United States
About Me With a Master’s degree in Computer Science from the University at Buffalo and professional experience as a Software Engineer at Samsung India Electronics Pvt. Ltd. (R&D), I have built a strong foundation in software engineering, Android development, systems programming, and machine learning. During my time at Samsung, I worked on performance-sensitive applications, including an Android-based document classifier app that achieved 83% accuracy using TensorFlow Lite and computer vision techniques, improving mobile gallery organization and retrieval. I also contributed to research on power-saving mechanisms in multi-hop D2D communication, strengthening my expertise in networking, optimization, and low-level system behavior. My Mission and What Drives Me I am passionate about building scalable, efficient, and reliable software solutions that solve real problems and enhance user experience. I enjoy working across the stack, from clean UI implementation with Jetpack Compose and Kotlin to backend logic, Retrieval-Augmented Generation (RAG) pipelines, agentic AI systems, data processing, and performance tuning. My skills include C++, Python, TensorFlow, PyTorch, LangChain, LlamaIndex, MVVM/Clean Architecture, CI/CD, Coroutines, and production ML deployment. I’m driven by curiosity, continuous learning, and turning complex ideas into practical, production-ready products. What I’m Looking to Do in the Future I am seeking software engineering roles where I can build impactful products, deepen expertise in Android development, agentic AI, RAG systems, LLMs, computer vision, NLP, system design, and scalable applications. I want to tackle challenges in data structures, algorithms, debugging, optimization, and clean architecture while contributing to innovative teams that value ownership and high-quality engineering. A Little Personal Touch Outside of coding, I express creativity through dance as Head Choreographer of my college dance club and enjoy organizing large-scale sports events, building leadership and collaboration skills. I thrive on learning, adapting, and new challenges. Let’s connect!
Working with Dr. Johannes Hachmann, on developing machine learning pipelines for FTIR/NIR spectroscopy data to group similar textile fibers and analyze possible labeling inconsistencies. Built preprocessing, clustering, and visualization workflows in Python to handle real-world spectral datasets with varying frequency ranges and resolutions.
• Assisted in teaching MGO 634 Project Management, enhancing students' understanding of project management principles. • Facilitated hands-on learning with Kanban boards and Smartsheet for effective project tracking. • Supported diverse student needs, fostering an inclusive learning environment that improved overall course engagement.
• Assisted in delivering coursework for the Intro to Machine Learning (CSE574) course at the University at Buffalo. • Guided students through foundational ML concepts, enhancing their understanding and application of the material. • Conducted office hours to address student queries, resulting in improved academic performance and engagement.
- Developed and implemented an Android-based document classifier app, enabling seamless integration into Samsung mobile galleries. Achieved an impressive classification accuracy of 80%, which significantly improved document organization and retrieval times, enhancing user experience. - Executed the deployment of Frame Interpolation models on mobile devices using Android Studio by converting them into TensorFlow Lite (TFLite) models. This innovation facilitated the creation of videos utilizing generative AI, effectively interpolating between frames to deliver a smooth and immersive viewing experience. - Engineered the transport layer of network communication, concentrating on TCP and IP protocols. Conducted packet tracking and analysis between various network modules on mobile devices utilizing Wireshark. Additionally, authored and contributed to an IEEE research paper focusing on power-saving techniques in multi-hop Device-to-Device (D2D) communication.
- Developed incentive simulation and gamification tools for over 100 Relationship Managers (RMs) and Business Heads, significantly enhancing motivation and performance tracking. These tools empowered RMs to better understand their performance metrics and achieve their targets. - Created comprehensive dashboards and simulation interfaces using Tableau and Excel, which resulted in a 25% improvement in the accuracy of RM earnings estimates. This facilitated informed decision-making and strategic planning within the organization. - Analyzed RM operations and incentive calculations, identifying key areas for improvement that led to a 15% increase in overall business efficiency. This analysis provided actionable insights that streamlined processes and optimized performance across teams. - Engaged with over 15+ Relationship Managers to identify and analyze sales percentage issues, facilitating discussions on strategies to enhance quarterly earnings. Collaborated on the development of interactive simulations that allowed for comparative analysis with past performance, leading to actionable insights for improvement.