Anirudh Varanasi

According to our database, Anirudh Varanasi authored at least 6 papers between 2024 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

RTNinja: a generalized machine learning framework for analyzing random telegraph noise signals in nanoelectronic devices.

Anirudh Varanasi, Robin Degraeve, Philippe Roussel, Clement Merckling

CoRR, July, 2025

Algorithm for Robust Correction of Long-Term Drift Components in Gate Leakage Current RTN Data.

Anirudh Varanasi, Robin Degraeve, Philippe J. Roussel, Clement Merckling

Proceedings of the IEEE International Reliability Physics Symposium, 2025

Advanced RTN Analysis on 3D NAND Trench Devices Using Physics-Informed Machine Learning Framework.

Yusuke Higashi, Anirudh Varanasi, Philippe J. Roussel, Pablo Saraza-Canflanca, J. P. Bastos, Alexander Grill, E. Catapano, R. Asanovski, Jacopo Franco, Ben Kaczer, Adrian Chasin, Devin Verreck, S. Ramesh, Laurent Breuil, Antonio Arreghini, S. Rachidi, Y. Jeong, Geert Van den Bosch, Maarten Rosmeulen, Robin Degraeve

Proceedings of the IEEE International Reliability Physics Symposium, 2025

2024

Alistair: Efficient On-device Budgeting for Differentially-Private Ad-Measurement Systems.

Pierre Tholoniat, Kelly Kostopoulou, Peter McNeely, Prabhpreet Singh Sodhi, Anirudh Varanasi, Benjamin Case, Asaf Cidon, Roxana Geambasu, Mathias Lécuyer

CoRR, 2024

Cookie Monster: Efficient On-Device Budgeting for Differentially-Private Ad-Measurement Systems.

Pierre Tholoniat, Kelly Kostopoulou, Peter McNeely, Prabhpreet Singh Sodhi, Anirudh Varanasi, Benjamin Case, Asaf Cidon, Roxana Geambasu, Mathias Lécuyer

Proceedings of the ACM SIGOPS 30th Symposium on Operating Systems Principles, 2024

Physics-informed machine learning to analyze oxide defect-induced RTN in gate leakage current.

Anirudh Varanasi, Robin Degraeve, Philippe J. Roussel, Andrea Vici, Clement Merckling

Proceedings of the IEEE International Reliability Physics Symposium, 2024