Memory-Immersed Collaborative Digitization for Area-Efficient Compute-in-Memory Deep Learning. - Shamma Nasrin; Maeesha Binte Hashem; Nastaran Darabi; Benjamin Parpillon; Farah Fahim; Wilfred Gomes; Amit Ranjan Trivedi (AICAS, 2023)

On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments. - Shruti R. Kulkarni; Aaron R. Young; Prasanna Date; Narasinga Rao Miniskar; Jeffrey S. Vetter; Farah Fahim; Benjamin Parpillon; Jennet Dickinson; Nhan Tran; Jieun Yoo; Corrinne Mills; Morris Swartz; et al. (ICONS, 2023)

Readout IC with 40 MSPS in-pixel ADC for future vertex detector upgrades of Large Hadron Collider. - Benjamin Parpillon; Amit Ranjan Trivedi; Farah Fahim (ISCAS, 2023)

Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning. - Jieun Yoo; Jennet Dickinson; Morris Swartz; Giuseppe Di Guglielmo; Alice Bean; Douglas Berry; Manuel Blanco Valentin; Karri Dipetrillo; Farah Fahim; Lindsey Gray; James Hirschauer; Shruti R. Kulkarni; et al. (Mach. Learn. Sci. Technol., 2024)

TimeFloats: Train-in-Memory with Time-Domain Floating-Point Scalar Products. - Maeesha Binte Hashem; Benjamin Parpillon; Divake Kumar; Dinithi Jayasuriya; Amit Ranjan Trivedi (VLSID, 2025)

From Signals to Features to Insights: Multi-Level Novelty Detection for Fast Scientific Discovery. - Devashri Naik; Nastaran Darabi; Sina Tayebati; Dinithi Jayasuriya; Shamma Nasrin; Danush Shekar; Corrinne Mills; Benjamin Parpillon; Farah Fahim; Mark S. Neubauer; Amit Ranjan Trivedi (VTS, 2025)