Work-in-Progress: Design-Space Exploration of Multi-Core Processors for Safety-Critical Real-Time Systems. - Dolly Sapra; Sebastian Altmeyer (RTSS, 2017)

ALOHA: an architectural-aware framework for deep learning at the edge. - Paolo Meloni; Daniela Loi; Gianfranco Deriu; Andy D. Pimentel; Dolly Sapra; Bernhard Moser 001; Natalia Shepeleva; Francesco Conti 001; Luca Benini; Oscar Ripolles; David Solans; Maura Pintor; et al. (INTESA@ESWEEK, 2018)

Architecture-aware design and implementation of CNN algorithms for embedded inference: the ALOHA project. - Paolo Meloni; Daniela Loi; Gianfranco Deriu; Andy D. Pimentel; Dolly Sapra; Maura Pintor; Battista Biggio; Oscar Ripolles; David Solans; Francesco Conti 001; Luca Benini; Todor P. Stefanov; et al. (ICM, 2018)

Optimization and deployment of CNNs at the edge: the ALOHA experience. - Paolo Meloni; Daniela Loi; Paola Busia; Gianfranco Deriu; Andy D. Pimentel; Dolly Sapra; Todor P. Stefanov; Svetlana Minakova; Francesco Conti 001; Luca Benini; Maura Pintor; Battista Biggio; et al. (CF, 2019)

An evolutionary optimization algorithm for gradually saturating objective functions. - Dolly Sapra; Andy D. Pimentel (GECCO, 2020)

Deep Learning Model Reuse and Composition in Knowledge Centric Networking. - Dolly Sapra; Andy D. Pimentel (ICCCN, 2020)

Constrained Evolutionary Piecemeal Training to Design Convolutional Neural Networks. - Dolly Sapra; Andy D. Pimentel (IEA/AIE, 2020)

The Choice of AI Matters: Alternative Machine Learning Approaches for CPS Anomalies. - Uraz Odyurt; Dolly Sapra; Andy D. Pimentel (IEA/AIE (2), 2021)

Exploring Cell-Based Neural Architectures for Embedded Systems. - Ilja van Ipenburg; Dolly Sapra; Andy D. Pimentel (PKDD/ECML Workshops (1), 2021)

CPU-GPU Layer-Switched Low Latency CNN Inference. - Ehsan Aghapour; Dolly Sapra; Andy D. Pimentel; Anuj Pathania (DSD, 2022)

Designing convolutional neural networks with constrained evolutionary piecemeal training. - Dolly Sapra; Andy D. Pimentel (Appl. Intell., 2022)

Scenario Based Run-Time Switching for Adaptive CNN-Based Applications at the Edge. - Svetlana Minakova; Dolly Sapra; Todor P. Stefanov; Andy D. Pimentel (ACM Trans. Embed. Comput. Syst., 2022)

PELSI: Power-Efficient Layer-Switched Inference. - Ehsan Aghapour; Dolly Sapra; Andy D. Pimentel; Anuj Pathania (RTCSA, 2023)

Exploring Multi-core Systems with Lifetime Reliability and Power Consumption Trade-offs. - Dolly Sapra; Andy D. Pimentel (SAMOS, 2023)

On Achieving Privacy-Preserving State-of-the-Art Edge Intelligence. - Daphnee Chabal; Dolly Sapra; Zoltán Ádám Mann (CoRR, 2023)

PiQi: Partially Quantized DNN Inference on HMPSoCs. - Ehsan Aghapour; Yixian Shen; Dolly Sapra; Andy D. Pimentel; Anuj Pathania (ISLPED, 2024)

FAA+RTS: Designing Fault-Aware Adaptive Real-Time Systems - From Specification to Execution -. - Lukas Miedema; Dolly Sapra; Petr Novobilsky; Sebastian Altmeyer; Clemens Grelck; Andy D. Pimentel (SAMOS, 2024)

ARM-CO-UP: ARM COoperative Utilization of Processors. - Ehsan Aghapour; Dolly Sapra; Andy D. Pimentel; Anuj Pathania (ACM Trans. Design Autom. Electr. Syst., 2024)

COLIBRI: Optimizing Multi-party Secure Neural Network Inference Time for Transformers. - Daphnee Chabal; Tim Müller; Eloise Zhang; Dolly Sapra; Cees de Laat; Zoltán Ádám Mann (SEC (1), 2025)

Rethinking Computing Systems in the Era of Climate Crisis: A Call for a Sustainable Computing Continuum. - Ella Peltonen; Suzan Bayhan; David Bermbach; Sebastian Buschjäger; Victoria Degeler; Aaron Yi Ding; Özlem Durmaz Incel; Dewant Katare; Mikkel Baun Kjærgaard; Sam Leroux; Toktam Mahmoodi; Zoltán Ádám Mann; et al. (IEEE Internet Comput., 2025)

Towards Adaptive Deep Learning: Model Elasticity via Prune-and-Grow CNN Architectures. - Pooja Mangal; Sudaksh Kalra; Dolly Sapra (CoRR, 2025)