Pragatindu Yajnashree Parida

Mr. Pragatindu Yajnashree Parida holds a B.Tech in Information Technology with a specialization in Cloud Computing. He has corporate experience in mobile application development and has worked across multiple domains in the corporate technology sector. His areas of expertise include Artificial Intelligence (AI), Machine Learning (ML), Cloud Security, High-Performance Computing (HPC), and Big Data Analytics.

His research on Cloud Security and related technologies reflects a deep understanding of data protection, scalability, and secure cloud architecture. With strong interdisciplinary knowledge and technical proficiency, Mr. Pragatindu is committed to developing innovative solutions that advance the fields of intelligent systems and high-performance computing.

Mr. Pragatindu Yajnashree Parida’s research areas include Cloud Security, Artificial Intelligence, Big Data Analytics, High-Performance Computing, Cloud Computing, Machine Learning, and Data-Driven Technologies. His work reflects a strong understanding of secure, scalable, and efficient computing systems. He also possesses professional experience in mobile application development and a solid technical foundation across emerging technologies.

Conference Paper:

• Cloud Security Using Deep Learning – ANN Approach
  April 2025
  DOI: 10.1109/ICKECS65700.2025.11035248
  Presented at the 2025 International Conference on Knowledge Engineering and Communication Systems (ICKECS)

1. AI-Based Medical Diagnosis System

• Developed an AI-driven medical diagnostic platform for early detection of diseases using patient data and imaging datasets.
• Implemented machine learning and deep learning models for predictive analysis and automated diagnostic recommendations.
• Designed user-friendly front-end interfaces and a robust backend system to securely store patient data and medical history.
• Enabled faster and more accurate clinical decision support, improving patient care efficiency.

2. Cyclone Intensity Estimation Based on Deep Learning Using INSAT 3D Images

• Developed a deep learning-based system to estimate cyclone intensity using INSAT 3D satellite images.
• Designed and implemented front-end interfaces for user interaction and back-end services using Flask and PostgreSQL.
• Integrated PyTorch to build and train the machine learning pipeline, enabling accurate cyclone intensity prediction.
• The system provides real-time data analysis and visualization for meteorologists and disaster management authorities.

3. Mobile Application Development – Pilot Training App(IndiGo)

• Developed a React Native-based mobile application for IndiGo Airlines’ pilot training program.
• Built a Competency-Based Training Platform (CBTP) with multiple features for training evaluation and progress tracking.
• Integrated APIs, optimized UI/UX, and ensured cross-platform functionality on iOS and Android.
• Managed the end-to-end development cycle, from feature design to deployment, delivering a scalable and user-friendly solution.

4. E-Learning Web Platform

• Developed an interactive e-learning web platform using HTML, CSS, and JavaScript for a responsive front-end.
• Implemented Python back-end logic, including data fetching and management from MySQL databases.
• Created a user-friendly system for accessing educational content, tracking progress, and managing user interactions.
• Integrated features such as quizzes, progress tracking, and content management to enhance learning experience.

5. High-Performance Computing (HPC) Optimization Projects

• Implemented parallel computing algorithms to accelerate data-intensive applications.
• Utilized multi-core and GPU-based computation to optimize large-scale AI and Big Data analytics workflows.
• Developed HPC pipelines for real-time simulation, data processing, and predictive modeling, improving computational efficiency and scalability.
• Demonstrated significant speedup and resource optimization for complex scientific computations and machine learning workloads.

6. Cisco Networking Project – University Network Security Design

• Designed a secure and scalable network architecture for a university using Cisco Packet Tracer.
• Implemented multi-layer topology including core, distribution, and access layers to ensure high availability and robust security.
• Configured firewalls, VLANs, and access control policies to protect sensitive academic and administrative data.
• Simulated and tested network traffic, routing, and intrusion scenarios to evaluate security and performance.
• Developed strategies to detect and mitigate cyber threats, ensuring a reliable and secure campus network environment.

• Participant in IEEE event 2022
• Participant in TECHNOFAIR 2023
• 1st Runners Up in Alliance One Event 2023
• Volunteered For Alliance Literary Festival 2022
• 3rd place in 5km Marathon 2023

• Machine Learning Regression, University of Washington-October 2023
• Networking in Google Cloud Specialization, Google Cloud-November 2023
• Developing Front-End Apps with React, IBM-March 2024

• Institute of Electrical and Electronics Engineers
• Project Management Institute
• Society of Human Resource Management