Rahul
Raghavendra Prasad

5 Zinzan Street · Reading · RG1 7UG ·· rahulrp@aimli.cloud

I have experience developing state-of-the-art models AI/ML models, Neural network optmisation, using BigData and ML and deep learning frameworks, creating visualisation dashboards and using statistical tools. I possess extensive expertise in handling complex analytical challenges within fast-paced, autonomous roles. Working as deep learning and machine learning Research assistant and internships have honed my leadership, problem-solving skills, and proficiency in AI and machine learning technologies.

Experience

AI/ML Engineer & Ops

[Founder]AIMLI.cloud

Develop and deploy Models on cloud for AI services.
Develop and Manage the website (AIMLI.cloud), database, data pipelines ,web pages, services.
Currently working on Large Language model chatbot (Gen AI)

June 2023 - Present

Knowledge Transfer Partnership (KTP) Assistant

Royal Holloway,University of London
  • Successfully deployed database systems and data automation tools
  • Utilized Microsoft Power Automate to streamline data processing from forums to databases
  • Processed and visualized data using Python
February 2023 - March 2023

Research Assistant - Deep Learning and Machine Learning

Royal Holloway,University of London
  • Developed and deployed high-accuracy neural network models for facial emotion recognition, action recognition, and image description generation
  • Built a real-time web application for facial emotion recognition using a webcam feed
  • Performed Hyper-parameter tuning using Particle Swarm Optimization (PSO) and Ant Colony Optimization
  • Applied Natural Language Processing (NLP) for text segmentation, POS tagging, tokenization, and stop-word removal, RNN( LSTM and GRU) for text generation
  • Technologies: Python, PyTorch, TensorFlow, OpenCV, Transformers, CNN, RNN (LSTM and GRU), Django, Flask, AWS (SageMaker, EC2, S3)
July 2022 - January 2023

Software Engineer, Machine Learning

Lilac Cloud PVT Ltd (Acquired by F5 Networks)
  • Built robust and accurate machine learning models for server load prediction, leading to cost savings
  • Gained insights from statistical models and clustering techniques for data analysis
  • Utilized Python, Scikit-learn, Pandas, NumPy, XGBoost, Time Series Analysis, Matplotlib, and Seaborn
April 2020 - July 2020

Education

Royal Holloway, University of London, UK

M.Sc. Artificial Intelligence

Distinction 78%

January 2022 - February 2023

Queen Mary, University of London, UK

PG-Cert Big Data Science

Pass

September 2018 - October 2019

National Institute of Engineering, University of Mysore, IND

Bachelors in Computer Applications

Distinction 74%

July 2014 - May 2017

Skills

Programming Languages & Tools
Proficient in Python, Java, SQL, MySQL, HTML, Flask, Git, C, C++, Azure Cloud Platform, AWS, DevOps/MLOps, JavaScript, MS Office, CI/CD pipelines, TensorFlow, PyTorch, Scikit-learn, NumPy, Pandas, OpenCV, MATLAB, PySpark, Hadoop, Matplotlib, NLP.
Soft Skills
  • Clear communication
  • Problem problem-solving
  • Creative
  • Critical Thinking
  • Time Management
  • leadership
  • Adapatability

Awards, Certifications & Publications

  • Amazon Web Services Solutions Architect Associate (Certification) by AWS :
    SYCLLFHK31VE13WX
    Verification link
  • Recipient of the Principal Master Scholarship at Royal Holloway University (2022).
  • Transfer Learning-Based Facial Emotion Recognition with PSO-Based Hyper-Parameter Tuning
    Link to Publication

Projects

  • Multimodal AI for Image & Text Analysis – Developed a multimodal AI system combining image classification and NLP (2023)
  • Image Classification using Deep Learning – Developed deep learning models for facial emotion recognition and image description generation (2022)
  • Real-Time Facial Emotion Recognition – Converted MSc project into a web application for real-time emotion detection (2022)
  • Machine Learning Algorithm Implementations – Implemented Logistic Regression, Random Forest, PCA, Hierarchical Clustering, and Conformal Predictors in Python (2022)
  • Football Score Prediction – Created a novel technique (‘Staged Hybrid Learning’) to predict football scores using a machine learning model (2019)
  • Ransomware Wallet Identification – Employed Big Data Processing to identify and visualize ransomware wallet transactions (2019)