Motivated and accomplished Software Engineer with a Ph.D. in Computer Science and a robust track record spanning over 15+ years in IT and services industry. Specializes in back-end development, SQL and NoSQL database systems, adept at diverse programming languages such as Java, Python, and Bash Script. Extensive competency in Development and Management with a proven ability to thrive under pressure while consistently meeting stringent deadlines. A lifelong learner passionate about remaining at the forefront of emerging technologies. Recognized for an immense enthusiasm in artificial intelligence, with a solid grasp on concepts such as neural networks, deep learning, modeling and NLP. Continually involve in hands-on project development to deliver impactful solutions, always striving to lead, innovate, and elevate performances in the field of AI and beyond.
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Responsibilities:
Responsibilities:
Responsibilities:
Responsibilities:
This project on GitHub leverages Jupyter Notebooks for experimenting with various neural network models using AI frameworks like Hugging Face, LangChain, Transformers, and others. The functionality is further enhanced by leveraging various GPT APIs including ChatGPT. The project seeks to explore diverse approaches to AI and language processing, demonstrating proficiency in adapting to a range of technology platforms.
View ProjectThe School Registration System is a comprehensive back-end application developed in Java 8 and Spring Boot. It provides a REST API for managing school data including students and courses, supporting operations like profile creation and advanced data filtering. It offers specific features such as pinpointing students per course, identifying unenrolled courses, and finding students without courses. Reliability is ensured via JUnit-powered tests and the Docker technology used allows for convenient containerization and portability, making this system a scalable and efficient solution for academic registration management.
View ProjectThe Dealer Rater Crawler, built with Java 8, is a sophisticated back-end system that effectively crawls and analyzes car dealer reviews. By scraping the initial five pages of feedback, it identifies and highlights the top three most "overly positive" reviews, presenting them in the console for immediate insight. The system guarantees reliability through comprehensive JUnit testing and efficient data extraction with HtmlUnit. It employs Stanford NLP for accurate sentiment analysis, ensuring correct identification of overly positive reviews. This unique combination of web crawling and sentiment analysis positions the Dealer Rater Crawler as a valuable tool for both car dealers and consumers.
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