Specializing in architecting robust and scalable software systems and leveraging AI technologies.
I am a Master of Science student in Computer Science at the University of Southern California. With 3+ years of professional experience as a software engineer, I specialize in architecting and developing robust and scalable applications. My expertise includes designing efficient backend systems, optimizing database performance, and ensuring seamless API integrations. I am passionate about leveraging technology to solve complex problems and deliver high-quality solutions. Constantly staying updated with the latest advancements in software development, I explore new frameworks and methodologies to enhance project efficiency and performance. As a dedicated team player, I have successfully contributed to multiple projects, collaborating closely with cross-functional teams to achieve project milestones effectively.
In addition to backend development, I have a keen interest in machine learning and its applications. My curiosity drives me to stay abreast of the latest developments in AI and machine learning, actively seeking opportunities to apply these technologies to innovate and improve software solutions. I value collaboration and empathy, which have been instrumental in my role as a software engineer, ensuring alignment between technical implementation and business objectives.
Master of Science in Computer Science (Honors) | January 2023 - December 2024
π GPA: 4.0/4.0
Coursework: Analysis of Algorithms, Database Systems, Machine Learning for Data Science, Applied Natural Language Processing, Deep Learning and its Applications, Information Retrieval and Web Search Engines.
Bachelor of Engineering in Electronics and Computer Engineering | June 2015 - June 2019
π GPA:3.7/4.0
Coursework: Data Structures and Algorithms, Machine Learning, Database Management Systems, Operating Systems, Embedded Systems, Digital Signal Processing, Image Processing, Natural Language Processing, VLSI, Computer Architecture.
Programming Languages and Databases: Python, Java, C/C++, HTML, CSS, JavaScript, MySQL, MongoDB, Vector Databases, Pinecone, AstraDB, Redis.
Technologies: Microservices, Docker, Kubernetes, SpringBoot, REST/SOAP APIs, Git, Linux, CI/CD, Elasticsearch.
Libraries/Frameworks: Flask, Numpy, Pandas, Tensorflow, PyTorch, Scikit-learn, LangChain, React, NodeJS.
Visualization Tools: Tableau, Power BI, Python: Matplotlib, Seaborn.
Cloud Platforms: AWS(Amazon Web Services), GCP(Google Cloud Platform).
AI/ML: Deep Learning, Computer Vision, NLP, Quantization, Generative AI.
Developer Tools: Postman, Jupyter, MobaXterm, Putty, Bitbucket, Visual Studio Code, JIRA, Confluence.