Puvvada Vamsidhar

Computer Science undergraduate with strong expertise in Machine Learning, Deep Learning, and Explainable AI, demonstrated through IEEE and international conference publications and research internship at University of Bonn. Experienced in predictive modeling, computer vision, and interpretable AI. Seeking opportunities to contribute to AI research and real-world intelligent systems.

Research Project Intern - University of Bonn, Germany - Germany

(2025-05 - 2026-02)

Institute of Cognitive Neuroscience

• Investigated speech/noise classification in complex real-world audio with overlapping frequency characteristics.
• Experimented with ZCR, BER, MFCCs, spectrograms, CNNs, deep learning frameworks, and transfer learning for audio classification.
• Proposed Hard-Soft Augmentation, achieving 94% accuracy with improved performance across evaluation metrics.
• Built and refined ML pipelines for feature extraction, model training and evaluation, using iterative experimentation to improve robustness.

MSc - Computer Graphics, Vision and Imaging - University College London (2026-09 - 2027-09)

B.Tech - Computer Science and Engineering - Amrita Vishwa Vidyapeetham (2022 - 2026)

Class 12 - PCM - FIITJEE College (2020 - 2022)