Krishnateja Killamsetty is a Research Staff Member at IBM, specializing in innovative research initiatives focused on language models. With a PhD in Computer Science from The University of Texas at Dallas, Krishnateja pioneered novel subset selection approaches for training deep models, achieving efficiency improvements of 5-80x. Their expertise encompasses fine-tuning of instruction-tuned models, continual learning, and optimized inference, with contributions recognized through multiple publications in prestigious AI conferences. Previously, Krishnateja held positions at Microsoft, Mercedes-Benz, and Amazon, and developed algorithms for advanced driver assistance systems as a Senior Software Engineer at Bosch.
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