Srujan rana

Srujan Rana

AI/ML Engineer

ranasrujan@gmail.com

Welcome to My Portfolio!

Hi there, I'm Srujan Rana, an AI/ML enthusiast and tech explorer driven by a passion for solving real-world problems using cutting-edge technology. With a strong academic foundation in AI/ML and Data Science from SUIIT

During my research internship at NIT Raipur, I developed a real-time voice stress analyzer using CNN-BiLSTM, achieving 92% accuracy and reducing inference time by 80%. This project was guided by Dr. Pradeep Singh, HOD of CSE at NIT Raipur.

I’m passionate about applying AI to real-world challenges and continuously grow through side projects, research, and tech competitions. One such highlight was becoming a Hackfest Hackathon finalist, where I showcased my ability to think creatively under pressure.

Welcome to my portfolio — a snapshot of my journey, accomplishments, and the road ahead. Feel free to check out my Résumé.

Interests
  • Research
  • Algorithms
  • Generative AI
  • Deep Learning
  • Machine Learning
Education
  • Bachelor of Science (Data Science),2024 - 2028

    IIT Madras (Indian Institute of Technology Madras),

    Bachelor of Technology (Artificial Intelligence and Machine Learning),2022 - 2026

    SUIIT (Sambalpur University Institute of Information Technology)

Experience

 
 
 
 
 
Summer Research Intern
May 2024 – Jun 2024 Onsite
  • Developed a voice stress analysis model using Mel Frequency Spectrogram features under Dr. Pradeep Singh, HOD, CSE at NIT Raipur.
  • Integrated CNN with BiLSTM and a self-attention layer to enhance pattern recognition and model performance.
  • Achieved 92% accuracy with 80% improvement in efficiency via extensive hyperparameter tuning.
  • Deployed the model on Google Cloud with a Flask interface for real-time usage.
> See Certificate
 
 
 
 
 
Technical Content Writer
Daily Tech Suggest
June 2023 – August 2023
  • Specialized in creating clear and engaging content to explain complex AI/ML concepts.
  • Wrote SEO-optimized blogs, product documentation, and API guides to boost web traffic.
  • Collaborated with developers and teams to deliver impactful and informative resources.
  • Skilled in tools and strategies for SEO, Python, and machine learning frameworks.
See Certificate View Blogs

Skills

AI & Data Science

1+ Years XP

Machine Learning

Deep Learning

Data Visualization

Predictive Modeling

Statistical Analysis

Computer Vision

Game Development

1+ Years XP

Unity - AR(AR-core)

Unity _3d

Unity - VR(Meta XR)

Programming

2+ Years XP

Python

Java

C

SQL

Cloud Computing

1+ Years XP

Google Cloud Platform

Docker

Front End

1+ Years XP

HTML

CSS

Figma

Canva

Back End

1+ Years XP

Python - Flask

Python - Django

Python - FastAPI

MLOps & Deployment

1+ Years XP

ML Lifecycle Management

Model Deployment

Serving APIs (FastAPI, Flask)

Miscellaneous

2+ Years XP

Git & GitHub

Linux

DevOps Practices

Software Development

Accomplish­ments

Geospatial Analysis using Google Earth Engine
  • Gained hands-on experience in utilizing Google Earth Engine for large-scale geospatial data analysis and visualization.
  • Learned advanced techniques for processing satellite imagery and deriving insights for environmental and land-use studies.
  • Developed skills in scripting and automation for geospatial workflows using the Earth Engine JavaScript API.
  • Explored real-world applications such as forest cover mapping, urban growth analysis, and water resource management.
View Certificate
Generative AI for Everyone
  • Learned the fundamentals of generative AI, how it works, and how it’s used in real-world applications.
  • Explored ethical implications, limitations, and opportunities in applying generative technologies responsibly.
  • Understood how tools like ChatGPT, DALL·E, and other foundation models are transforming various industries.
  • Discussed practical strategies for integrating generative AI into products, services, and workflows.
View Certificate
Supervised Machine Learning: Regression and Classification
  • Mastered core ML techniques like linear regression, logistic regression, and decision trees with real-world datasets.
  • Built and evaluated models with strong emphasis on bias-variance tradeoff and model generalization.
  • Learned to use loss functions and gradient descent for optimizing supervised learning algorithms.
  • Worked with tools like Python, Jupyter, and Scikit-learn to implement practical ML solutions.
View Certificate
Data Science Essentials
  • Gained a solid foundation in statistics and programming concepts for data science.
  • Learned to write basic Python code and use it for handling data and solving simple problems.
  • Understood key ideas like averages, variance, data distributions, and visual representation of data.
  • Explored how data is used in decision-making and predictions in real-life applications.
View Certificate

Contact Me

Feel free to connect with me through the following channels: