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 (IRPS, 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 (SOSP, 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)

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; et al. (IRPS, 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 (IRPS, 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, 2025)