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Hi, I'm Abhirup Paul, a Computing MSc student at Dublin City University with a strong interest in AI, ML, and data analytics. I earned a B.Tech in Computer Science Engineering from Amrita University, and I enjoy turning complex data into practical, impact-driven solutions. I have hands-on experience building computer vision pipelines, video analysis models, and full-stack web applications using Python, TensorFlow, OpenCV, and cloud technologies. I'm motivated by problem solving and collaboration; I like learning new tools and sharing insights with teammates and stakeholders. I'm excited to contribute to innovative projects that bridge AI research and real-world applications, from preprocessing to deployment and monitoring on cloud and MLOps pipelines.…Hi, I'm Abhirup Paul, a Computing MSc student at Dublin City University with a strong interest in AI, ML, and data analytics. I earned a B.Tech in Computer Science Engineering from Amrita University, and I enjoy turning complex data into practical, impact-driven solutions. I have hands-on experience building computer vision pipelines, video analysis models, and full-stack web applications using Python, TensorFlow, OpenCV, and cloud technologies. I'm motivated by problem solving and collaboration; I like learning new tools and sharing insights with teammates and stakeholders. I'm excited to contribute to innovative projects that bridge AI research and real-world applications, from preprocessing to deployment and monitoring on cloud and MLOps pipelines.

Abhirup Paul

AI Engineer, Data Scientist, Programmer, +2

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Hi, I'm Abhirup Paul, a Computing MSc student at Dublin City University with a strong interest in AI, ML, and data analytics. I earned a B.Tech in Computer Science Engineering from Amrita University, and I enjoy turning complex data into practical, impact-driven solutions. I have hands-on experience building computer vision pipelines, video analysis models, and full-stack web applications using Python, TensorFlow, OpenCV, and cloud technologies. I'm motivated by problem solving and collaboration; I like learning new tools and sharing insights with teammates and stakeholders. I'm excited to contribute to innovative projects that bridge AI research and real-world applications, from preprocessing to deployment and monitoring on cloud and MLOps pipelines.…Hi, I'm Abhirup Paul, a Computing MSc student at Dublin City University with a strong interest in AI, ML, and data analytics. I earned a B.Tech in Computer Science Engineering from Amrita University, and I enjoy turning complex data into practical, impact-driven solutions. I have hands-on experience building computer vision pipelines, video analysis models, and full-stack web applications using Python, TensorFlow, OpenCV, and cloud technologies. I'm motivated by problem solving and collaboration; I like learning new tools and sharing insights with teammates and stakeholders. I'm excited to contribute to innovative projects that bridge AI research and real-world applications, from preprocessing to deployment and monitoring on cloud and MLOps pipelines.

Available to hire

Hi, I’m Abhirup Paul, a Computing MSc student at Dublin City University with a strong interest in AI, ML, and data analytics. I earned a B.Tech in Computer Science Engineering from Amrita University, and I enjoy turning complex data into practical, impact-driven solutions. I have hands-on experience building computer vision pipelines, video analysis models, and full-stack web applications using Python, TensorFlow, OpenCV, and cloud technologies.

I’m motivated by problem solving and collaboration; I like learning new tools and sharing insights with teammates and stakeholders. I’m excited to contribute to innovative projects that bridge AI research and real-world applications, from preprocessing to deployment and monitoring on cloud and MLOps pipelines.

Skills

Experience Level

Expert

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Intermediate

Language

English

Fluent

Hindi

Fluent

Bengali

Fluent

Work Experience

Deep Learning Engineer (Project-based) at Self-initiated Projects

April 1, 2023 - Present

Developed multiple AI projects including a diabetic retinopathy classification system using cascaded ensemble models to enhance minority class predictions; a violence detection system in surveillance videos improving accuracy with attention mechanisms and transfer learning; a scalable college management web application integrating Firebase and MongoDB with role-based access control; and an LSTM AI music generative model creating genre-specific melodies evaluated with high listener consistency and novelty.

Data Analytics & AI Virtual Experience Participant at Accenture

October 1, 2025 - October 31, 2025

Completed Accenture's Data Analytics & AI virtual experience, performing data cleaning, predictive modeling, and delivering insights to simulated business problems; strengthened skills in Python and data visualization through hands-on tasks and stakeholder-style reporting.

Software Engineering Virtual Internship at JPMorgan Chase

September 1, 2025 - September 30, 2025

Optimized a financial data visualization interface, improving code quality, performance, and readability; integrated real-time data feeds and practiced Git-based version control in a production-style workflow.

Technology Consulting Virtual Experience at KPMG

June 1, 2025 - June 30, 2025

Analyzed digital transformation challenges for a simulated client and conducted data-driven assessments to identify improvement areas; created a structured technology roadmap, strengthening skills in solution design and automation recommendations.

Diabetic Retinopathy Classification - Project at Self-initiated / Academic Project

September 1, 2024 - May 31, 2025

Built a deep learning pipeline for multi-class classification (5 classes) of retinal images sourced from two datasets. Used OpenCV preprocessing (smart cropping, resizing, median blur) and data augmentation (flip, brightness, contrast, saturation) to expand the dataset to 100,000+ images. Designed a cascaded ensemble with ResNet50 as base classifier and specialist models (DenseNet, InceptionNet, MobileNet) to reduce inter-class confusion. Evaluated models with per-class metrics; cascaded ensemble improved F1-scores for minority classes by 5–8% over standalone models.

Violence Detection in Videos - Project at Self-initiated / Academic Project

January 1, 2024 - April 30, 2024

Designed and implemented a deep learning model to detect violent activities in surveillance videos, trained on a dataset of 2,000 labeled video clips. Incorporated attention mechanisms to enhance temporal feature extraction and improve detection of subtle violent actions. Experimented with multiple CNN/RNN architectures; best performance was achieved with transfer learning using MobileNet, reaching an accuracy of 94%. Validated against baselines and prior literature, achieving a 6–7% improvement in accuracy, precision, and recall.

College Management System - Project at Self-initiated / Academic Project

October 1, 2023 - December 31, 2023

Developed a scalable full-stack web application handling 500+ simulated student records for enrollment, attendance, and performance tracking with <200ms query response time. Integrated Firebase cloud storage, MongoDB NoSQL database, and authentication features; enabled secure role-based access for admin, faculty, and students. Streamlined workflows by reducing manual data entry by ~40% in simulation.

Music Generation with AI - Project at Self-initiated / Academic Project

April 1, 2023 - September 30, 2023

Implemented an LSTM-based generative model trained on 10,000+ MIDI sequences, composing melodies in genre-specific styles. Focused on melody generation with sequence modeling, producing compositions evaluated with 85% genre consistency by listeners and 4/5 on novelty and coherence in peer evaluation.

Accenture – Data Analytics & AI Virtual Experience at Accenture

October 1, 2025 - Present

Completed Accenture’s Data Analytics & AI Virtual Experience, performing data cleaning, predictive modeling, and delivering insights to simulated business problems. Strengthened skills in Python, data visualization, and business communication through hands-on tasks and stakeholder-style reporting.

JPMorgan Chase – Software Engineering Virtual Internship at JPMorgan Chase

September 1, 2025 - Present

Optimized a financial data visualization interface, improving code quality, performance, and readability. Integrated real-time data feeds, practiced Git-based version control, and enhanced debugging skills in a production-style workflow.

KPMG – Technology Consulting Virtual Experience at KPMG

June 1, 2025 - Present

Analyzed digital transformation challenges for a simulated client and conducted data-driven assessments to identify improvement areas. Created a structured technology roadmap, strengthening skills in solution design, automation recommendations, and business communication.