Scalable IP Core for Feed Forward Random Networks. - Anurag Reddy Daram; Karan Paluru; Vedant Karia; Dhireesha Kudithipudi (ELM, 2018)

Task-Based Neuromodulation Architecture for Lifelong Learning. - Anurag Reddy Daram; Dhireesha Kudithipudi; Angel Yanguas-Gil (ISQED, 2019)

MetaplasticNet: Architecture with Probabilistic Metaplastic Synapses for Continual Learning. - Fatima Tuz Zohora; Vedant Karia; Anurag Reddy Daram; Abdullah M. Zyarah; Dhireesha Kudithipudi (ISCAS, 2021)

Biological underpinnings for lifelong learning machines. - Dhireesha Kudithipudi; Mario Aguilar-Simon; Jonathan Babb; Maxim Bazhenov; Douglas Blackiston; Josh C. Bongard; Andrew P. Brna; Suraj Chakravarthi Raja; Nick Cheney; Jeff Clune; Anurag Reddy Daram; Stefano Fusi; et al. (Nat. Mach. Intell., 2022)

NEO: Neuron State Dependent Mechanisms for Efficient Continual Learning. - Anurag Reddy Daram; Dhireesha Kudithipudi (NICE, 2023)

NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. - Jason Yik; Soikat Hasan Ahmed; Zergham Ahmed; Brian Anderson; Andreas G. Andreou; Chiara Bartolozzi; Arindam Basu; Douwe den Blanken; Petrut Bogdan; Sander M. Bohté; Younes Bouhadjar; Sonia M. Buckley; et al. (CoRR, 2023)

Design Principles for Lifelong Learning AI Accelerators. - Dhireesha Kudithipudi; Anurag Reddy Daram; Abdullah M. Zyarah; Fatima Tuz Zohora; James B. Aimone; Angel Yanguas-Gil; Nicholas Soures; Emre Neftci; Matthew Mattina; Vincenzo Lomonaco; Clare D. Thiem; Benjamin R. Epstein (CoRR, 2023)

Towards Continually Learning Application Performance Models. - Ray A. O. Sinurat; Anurag Reddy Daram; Haryadi S. Gunawi; Robert B. Ross; Sandeep Madireddy (CoRR, 2023)

A domain-agnostic approach for characterization of lifelong learning systems. - Megan M. Baker; Alexander New; Mario Aguilar-Simon; Ziad Al-Halah; Sébastien M. R. Arnold; Eseoghene Ben-Iwhiwhu; Andrew P. Brna; Ethan Brooks; Ryan C. Brown; Zachary Daniels; Anurag Reddy Daram; Fabien Delattre; et al. (Neural Networks, 2023)

TACOS: Task Agnostic Continual Learning in Spiking Neural Networks. - Nicholas Soures; Peter Helfer; Anurag Reddy Daram; Tej Pandit; Dhireesha Kudithipudi (CoRR, 2024)

Does Alignment help continual learning? - Anurag Reddy Daram; Dhireesha Kudithipudi (CLD2, 2025)

Benchmarking Spiking Network Partitioning Methods on Loihi 2. - William Severa; Felix Wang; Yang Ho; Fred Rothganger; Anurag Reddy Daram; Efrain Gonzalez (ACM Great Lakes Symposium on VLSI, 2025)