Sai Chakrin Yanamadala

Aspiring Data Scientist & Machine Learning Engineer
Hyderabad, IN.

About

Highly motivated Computer Science and Engineering student with a strong foundation in data analysis, machine learning, and IoT systems, seeking to leverage robust technical skills in Python, SQL, and deep learning frameworks to drive impactful data-driven solutions. Proven ability to develop and deploy complex models, create interactive visualizations, and lead projects from conception to implementation, aiming for roles in Data Science, Machine Learning Engineering, or AI/ML Development.

Work

Vilindha Technologies
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Python Data Analyst

Hyderabad, Telangana, India

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Summary

As a Python Data Analyst, I was responsible for transforming raw data into actionable insights through advanced visualization and reporting, utilizing a suite of tools to support data-driven decision-making.

Highlights

Developed interactive visualizations and dashboards using Power BI, Excel, Matplotlib, and Pandas, enhancing data interpretability for stakeholders.

Applied SQL extensively to query relational databases and generate comprehensive data reports, improving data accessibility and reporting efficiency.

Gained hands-on experience in machine learning fundamentals, implementing basic predictive models and pattern recognition techniques to extract valuable insights from complex datasets.

Volunteer

National Service Scheme
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Logistics and Management Committee Lead

Chennai, Tamil Nadu, India

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Summary

Led a team of 40 members in organizing and managing NSS activities, ensuring smooth execution of events and community outreach programs.

Highlights

Directed a 40-member team in planning and executing diverse NSS activities, significantly enhancing community engagement and program impact.

Optimized logistical operations for various outreach programs, ensuring efficient resource allocation and seamless event execution.

Education

Vellore Institute of Technology
Chennai, Tamil Nadu, India

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Bachelor of Technology

Computer Science and Engineering

Grade: CGPA: 8.33

Telangana State Board of Intermediate Education
Hyderabad, Telangana, India

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Senior Secondary (Class XII)

MPC Stream (Mathematics, Physics, Chemistry)

Grade: Percentage: 96.6%

Publications

A Secure System to Detect Animal Intrusion and Notify Users in a Farmland

Published by

Springer

Summary

Developed a secure IoT animal intrusion detection system using Raspberry Pi and PIR sensors for real-time monitoring. Integrated a deep learning model (EfficientNetB3) to classify animals with 95% accuracy and implemented AES encryption for secure image storage and sharing. Built a desktop app and email alert system for authorities, ensuring cost-effective, scalable monitoring for rural farmlands.

Languages

English

Certificates

AWS Certified Cloud Practitioner

Issued By

AWS

Google Cloud Digital Leader

Issued By

Google Cloud

Skills

Programming Languages

Python, C, C++, Java, JavaScript, TypeScript, HTML, CSS, MySQL, Flask, React, MongoDB, PostgreSQL.

Data Science & ML Frameworks

PowerBI, Tableau, Machine Learning, Google Collab, MatLab, Github, Data Structures, Algorithms.

Cloud Platforms

AWS (EC2, S3, IAM, RDS), GCP (Compute Engine, Cloud Functions, BigQuery, IAM).

Machine Learning

Deep Learning, EfficientNetB3, VGG19, Vision Transformer (ViT), U-Net, Grad-CAM, Regression Models, Classification Models (Ridge, MLP, RF, DT).

Data Analysis & Visualization

Power BI, Tableau, Excel, Matplotlib, Pandas, SQL.

IoT & Embedded Systems

Raspberry Pi, PIR Sensors, Arduino, Sensors, GPS, Bluetooth.

Natural Language Processing

Dialogflow, Chatbot Development.

Projects

Explainable Brain Tumor Segmentation using VGG19-ViT Enhanced U-Net and XAI

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Summary

Designed a hybrid deep learning model for brain tumor segmentation from multi-modal MRI scans, integrating VGG19 and Vision Transformer (ViT) with a custom U-Net architecture to enhance interpretability.

Campus Companion: NLP-Powered Chatbot for VIT Chennai

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Summary

Developed an advanced university-specific chatbot for VIT Chennai, leveraging Dialogflow and Python with FastAPI to provide seamless, responsive user interactions and efficient data management.

Runtime Monitoring of Diabetes Using ECG Signals and Machine Learning

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Summary

Developed a runtime system for non-invasive glucose monitoring using ECG-derived features from wearable sensors, integrating machine learning models and temporal logic for high-accuracy event detection.

RIDE SHIELD: Call Filtering System for Safer Biking

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Summary

Designed and implemented an IoT-based call filtering system using Arduino, sensors, GPS, and Bluetooth to enhance biker safety by blocking calls while riding and prioritizing emergency notifications.