevant conversations. Applications of this chatbot span various sectors, including customer service, healthcare, and education.


Feed Forward Neural Network and Recurrent Neural Network from scratch

This project implements a feed forward neural network from scratch using NumPy, exploring various architectures, regularization techniques, and optimizers to understand their impact on model performance. Additionally, it also implements a recurrent neural network LSTM using PyTorch for temperature forecasting, experimenting with different LSTM configurations and optimization strategies. This project helped in deeper intuition and understanding of neural networks behavior and optimization techniques across different implementations.

Roomba and Breakout Game (Deep Reinforcement Learning)

This Project showcases the implementation and analysis of various reinforcement learning (RL) algorithms, from basic Q-learning to advanced Deep Q-Networks (DQN). The project applies Q-learning to a simplified house cleaning scenario, demonstrating parameter sensitivity and convergence behaviors in a basic task. For more complex environments, it implements DQN and Double DQN with prioritized experience replay, aiming to maximize rewards. Through these implementations, the project explores the progression from tabular methods to deep learning-based approaches in RL. This work highlights the versatility and effectiveness of RL algorithms in solving diverse problems, showcasing their potential for both practical applications and gaming environments.

Achievements

Achievements

🏅

NLP Challenge Winner
(Jan 2025)

Won Harmony NLP Challenge by improving the algorithm for psychology survey question similarity ratings, reducing MAE from 24 to 20.544, organised by researchers from University College London (UCL), Ulster University, Universidade Federal de Santa Maria, and Fast Data Science.
🏆

Research Internship
(July 2024)

Selected for AI/ML Research Internship at City, University of London utilising UK Cancer Research, and TracerX datasets (publication in progress)

💼

Early Career Offer
(Jan 2023)

Offered a full-time role in the 3rd month of a 6-month internship based on exceptional performance and contributions at Webomates, Stamford, USA (remote).

More projects on Github and Hugging Face

I love harnessing AI to drive impactful results and solve business problems.


GitHub Hugging Face

Contact

Contact Me

Below are the details to reach out to me!

Address

London, United Kingdom

Contact Number

+44 777 487 4773

Email Address

rafa.works313@gmail.com

Download Resume

Download Resume



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