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

AIMLI.cloud

Develop and deploy Models on cloud for AI services.
Develop and Manage the website (AIMLI.cloud), database, data pipelines ,web pages, services.
Working on upcoming services - XGBoost decision trees, Image processing to increase resolution, remove blur from images, Action recognition, Emotion recognition, Image description generation, Large learning model (Gen AI)

May 2023 - Present

Knowledge Transfer Partnership (KTP) Assistant

Royal Holloway,University of London

Deploy Database systems, Microsoft Lists, MS Excel, and Forums, automated storing the submitted Contact forums into the database through MS Power Automate, speeding up the process and improving efficiency. Process Data and visualisation using Python

February 2023 - March 2023

Research Assistant - Deep Learning and Machine Learning

Royal Holloway,University of London

Trained and deployed neural network models for Facial emotion recognition, Action recognition and image description generation. Developed models with high accuracy on Image description generation by fine-tuning the hybrid neural network using Particle Swarm Optimisation. Improvised emotion recognition model by making it usable in real-time, making it a web app taking a live feed from the camera and instantly giving out the prediction.

July 2022 - January 2023

Software Engineer, Machine Learning

Lilac Cloud PVT Ltd (Acquired by F5 Networks)

Successfully built Machine learning models in a constantly evolving and challenging environment. ML models had High accuracy and robustness even for evolving data. Extract valuable insights using Statistical models and clustering techniques to analyse the data. Fulfilled the requirement of my internship project to build ML model that can accurately predict server loads helping the company to save on server resource cost. Used python to preprocess data and to generate data visualisation.

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