My Stack

StressDucer is a mobile application developed myself designed to help users reduce their stress levels effectively. This app provides various features to assist students in managing their time efficiently and minimizing stress. Especially created for university students to reduce stress by using auto-generated timetables and more. Also using this you will be able to test your stress level as well.

I developed this app for two months. I got a lot of advice from different people like doctors, and lecturers as well. Also, I collected data from my friends who have more stress than normal people.

So I think this app will help every student who has stress. I hope to develop the feature of a generating timetable in the future. That feature was developed using my algorithm. Most of the time of developing this app was spent thinking about how to generate the timetable. I think this timetable gives you a more efficient timetable.

Skills

Programming | Time Management | Flutter | Mobile Applications | Software Engineering Practices

This project is about a Mixed Reality Simulation Platform for SWARM Robotics. This platform merges the physical and the virtual reality and allows us to run SWARM behavioral experiments using robots in both realities in the same environment. This system consists of five main components, which are physical robots, virtual robots, the localization system, the visualizer, and the SWARM simulator.

I was responsible for implementing the Java-based Virtual Robot, creating virtual robots that behave like their physical counterparts. This involved developing communication features, building interaction with the simulator, and managing sensor data. My contributions included setting up the Java environment, creating installation guides, and ensuring seamless integration with other system components. I fully developed the Maze following the robot class. Here I programmed a robot to figure out the right path and navigate the maze environment.

The robot firmware was implemented to support swarm behavioral implementations. It interacts with various sensors and functionalities while communicating with the simulator and other components in near real-time.

Skills

java | Spring Boot | Management | Communication | Mqtt | Software Documentation | Problem Solving

In this study, we propose a novel approach utilizing an apparatus that enables users to walk in place while supported by a support rig, coupled with inertial measurement unit (IMU) sensors at the feet to capture locomotion data. Our research focuses on analyzing the gait patterns of users during locomotion and employing Long Short-Term Memory (LSTM) networks, a specialized form of Recurrent Neural Networks (RNNs), to classify different types of locomotion, including walking, running, turning, and reversing.

Skills

Augmented Reality (AR) | Virtual Reality(VR) | Time Management | Machine Learning | Artificial Intelligence(AI) | Flutter | Mechanical Engineering