Sri Teja Valusa

Developed and implemented a web-based Data Asset Management System using React and Vue.js, achieving a 40% reduction in development time and enhancing application performance. Led the development of machine learning models using Generative AI, employing BERT and GPT-based architectures for NLP tasks and integrating a Retrieval-Augmented Generation (RAG) Chatbot to enhance clarity and user experien

Architected and rolled out scalable backend and frontend systems using Qt with C++, reducing system crashes by 60% and improving performance by 20% on ARM437X microprocessors for energy sector applications. Engineered secure APIs with Django REST Framework, incorporating serialization and token-based authentication to ensure data integrity and security.

Worked in Agile environment collaborating with other teams to enhance workflow predictability and cut down the delivery time variability by 25% for machine learning projects. Utilized Python libraries including Pandas, NumPy, Scikit-learn, TensorFlow, Spark, Matplotlib, and SciPy in developing efficient machine learning models that has improved operational efficiency by 20%.

Designed and deployed advanced ML models for image analysis and object detection using U-Net architecture and SMOTE, enhancing data stability and improving baseline accuracy by 50%. Processed and analyzed large-scale satellite imagery datasets from Sentinel and Landsat-8, leveraging TIFF file equalization, principal component analysis (PCA), and K-means clustering algorithms to optimize visualizat

Pursued a Master's degree focusing on Information Systems, gaining advanced knowledge in data management, system analysis, and IT strategy. Developed skills in leveraging technology to solve complex business challenges and improve organizational efficiency.

Completed a Bachelor's degree in Computer Science, building a strong foundation in programming, algorithms, and software development. Engaged in various projects to apply theoretical knowledge to practical computing problems.