Prudvi Kamtam is a graduate research assistant and soon-to-be MS in Computer Science at UCF with eight years of industry and research experience focused on computer vision, machine learning, and deep learning. He has contributed to CVPR‑accepted work by creating the UCF101-DS action recognition dataset and benchmarking SOTA CNNs and Transformers, and has practical expertise training and fine-tuning ResNet and MViT-based architectures on distributed GPU clusters. Prudvi’s industry experience spans health‑tech and mobile computer vision—driving a 30% improvement in rehabilitation outcomes at MirrorAR and optimizing on-device inference via TFLite/ONNX conversions and quantization. He’s fluent in PyTorch, AWS (EC2, SageMaker, Glue, Lambda) and slurm-based HPC workflows, having reduced training times by up to 6x and scaled several datasets by 10x for ReID and gait tasks. Comfortable bridging research and product, he’s delivered end-to-end MLOps pipelines and interactive visualization dashboards while co-authoring academic work. Pragmatic and curious—his Github tagline “Trying to connect the dots” mirrors a pattern of turning datasets and prototypes into deployable ML systems.
8 years of coding experience
2 years of employment as a software developer
Engineer’s Degree, Computer Science, Engineer’s Degree, Computer Science at JNTUH College of Engineering Hyderabad
Master's degree, Computer Science, Master's degree, Computer Science at University of Central Florida
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