Simran Kaisher

A recent graduate in Computer Science and Engineering, I am an eager and industrious individual with a drive to combine theoretical knowledge with practical skill. Competent in a variety of paradigms, primed to contribute dynamic insights while embracing collaborative challenges. Seeking to leverage comprehensive education to excel within a growth-oriented professional environment.

Languages: Java, C++, C, Python, HTML/CSS

Databases: MySQL

Developer Tools: VS Code, Eclipse, Google Cloud Platform, AWS Cloud Platform

Technologies/Frameworks: Jenkins, Maven, MySQL Workspace, Mongo Compass, Sonarqube, Kubernetes, Linux OS, Git/Gerrit, DockerHub, Grafana, Prometheus

Predicting Brain Tumor Using Machine Learning Algorithms

• The dataset gathered from the open source UCI Machine Learning Repository which contains 395 training and 105 testing MRI images in .jpg format.
• Preprocessing done on signal to noise-ration, upgrading the visual appearance of MRI images, eliminating the unimportant noise and undesired parts in the background, smoothing the internal piece of the area, and protecting its edges.
• Accuracy of 96.0% is achieved by using a support vector machine algorithm.

Handwritten Text Detection Using Deep Learning

• Implemented a deep learning-based system to detect and recognize handwritten text from images.
• Employed convolutional neural networks (CNNs) for image feature extraction and text localization, followed by sequence models like Long Short-Term Memory networks (LSTMs) for text recognition.
• Utilized Python programming language along with TensorFlow and Keras libraries for model development and training.
• Achieved an accuracy of 95% on a benchmark dataset, demonstrating robust performance in detecting and transcribing handwritten text under varying conditions.

Efficient Home Management System using Raspberry Pi Pico W and Blynk 2.0

• Developed an IoT-based home management system leveraging Raspberry Pi Pico W microcontroller and Blynk 2.0 platform. The project aimed to automate and monitor various household tasks and appliances for enhanced efficiency and control.
• Integrated sensors and actuators with Raspberry Pi Pico W to monitor environmental parameters and control home appliances remotely via the Blynk 2.0 mobile app. Implemented features such as alerts to improve user convenience.
• Successfully deployed and tested the system in a home environment, demonstrating reliable operation and seamless integration with household devices.

• Introduction to Minikube: Docker & Kubernetes through LinkedIn Learning
• Cloud Fundamentals: AWS & Azure through LinkedIn Learning
• Crash Course in Python through LinkedIn Learning
• Generative AI through Coursera
• Linux Fundamentals through Persistent Systems
• Database Management System by Persistent Systems
• Java Fundamentals
• DevOps and DevSecOps

TEDx SOA University 2022

• Worked as the Head of Content Ideation and Management
• Co-convened on various managerial and executive tasks with brands like Social Nation.

SOA MUN 2021 & 2022

• Secured the High Commendation award from the International Press Committee in 2021 edition.
• Mentored the Content Management team for 2022 edition and managed a team of 8 anchors.

State Opens Odisha 2020

• Achieved Gold Medal in Athletics (Long Jump) and qualified for the State Opens competition.

Inter-University Debate Championship | SOA University 2020

• Eloquently articulated my viewpoints, earning accolades as a persuasive and articulate speaker amidst fierce competition from VIT Chennai, VIT Vellore, and CUSAT in October, 2020.

• Data Structures and Algorithm
• Cloud Computing
• Database Management Systems
• Computer Networking
• Object-Oriented Programming
• DevOps