Santonu Sarkar

Employment

• ABB Senior Principal Scientist
  2019 - Present
• Birla Institute of Technology and Science Pilani Professor
  2014 - 2019
• Infosys Technologies Ltd Principal Research Scientist
  2010 - 2014
• Accenture Head, Software Engineering Research
  2007 - 2010
• Infosys Ltd Principal Architect
  2002 - 2007

Education

• Indian Institute of Technology Kharagpur PhD
  1992 - 1997
• Indian Institute of Technology Kharagpur Masters
  1990 - 1992
• Indian Institute of Engineering Science and Technology BTech
  1984 - 1988

Projects & Funding

Projects & funding information is unavailable.

Publications (62)

• PowerQuant: Architecture-Agnostic GPU Power Estimation via Quantile Regression
  2026 DOI: 10.1145/3806645.3807591
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• Adaptive GPU Power Capping: Balancing Energy Efficiency,Thermal Control and Performance
  2025 DOI: 10.1145/3731545.3735119
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• quantile-Long Short Term Memory: A Robust, Time Series Anomaly Detection Method
  IEEE Transactions on Artificial Intelligence 2024 DOI: 10.1109/TAI.2024.3353163
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• Program Analysis and Machine Learning–based Approach to Predict Power Consumption of CUDA Kernel
  ACM Transactions on Modeling and Performance Evaluation of Computing Systems 2023 DOI: 10.1145/3603533
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• Performance modeling of graphics processing unit application using static and dynamic analysis
  Concurrency and Computation: Practice and Experience 2022 DOI: 10.1002/cpe.6602
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• Fitness-Aware Containerization Service Leveraging Machine Learning
  IEEE Transactions on Services Computing 2021 DOI: 10.1109/TSC.2019.2898666
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• Clustering, Separation, and Connection: A Tale of Three Characteristics
  2021 DOI: 10.1109/ICSME52107.2021.00078
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• Understanding the Inter-Domain Presence of Research Topics in the Computing Discipline
  IEEE Transactions on Emerging Topics in Computing 2021 DOI: 10.1109/TETC.2018.2869556
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• Assessing Invariant Mining Techniques for Cloud-Based Utility Computing Systems
  IEEE Transactions on Services Computing 2020 DOI: 10.1109/TSC.2017.2679715
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• Architectural partitioning and deployment modeling on hybrid clouds
  Software: Practice and Experience 2018 DOI: 10.1002/spe.2496
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