"Welcome to my portfolio! I am Mohammed Saqlain Patel, a passionate software developer with a Master's in Computer Science from California State University Long Beach. With over 3 years of professional experience at Tata Consultancy Services, I specialize in Java and Spring Boot development, alongside proficiency in a diverse range of technologies including REST API, Microservices, and cloud platforms like AWS and Azure.
My career journey is defined by hands-on expertise in creating robust applications, from designing and deploying enterprise solutions to implementing cutting-edge technologies. I have successfully contributed to diverse projects, including a Women Safety Application for Android, a Face Recognition system using OpenCV, and an Ecommerce platform using MEAN stack.
Explore my portfolio to discover more about my projects, skills, and achievements. Let's collaborate and innovate together to shape the future of technology!"
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California State University Long Beach
Graduation: Dec 2024
Vnr Vignana Jyothi Institute of Engineering and Technology
Graduation: Aug 2021
I bring over 3 years of experience as a Java Developer, proficient in the full SDLC from analysis to maintenance. Specializing in Agile methodologies like Scrum with Jira, I excel in designing Microservices, implementing RESTful APIs with Spring Boot, and ensuring application security. My expertise includes Core Java, MySQL, ORM frameworks like JPA, and extensive experience in testing with tools like POSTMAN and SOAP. I'm adept at collaborating in Agile teams, managing JIRA issues, and maintaining high coding standards to deliver efficient solutions aligned with stakeholder needs.
With a strong foundation in Core Java, I handle serialization, multi-threading, and robust exception handling with ease. I've deployed applications using Jenkins, conducted thorough testing with Junit, Karate, and Mockito, and maintained version control with GIT. My proactive approach to bug fixing and continuous improvement ensures smooth project operations. I prioritize stakeholder collaboration to deliver high-quality solutions that meet and exceed expectations.
As an intern at Tata Consultancy Services, I took on the responsibility of managing RESTful APIs, ensuring their reliability, maintainability, testability, and reusability. I conducted thorough testing by validating parameters in XML using SOAP, contributing to the overall robustness of the codebase.
During my internship at Kahaniya Private Ltd., I gained hands-on experience in web development, data management, and cloud-based deployment strategies. I successfully optimized data retrieval from MongoDB through Redis caching, enhancing system efficiency. Additionally, I implemented Gmail OAuth for secure automated email notifications using SendGrid, and integrated OTP verification via Msg91, contributing to robust security protocols and seamless user interactions. These experiences deepened my understanding of modern web technologies and cloud solutions, preparing me to tackle complex challenges in software development.
Developed some interesting features in a dynamic travel website that facilitated flight and hotel bookings. In this role, I oversaw the development of various components, utilizing a tech stack centered around React JS, Node JS, Express JS, and MongoDB for seamless real-time functionality. This allowed for a user-friendly and efficient experience, ensuring smooth navigation and booking processes for our customers.
During my internship, I immersed myself in Android app development, specializing in UI design with components such as ConstraintLayout, LinearLayout, and RelativeLayout. I gained proficiency in displaying images using drawable vector graphics, ensuring a visually appealing user experience.
My work centered on enhancing app functionality through the Volley HTTP library, mastering API data retrieval and optimizing network communication in Android applications. I also successfully integrated Place Autocomplete using the Google API, elevating the app's location-based features and further honing my skills in API integration and dynamic app development.
This internship not only solidified my technical capabilities but also instilled a passion for crafting seamless user experiences and leveraging cutting-edge technologies to enhance app performance.
Developed a versatile cross-platform application seamlessly operating on various devices. Powered by JavaScript, it leverages the MERN stack for robustness - MongoDB for data management, Express.js for API creation, React.js for dynamic UI, and Node.js for a swift backend. Adding to this, the Ionic Framework ensures a native-like experience across platforms. What sets this application apart is its recommendation engine, fortified with Natural Language Processing. This engine deciphers user-generated content, unveiling insights and sentiments to offer personalized suggestions. It's a fusion of technology and human understanding, promising an unmatched user experience. Welcome to a new standard in cross-platform applications.
Led a dedicated team of four in the development of a cutting-edge women's safety native application using the Ionic Framework. This innovative app serves as a crucial tool in assisting individuals during emergency situations by monitoring their pulse rate in real-time. Our project was driven by a strong sense of social responsibility, aiming to provide women with a reliable and accessible means of ensuring their safety. Through meticulous planning, collaborative efforts, and a deep understanding of both the Ionic Framework and pulse rate monitoring technology, we successfully created a powerful application that addresses a critical need in today's society. Our collective commitment to this cause has resulted in a solution that empowers individuals and promotes a safer environment for all.
Developed a system utilizing Convolutional Neural Networks (CNNs) to recognize various sign languages, aiming to facilitate communication for deaf and mute individuals. These CNNs, specialized deep learning models proficient in processing image data, underwent extensive training on a diverse dataset of annotated sign language gestures. Through this process, the network learned to discern unique features and patterns specific to each sign, allowing it to generalize its knowledge and effectively recognize a wide range of gestures.
Engineered a model using Python, OpenCV, TensorFlow, and Keras to monitor employee efficiency through face recognition and human tracking. This adaptable solution underwent thorough testing in diverse environments to guarantee its precision and dependability. By seamlessly integrating these cutting-edge technologies, the model not only accurately identifies employees but also offers real-time feedback on their performance, ultimately boosting operational efficiency across a range of work environments. This innovative tool has the potential to significantly optimize workforce productivity and streamline operations.