Harsh Shah

I have 3+ years of hands-on experience as Software Engineer in software development. I have done my specializing in designing, integrating, and testing virtual controller models and components for dynamic simulations in automotive systems. I’m proficient in using Python (4 years), MATLAB(4 years), and Simulink(4 years), with a solid understanding of automotive communication protocols. Skilled in developing and parameterizing subsystem models, integrating plant models, and maintaining detailed documentation. Adept at troubleshooting and providing support for released simulations. Organized and dependable candidate successful at managing multiple priorities with a positive attitude. Willingness to take on added responsibilities to meet team goals. Complex problem-solver with analytical and driven mindset. Dedicated to achieving demanding development objectives according to tight schedules while producing impeccable code.

1) Fire Detection and Surveillance, 09/01/22, 12/01/22, Associated with Durham College. As a dedicated software developer in the Fire Detection and Surveillance project, I led the development and implementation of cutting-edge technologies to enhance fire safety and security measures. The project aimed to deploy advanced surveillance systems coupled with intelligent fire detection algorithms, ensuring rapid and accurate response to potential fire incidents. I spearheaded the development of an advanced Fire Detection and Surveillance System, leveraging cutting-edge technologies to enhance fire prevention and safety measures. Our system, deployed in commercial and residential buildings, received accolades for its effectiveness in mitigating fire-related risks and safeguarding lives and assets. Collaborating with emergency services and stakeholders, I facilitated seamless integration with response protocols, contributing to community safety and resilience., Successfully deployed the Fire Detection and Surveillance System in commercial and residential buildings, reducing fire-related incidents and minimizing property damage. Received commendation from clients for the system's effectiveness in early fire detection and rapid response, ultimately saving lives and safeguarding assets. Contributed to community safety by enhancing fire prevention measures and fostering collaboration between stakeholders in emergency response efforts., Sensors: Thermal Cameras, Smoke Detectors, Machine Learning: Convocational Neural Networks (CNNs), Communication Protocol: MQTT, Visualization: GIS (Geographic Information Systems)                                                                                                     2) Stock Price Prediction, 09/01/22, 12/01/22, Associated with Durham College. In this exciting project, I leveraged machine learning and data analysis techniques to predict stock prices, contributing to the ever-evolving landscape of financial technology. Data Collection, Feature Engineering, Machine Learning Models, Time Series Analysis, Evaluation Metrics, Visualization, Risk Management and Continuous Improvement., The project resulted in a robust stock price prediction model, providing valuable insights for informed decision-making in the financial domain. The successful implementation demonstrates the power of combining data science and finance to navigate the complexities of the stock market., Python, Pandas, NumPy, Scikit-learn, TensorFlow, Kera’s, Matplotlib, Web scraping and APIs for data retrieval.                                                            3) Bus Reservation System, 01/01/21, 05/01/21, Associated with SSIU. I played a pivotal role in developing a robust Bus Reservation System during the COVID-19 pandemic, aimed at facilitating safe and efficient bus bookings. Leading the project's design phase, I collaborated closely with team members to architect scalable solutions. Leveraging technologies like Python/Django for backend development and HTML/CSS/JavaScript for frontend, I ensured a seamless user experience. Incorporating COVID-19 safety measures such as seat distancing algorithms and mask detection alerts, the system received positive feedback for its user-friendly interface and adherence to safety guidelines. Deployed on cloud platforms like AWS/Azure, the system contributed significantly to the revival of the bus transportation industry, providing a critical service amidst the pandemic., Successfully launched the Bus Reservation System, catering to a significant increase in demand for safer travel options during the COVID-19 pandemic. Received positive feedback from users for the system's user-friendly interface and seamless booking experience. Contributed to the revival of the bus transportation industry by providing a reliable and convenient booking platform amidst the pandemic., Frontend: HTML, CSS, JavaScript, Backend: Python, Django, Database: PostgreSQL