SCHEDULE

**All  talks will be held in the New Mexico Room. Coffee, tea, and water available all day in the Santa Fe Room**

7:00 - 9:00 Breakfast and Badge Pick Up (Santa Fe Room, La Fonda)

8:15 - 8:30 Welcome and Workshop Introduction – Art Edwards, AFRL 

8:30 - 9:00 KEYNOTE: Insights from the Brain’s Co-Design Principles - Suma Cardwell, SNL 

Topic A:  Where is AI today and where do we need to go?

Session Chair: Art Edwards, AFRL

9:05 - 9:25 KEYNOTE: Shared experience/Lifelong Learning Continuous Learning – Ted Senator, Former DARPA Program Manager

9:25 - 9:35 Efficient inference and learning in recurrent neural circuits – Alexander Belsten, UC Berkeley 

9:35 - 9:55 A Theoretical Framework for Time, Space, and Energy Scaling in Neuromorphic Systems – Brad Aimone, SNL

9:55 - 10:05 Understanding and Optimizing Quantization-enabled LLM Serving Systems: A Performance, Energy, and Quality Perspective – Yi Ding, Purdue University 

Topic B: AI at the edge/ training

Session Chair: Art Edwards, AFRL

10:05 - 10:25 KEYNOTE: Neuro-Inspired Continual Learning:  What, How, and Why? – Dhireesha Kudithipudi, UT San Antonio

10:25 - 10:35 Spiking Neural Networks Integration in Heterogeneous Architectures with MoSAIC – Farzad Fatollahi-Fard, LBL 

10:35 - 10:45 Enable Native Full-Integer Spiking Neural Network Training with Algorithm and Hardware Co-Design – Xiaoxuan Yang, University of Virginia

10:45 - 10:55 Neuromorphic Signal Processing at the Edge: Energy-Efficient SNNs for Audio Processing – Qiang Guan, Kent State University

10:55 - 11:35 Panel Discussion

11:35 - 12:35 LUNCH KEYNOTE: Another 40 years of Moore's Law - Jim Lyke, Latin American Office for AFOSR

12:35 - 12:50 *Break*

Topic C: Frameworks for fundamental energetic limitations

Session chair: Jeremy Wojcik, Blue Halo (AFRL)

12:50 - 1:10 KEYNOTE:  Energetic Demands of Continual Learning in Biological Brains – Becket Ebitz, University of Montreal 

1:10 - 1:20 Reliable AI in Unreliable Energy-Constrained Distributed Environments – George Michelogiannakis, LBL

1:20 - 1:30 From IMT Device Measurements to Network-Level Consequences: When Learning Suppresses Beyond-LIF Neuron Dynamics – Kevin Griffin, NLR

1:30 - 1:40 Energy-Efficient Solar Forecasting with a Neuromorphic-Bayesian State Estimation Approach –  Kumar Anurag, University of New Mexico

1:40 - 1:50 Non-volatile Programmable Photonic Devices for Computing Applications – Midya Parto, University of Central Florida 

1:50 - 2:10 Panel Discussion

Topic D:  Next-Generation Technologies

Session chair: Derrek Landauer, Blue Halo (AFRL)

2:10 - 2:30 KEYNOTE: Quantum Computing Data Centers: Current Trends and Future Outlook – Carleton Coffrin, LANL

2:30 - 2:40 Naïve resource estimation in quantum and brain-inspired computing – Shashank Misra, SNL

2:40 - 2:50 Emergent Spatiotemporal Neuromorphic Computing in Protonic Nickelate Network – Duygu Kuzum, UC San Diego

2:50 - 3:00 THOR : The Neuromorphic Commons  – Tej Pandit, UT San Antonio

3:00 - 3:10 Neuro-Symbolic Architectures for Scalable and Energy-Efficient Computation: Opportunities and Open Challenges – Shay Snyder, George Manson University

3:10 - 3:30 Panel Discussion

Topic E: Next-Generation Technologies - Session 2

Session chair: Evan Kain, AFRL 

3:30 - 3:50 KEYNOTE: Edge of Chaos and Entropy Production Minimization as Keys to Neuromorphic Computing – Stan Williams, Texas A&M University

3:50 - 4:00 Energy and Information in Open Thermodynamic Systems – Narayan Srinivasa,  Arch Systems, LLC 

4:00 - 4:10 Advanced packaging for low power, weight and form factor bio-inspired sensing platform – Anastasiia Butko, LBL

4:10 - 4:20 Reshaping LLM Edge Architecture by Emerging Memory Technologies – Ramtin Zand, University of South Carolina

4:20 - 4:30 Neuromorphic Energy-Efficient Multi-Layer Learning with Compartmental Spiking Neurons – Ashish Gautam, ORNL

4:30 - 4:50 Panel Discussion

4:50 - 5:00 Day 1 closeout (Observations and Day 2 Outlook) – Art Edwards, AFRL 

5:00 - 5:30 Poster Summary Blitz (New Mexico Room, La Fonda) 

5:30 - 7:30 Poster Session with refreshments  (Mezzanine, La Fonda) and RUMP Session with informal technical discussions (Santa Fe Room, La Fonda)

A-Graph: A Unified System Representation for Automated Cross-Stack Optimization - Di Wu, University of Central Florida

Beyond Success Rate: Evaluating and Understanding Non-Functional Metrics in Embodied Vision-Language-Action Agents - Yang (Katie) Zhao, University of Minnesota 

Catwalk Neuron for Efficient Temporal Neural Networks - Di Wu, University of Central Florida      

Control of analog brain dynamics & learning as a computational principle for neuromorphic computing derived from the brains SWaP optimized multi-scale co-design principles - Kris Bouchard, LBNL/UC Berkeley    

Creating a path for accelerated quantum computing deployment through energy-aware co-design - Michael Martin, NLR

Denoising with Equilibrium Propagation - Siddharth Mansingh, LANL

DISTIL: A Distributed Spiking Neural Network Accelerator on 2.5D Chiplet Systems - Abhishek Moitra, Washington State University 

Efficient prediction in cultured neurons and humans - Sarah Marzen, Department of Natural Sciences, Scripps and Pitzer College  

Energy-Efficient Acceleration of Transformers with Stochastic Photonic Computing - Ishan Thakkar, University of Kentucky  

Energy-Efficient Hyperdimensional Computing via PATH-Based Digital In-Memory Crossbar Architectures - Sunny Raj, Oakland University 

Federated neuromorphic computing in distributed edge environments - Seung-Hwan Lim, ORNL

GPU Support and Other Improvements for SuperNeuroMAT - Prasanna Date, ORNL        

Hybrid Splat-and-Mesh Simulation for Rapid Humanoid Training in Isaac Sim - Wei Xu, BNL          

In-DRAM Stochastic Computing for Energy-Efficient Acceleration of Transformer Neural Networks - Ishan Thakkar, University of Kentucky     

Inverse-Designed Photonic Dot-Product Primitives for Energy-Efficient Neuromorphic Computing – Raktim Sarma, SNL   

Nanoscale Tracking of the LaCoO3 Spin-State Transition for Application in Neuromorphic Devices - Michelle Smeaton, NLR

Performance Analysis and Optimization of Fructose Memristor-Based Neuromorphic Systems - Aiping Chen on behalf of Jinhui Wang, The University of Alabama

Reliable Cryogenic Circuits in Unreliable Environments - George Michelogiannakis, LBNL

Sample- and Modality‐Efficient Spatiotemporal Learning for Neuroscience and Robotics - David Park on behalf of Xihaier Luo,  BNL

Sense-as-You-Go: A Neuromorphic Framework for Efficient Edge Sensing and Processing - Di Wu & Mohsen Rakhshan, University of Central Florida           

Signal propagation dynamics across the Drosophila hemi-brain connectome modeled as a multiplex networks reveal a parallel-hierarchical (‘U-Net’) sensory-cogntive-motor architecture - Kris Bouchard, LBNL/UC Berkeley

Spatial Mental Modeling from Limited Views -  Manling Li, Northwestern University    

Towards Optimal Readout Partitioning for Qubit and Quantum Sensor Readout and Control - Carl Grace, LBL

UQ-VarQA: Benchmarking and Characterizing NISQ Computers Through Uncertainty Quantification of Variational Quantum Algorithms - Qiang Guan, Kent University 

**All  talks will be held in the New Mexico Room. Coffee, tea, and water available all day in the Santa Fe Room**

7:00 - 9:00 Breakfast and Badge Pick Up (Santa Fe Room, La Fonda)

8:30 - 8:45 Day 2 Welcome - Suma Cardwell, SNL

Topic F:  Neuromorphic Primitives and Circuit Design

Session chair: Suma Cardwell, SNL

8:45 - 9:05 KEYNOTE:  Advancing Neuromorphic Hardware using Recent Advancements in Analog Computing & Tools - Jennifer Hasler, Georgia Institute of Technology 

9:05 - 9:15 Time-Domain Neuromorphic Computing Circuits – Cory Merkel, Rochester Institute of Technology

9:15 - 9:25 Biological Plausibility and Energy Efficiency in Artificially Intelligent Learning Hardware – Joseph Friedman, UT Dallas 

9:25 - 9:35 Efficient Log-Domain Circuit Realization of Biologically-Plausible Neurons – Tomohisa Kawakami, Duke University

9:35 - 9:45 Biologically-Inspired Multiscale Neuromorphic Architecture – Christian O’Reilly, University of South Carolina 

9:45 - 10:05 Panel Discussion

Topic G: Novel Use-Cases for Emerging Devices

Session chair: Cory Merkel, Rochester Institute of Technology 

10:05 - 10:25 KEYNOTE: Integration of Efficient Sensing, Encoding, and Learning via Memristive Dynamics – Joshua Yang, University of Southern California

10:25 - 10:35 Memristor-Based Spiking Neural Network Accelerator for Neuromorphic Computing – Chenyun Pan, UT Arlington

10:35 - 10:45 Energy-efficient and Scalable Inferencing with Hardware Innovation – Beyond-CMOS Technologies – Guojing Cong, ORNL

10:45 - 10:55 Energy-Efficient Temporal Processing with Artificial Spin Ice Based Neuromorphic Nonlinear Vector Autoregression Machine – Ishan Thakkar, University of Kentucky

10:55 - 11:05 Hybrid Opto-electronic Integrated Encoders for Ultralow Power Data Compression – Nicholas Nobile, SNL

11:05 - 11:25 Panel Discussion

11:25 - 11:35 *Break before Working Lunch Keynote*

11:35 - 12:35 LUNCH KEYNOTE: Spiking Manifesto – Eugene Izhikevich, CEO of SpikeCore, Chairman of Brain Corp

12:35 - 12:50 *Break*

Topic H: Beyond CMOS/ Emerging Devices and Technologies

Session chair: Jim Lyke, Latin American Office for AFOSR

12:50 - 1:10 KEYNOTE: Emerging devices for Neuromorphic Computing – Yuping Zeng, University of Delaware 

1:10 - 1:20 Modeling Ferroelectric and Antiferroelectric Capacitors with Physics-Informed LSTMs – Nicholas Ramos, Duke University

1:20 - 1:30 Van der Waals ferroelectric tunnel junctions for next-generation logic-in-memory hardware – Cheng Gong, University of Maryland

1:30 - 1:40 First-Principles Investigation of the Resistive Switching Energetics in Monolayer MoS2: Insights into Metal Diffusion and Adsorption – Jameela Fatheema, UT Austin

1:40 - 1:50 SuperNeuroABM: Scalable, Biologically Realistic, and Hardware-Aware Neuromorphic Simulator – Xi Zhang, ORNL 

1:50 - 2:10 Panel Discussion 

Topic I: Energy Consequences of Biological Systems

Session chair: Hal Greenwald, AFOSR 

2:10 - 2:15 Introduction - Hal Greenwald, AFOSR

2:15 - 2:35 KEYNOTE: From Dendrites to Waves: Multiplexed Codes for Energy-Efficient Cortical Information Processing – Krishna Jayant, Purdue University 

2:35 - 2:45 Principles for energy efficient, brain-like computing – Corinne Teeter, SNL

2:45 - 2:55 Large Multimodal Brain Models for Neuroscience and Computing – David Park, BNL

2:55 - 3:05 Energy-Efficient Intracellular Processing in Neuronal Networks –  William Chapman, SNL

Topic J: Advances in Neuroscience relevant to Emerging Computing

Session chair: Hal Greenwald, AFOSR 

3:05 - 3:25 KEYNOTE: Overview DOE Neuromorphic Workshop – Garrett Kenyon, LANL

3:25 - 3:35 Neural Primitives for Energy-Efficient Neuromorphic Architectures – Frances Chance,  SNL

3:35 - 3:45 Autonomous Learning of Attractors for Neuromorphic Computing – Riley Acker, LANL 

3:45 - 3:55 Compositional associative memories support efficient, robust, and flexible computations – Christopher Kymn, UC Berkeley 

3:55 - 4:05 Mapping Challenges of Connectomes for Performant Neuromorphic Simulation – Felix Wang, SNL

4:05 - 4:50 Panel Discussion

4:50 - 5:00 Day 2 closeout  - Suma Cardwell, SNL

6:30 - Social Hour begins (La Terraza, La Fonda)

7:00 - 9:00 ECI Workshop Dinner (La Terraza, La Fonda)

**All  talks will be held in the New Mexico Room. Coffee, tea, and water available all day in the Santa Fe Room**

7:00 - 9:00 Breakfast and Badge Pick Up (Santa Fe Room, La Fonda)

8:30 - 8:45 Day 3 Welcome – Chiping Li, AFOSR

Topic K: Thermodynamics of Computing

Session Chair: Chiping Li, AFOSR

8:45 - 8:50 Introduction to Thermodynamic Computing - Chiping Li, AFOSR

8:50 - 9:10 KEYNOTE: From Turbulence-in-a-Box to an Exploding Star: Energy Cost of Modern Computational Fluid Dynamics – Alexei Poludnenko, University of Connecticut

9:10 - 9:20 Scalable Ising Solvers for Combinatorial Optimization – Shimeng Yu, Georgia Institute of Technology

9:20 - 9:30 A Digital Twin of Future Quantum HPC Systems – Qiang Guan, Kent State University 

9:30 - 9:40 Kinetic Inductors Enable Reversible Logic – Erik DeBenedictis, Zettaflops LLC

Topic L:  Energy Aspects of Quantum Computing

Session Chair: Erik DeBenedictis, Zettaflops, LLC

9:40 - 10:00 KEYNOTE: Quantum Benchmarking Initiative+ – Mike Descour, SNL 

10:00 - 10:10 The footprint of Quantum Computing: Technologies and Trade-offs – Kasia Kryzyzanowska, LANL

10:10 - 10:20 EnerQy: Energy Estimation for Quantum Computing – Di Wu, University of Central Florida

10:20 - 10:30 Energy-Aware Orchestration for Hybrid Quantum-Classical Computing: Towards Unified Telemetry and Cost Models – Ozgur Ozan Kilic, BNL

10:30 - 10:40 Quantum Enhanced Josephson Junction Field-Effect Transistors for Low-Energy Power-Efficient Microelectronics Applications  – Wei Pan, SNL

10:40 - 11:20 Panel Discussion

11:20 - 11:45 *Break before Working Lunch*

11:45 - 12:35 FUNDING AGENCIES PANEL,  LUNCH 

• Hal Greenwald (AFOSR)

• Chiping Li (AFOSR)

• Art Edwards (AFRL)

• Jim Lyke (Latin American Office for AFOSR)

12:35 - 12:50 *Break*

Topic M:  Macro- and micro solutions to HPC Energy budgets

Session chair: Chiping Li, AFOSR 

12:50 - 1:10 KEYNOTE:  Mapping neuro-inspired principles and motifs to on-chip AI in sensor networks and signal processing applications – Angel Yanguas-Gil, ANL 

1:10 - 1:20 Chiplets already fuel the Exascale. Chiplet modularity is key for the next 100-1000x energy savings –  Patricia Gonzalez-Guerrero/George Michelogiannakis, LBL

1:20 - 1:30 Thermal Management Opportunities from Exploding Energy Demands in Datacenters  – Foluso Ladeinde, Stony Brook University

1:30 - 1:40 Energy Consequences of Machine Learning Inference on HPCs – Mohammed Atif, BNL

1:40 - 1:50 Mozart-RL: A Disaggregating-then-Packing Wafer-Scale Chiplet Framework for Efficient RL-based LLM Post-Training – Yang (Katie) Zhao, University of Minnesota 

1:50 - 2:10 Panel Discussion 

Topic N:  Co-Design

Session Chair: Felix Wang, SNL 

2:10 - 2:30 KEYNOTE: A Full-Stack Neuromorphic System Implementation for Development and Benchmarking –  Rajit Manohar, Yale University

2:30 - 2:40 A principled procedure for designing brain-derived SWaP optimized neuronal units for low-power neuromorphic analog computation and digital communication – Kris Bouchard, LBL

2:40 - 2:50 Fault-Tolerance as a Basis for Energy-Efficient Co-Design – Hemanth Kolla, SNL

2:50 - 3:00 Towards Efficient and Scalable Graph Solutions with Neuromorphic Learning –  Seung-Hwan Lim, ORNL

3:00 - 3:10 Predictive Quantum Simulations for State-of-the-Art and Beyond CMOS Device Technologies: Enabling the Full Stack Co-design of Novel Computing Systems – Juan Mendez, SNL

3:10 - 3:30 Panel Discussion

Topic O: AI-guided Co-Design/ Digital Twins

Session Chair: William Chapman, SNL 

3:30 - 3:50 KEYNOTE: AI for Quantum Computing Co-Design – Shinjae Yoo, BNL

3:50 - 4:00 Agentic AI for Accelerating Automated Co-design of Neuromorphic Systems – Yihui Ren, BNL 

4:00 - 4:10 Neuromorphic Co-Discovery: Beyond Co-Design – Cale Crowder, SNL

4:10 - 4:20 Spike-based Agentic AI and Knowledge Graphs for Electronic Design Automation – Prasanna Date, ORNL

4:20 - 4:50 Panel Discussion 

4:50 - 5:30 Day 3 closeout - Chiping Li, AFOSR

5:30 - 7:30 Follow On Discussions with light refreshments (Hospitality Suite, Room 500, 5th Floor, La Fonda)