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Caleb Tung is an AI Research Scientist at Latent AI, Inc. since December 2022, focusing on the technical feasibility of AI optimization and deployment tools. Prior experiences include a Graduate Research Assistant role at Purdue University, where contributions were made to robust, energy-efficient computer vision systems under Prof. Yung-Hsiang Lu, and a Graduate Teaching Assistant position, mentoring undergraduate students. As an intern at Arm, Caleb accelerated object detector inference using residual activation networks, and during a prior internship at Latent AI, neural network runtime throttling was enabled, significantly improving AI model latency. Additional experience includes developing a Deep Neural Network for real-time methane and oil leak detection at Southwest Research Institute and leading undergraduate research efforts at Purdue University. Caleb has also gained software engineering experience through internships at USAA and Software Engineering Professionals. Educational qualifications include a PhD in Computer Engineering and a Bachelor of Science in Honors Computer Engineering, both from Purdue University.