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Sandeep Madireddy is an Assistant Computer Scientist in the Mathematics and Computer Science Division at Argonne National Laboratory. His research interests include machine learning, probabilistic modeling and high performance computing, with applications across science and engineering. His current research aims at developing deep learning algorithms and architectures tailored for scientific machine learning, with a particular focus on improving training efficiency, model robustness, uncertainty quantification and feature representation learning. He has experience applying these approaches to address diverse problems in various domains, ranging from physical sciences (material science, high energy physics, climate science) to computer systems modeling and neuromorphic computing.

He obtained his Ph.D. in mechanical and materials engineering from the University of Cincinnati, as part of the UC Simulation center (a UC Engineering and Procter & Gamble Collaboration). Before that, he obtained his masters from Utah State University and bachelors from Birla Institute of Technology and Science (BITS-Pilani) in India.
System Software and Runtime Systems
Big Data
Data Analytics, Compression, and Management
Data Movement
File Systems and I/O
File Systems and I/O
Machine Learning, Deep Learning and Artificial Intelligence
Performance/Productivity Measurement and Evaluation
Resource Management and Scheduling
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