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Dr. Korrapati Sindhu

Assistant Professor, Level 10, School of Computing, Amaravati

Qualification: Ph.D
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Research Interest: Machine Learning, Probabilistic Graphical Models

Bio Publications
Bio

Dr. Korrapati Sindhu holds a Ph.D. in Computer Science and Engineering from the National Institute of Technology, Andhra Pradesh (2025), with research focused on developing models for effective and efficient resource management in virtual data centers. She completed her M.Tech in CSE from RVR & JC College of Engineering with a CGPA of 9.25 and earned her B.Tech from DRK Institute of Science & Technology with 77.2%.

She has qualified UGC NET (2019), APSET (2016), and GATE (2012), and was the branch topper in M.Tech as well as the school topper in S.S.C. During her Ph.D., she worked on a research project sponsored by LinkedIn

Publications

Journal Article

Year : 2025

A dynamic probabilistic graphical model for mapping tasks to virtual machines in data centers

Cite this Research Publication : Korrapati Sindhu, Karthick Seshadri, A dynamic probabilistic graphical model for mapping tasks to virtual machines in data centers, Engineering Applications of Artificial Intelligence, Elsevier BV, 2025, https://doi.org/10.1016/j.engappai.2025.110963

Publisher : Elsevier BV

Year : 2024

Design and Evaluation of a Hierarchical Characterization and Adaptive Prediction Model for Cloud Workloads

Cite this Research Publication : Karthick Seshadri, Korrapati Sindhu, S. Nagesh Bhattu, Chidambaran Kollengode, Design and Evaluation of a Hierarchical Characterization and Adaptive Prediction Model for Cloud Workloads, IEEE Transactions on Cloud Computing, Institute of Electrical and Electronics Engineers (IEEE), 2024, https://doi.org/10.1109/tcc.2024.3393114

Publisher : Institute of Electrical and Electronics Engineers (IEEE)

Year : 2022

Workload characterization and synthesis for cloud using generative stochastic processes

Cite this Research Publication : Korrapati Sindhu, Karthick Seshadri, Chidambaran Kollengode, Workload characterization and synthesis for cloud using generative stochastic processes, The Journal of Supercomputing, Springer Science and Business Media LLC, 2022, https://doi.org/10.1007/s11227-022-04597-y

Publisher : Springer Science and Business Media LLC

Conference Proceedings

Year : 2022

Unsupervised Modeling of Workloads as an Enabler for Supervised Ensemble-based Prediction of Resource Demands on a Cloud

Cite this Research Publication : Karthick Seshadri, C. Pavana, Korrapati Sindhu, Chidambaran Kollengode, Unsupervised Modeling of Workloads as an Enabler for Supervised Ensemble-based Prediction of Resource Demands on a Cloud, Lecture Notes on Data Engineering and Communications Technologies, Springer Nature Singapore, 2022, https://doi.org/10.1007/978-981-16-8403-6_10

Publisher : Springer Nature Singapore

Year : 2021

Dimensionality Prediction for Word Embeddings

Cite this Research Publication : Korrapati Sindhu, Karthick Seshadri, Dimensionality Prediction for Word Embeddings, Algorithms for Intelligent Systems, Springer Singapore, 2021, https://doi.org/10.1007/978-981-33-4604-8_24

Publisher : Springer Singapore

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