Clemens JS Schaefer

I am a Software Engineer on the ML Performance Team at Google. Previously, I obtained a PhD in Computer Science and Engineering at the University of Notre Dame, where I worked on hardware-aware quantization for machine learning. You can find my full CV here.

Publications

GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance
Jinuk Kim, Marwa El Halabi, Wonpyo Park, Clemens JS Schaefer, Deokjae Lee, Yeonhong Park, Jae W Lee, Hyun Oh Song
International Conference on Machine Learning (ICML)
2025
EQuARX: Efficient Quantized AllReduce in XLA for Distributed Machine Learning Acceleration
Ibrahim Ahmed, Clemens JS Schaefer, Gil Tabak, Denis Vnukov, Zenong Zhang, Felix chern, Anatoliy Yevtushenko, Andy Davis
ML for Computer Architecture and Systems (MLArchSys)
2025
Hadamard Domain Training with Integers for Class Incremental Quantized Learning
Martin Schiemer, Clemens JS Schaefer, Jayden Parker Vap, Mark James Horeni, Yu Emma Wang, Juan Ye, Siddharth Joshi
Conference on Lifelong Learning Agents (CoLLAs)
2024
Augmenting Hessians with Inter-Layer Dependencies for Mixed-Precision Post-Training Quantization
Clemens JS Schaefer, Navid Lambert-Shirzad, Xiaofan Zhang, Chiachen Chou, Tom Jablin, Jian Li, Elfie Guo, Caitlin Stanton, Siddharth Joshi, Yu Emma Wang
arXiv:2306.04879
2023
Edge Inference with Fully Differentiable Quantized Mixed Precision Neural Networks
Clemens JS Schaefer, Siddharth Joshi, Shan Li, Raul Blazquez
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision
2024
The Hardware Impact of Quantization and Pruning for Weights in Spiking Neural Networks
Clemens JS Schaefer, Pooria Taheri, Mark Horeni, Siddharth Joshi
IEEE Transactions on Circuits and Systems II: Express Briefs
2023
A compute-in-memory chip based on resistive random-access memory
Weier Wan, Rajkumar Kubendran, Clemens JS Schaefer, S. Burc Eryilmaz, Wenqiang Zhang, Dabin Wu, Stephen Deiss, Priyanka Raina, He Qian, Bin Gao, Siddharth Joshi
Nature
2022
LSTMs for Keyword Spotting with ReRAM-based Compute-In-Memory Architectures
Clemens JS Schaefer, Mark Horeni, Pooria Taheri, Siddharth Joshi
IEEE International Symposium on Circuits and Systems (ISCAS)
2021
Quantizing Spiking Neural Networks with Integers
Clemens JS Schaefer, Siddharth Joshi
International Conference on Neuromorphic Systems (ICONS)
2020
Memory Organization for Energy Efficient Learning and Inference in Digital Neuromorphic Accelerators
Clemens JS Schaefer, Patrick Faley, Emre Neftci, Siddharth Joshi
IEEE International Symposium on Circuits and Systems (ISCAS)
2020
Supervised Learning in All FeFET-Based Spiking Neural Network
Sourav Dutta, Clemens JS Schaefer, Jorge Tomas Gomez, Siddharth Joshi, Suman Datta
Frontiers in Neuroscience
2020