Experienced Flutter developer with expertise in creating large-scale, cross-platform mobile applications for Android and iOS. Skilled in integrating Firebase for seamless backend solutions, implementing push notifications, and working with IoT and BLE (Bluetooth Low Energy) for connected devices. Proficient in developing AI chatbots and AI models, utilizing Cloud Functions, and integrating various APIs. Experienced in background/foreground services, data structures and algorithms (DSA), and state management (BLoC, Provider). Demonstrated ability to deliver high-quality, performance-oriented apps with a focus on user experience and reliability. Dedicated to staying updated with the latest industry trends and technologies.

As the Data Annotation and Innovation Lead at TrueClaim.ai, I entrusted the management of a team of data annotators, ensuring the seamless delivery of high-quality annotated datasets to our machine learning engineers. Throughout my tenure I:[x] Successfully recruited and managed a team of 7 individuals, effectively optimizing their performance and to elevate machine learning model accuracy to an impressive 97.2%, all while ensuring cost efficiency.[x] Continuously devised new annotation methods through critical analysis of our existing methodologies, striving for continuous improvement and enhanced efficiency in data annotation processes.[x] Conducted thorough market research for competitor analysis, enabling our product to stay competitive.

Built Strategy to drive growth through effective partnerships and business expansion.

As Director of the Endowment Fund, I orchestrated strategic growth, significantly increasing funding through successful fundraising initiatives. With a focus on impactful allocation, I empowered students through scholarships and academic support, fostering an environment conducive to learning. Collaborating closely with stakeholders, I exceeded growth targets, ensuring substantial contributions to our institution's mission.

The purpose of the research was to address the challenges related to traffic parking and vehicle roaming, aiming to enhance overall efficiency in parking systems. The primary goal was to develop a smart parking system model that could effectively reduce the unnecessary roaming of vehicles, minimize the time taken to find parking spaces, and provide a seamless experience for drivers.By integrating cutting-edge technology (JAVA OOP & AI) and advanced simulations, the research aimed to create a global smart parking system that would enable drivers to easily identify the nearest available parking slots. This would not only streamline the parking process but also reduce traffic congestion and carbon emissions associated with vehicles searching for parking.The ultimate objective was to optimize parking management and utilization, offering a more convenient and sustainable solution for both drivers and parking authorities. Implementing such a system would contribute to reducing traffic-related stress, enhancing the overall flow of urban transportation, and fostering a more eco-friendly approach to parking.