Research

1. July 2025 — Present

   Gemini + Cloud, Advanced Development Team

   Agent Architect

2. June 2024 — June 2025

   Google, TPU Performance Team

   Student Researcher

3. June 2022 — May 2024

   Google, Platforms-Aware AutoML

   Student Researcher

4. August 2019 — June 2025

   Computer Systems Laboratory, Cornell

   PhD Candidate

5. June 2017 — June 2018

   Datto

   Software Engineer

1. 01 FLIQS: One-Shot Mixed-Precision Floating-Point and Integer Quantization Search Jordan Dotzel, Gang Wu, Andrew Li, Muhammad Umar, Yun Ni, Mohamed S. Abdelfattah, Zhiru Zhang, Liqun Cheng, Martin G. Dixon, Norman P. Jouppi, Quoc V. Le, Sheng Li AutoML 2024 · Best Paper ↗
2. 02 Learning from Students: Applying T-Distributions to Explore Accurate and Efficient Formats for LLMs Jordan Dotzel, Yuzong Chen, Bahaa Kotb, Sushma Prasad, Gang Wu, Sheng Li, Mohamed S. Abdelfattah, Zhiru Zhang ICML 2024 ↗
3. 03 Exploring the Limits of Semantic Image Compression at Micro-Bits per Pixel Jordan Dotzel*, Bahaa Kotb*, James Dotzel, Mohamed S. Abdelfattah, Zhiru Zhang ICLR Tiny Papers 2024 ↗
4. 04 Opportunities for Post-Training Dynamic Layer Sparsity in Large Vision and Language Models Jordan Dotzel, Carly Jiang, Mohamed S. Abdelfattah, Zhiru Zhang CVPR Workshop 2024 ↗
5. 05 Semantic Compression of 3D Objects for Open and Collaborative Virtual Worlds Jordan Dotzel*, Tony Montes*, Mohamed S. Abdelfattah, Zhiru Zhang arXiv 2025 ↗
6. 06 Radial Networks: Dynamic Layer Routing for High-Performance Large Language Models Jordan Dotzel*, Yash Akhauri*, Ahmed S. AbouElhamayed, Carly Jiang, Mohamed S. Abdelfattah, Zhiru Zhang arXiv 2024 ↗
7. 07 OverQ: Opportunistic Outlier Quantization for Neural Network Accelerators Jordan Dotzel*, Ritchie Zhao*, Zhanqiu Hu, Preslav Ivanov, Christopher De Sa, Zhiru Zhang arXiv 2019 ↗
8. 08 Improving Neural Network Quantization Without Retraining Using Outlier Channel Splitting Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang ICML 2019 ↗
9. 09 Building Efficient Deep Neural Networks With Unitary Group Convolutions Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang CVPR 2019 ↗
10. 10 ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models Yash Akhauri, Ahmed F. AbouElhamayed, Jordan Dotzel, Zhiru Zhang, Alexander M. Rush, Safeen Huda, Mohamed S. Abdelfattah EMNLP 2024 ↗
11. 11 SparAMX: Accelerating Compressed LLMs Token Generation on AMX-powered CPUs Ahmed F. AbouElhamayed, Jordan Dotzel, Yash Akhauri, Chi-Chih Chang, Sameh Gobriel, J. Pablo Muñoz, Vui Seng Chua, Nilesh Jain, Mohamed S. Abdelfattah arXiv 2025 ↗
12. 12 M4BRAM: Mixed-Precision Matrix-Matrix Multiplication in FPGA Block RAMs Yuzong Chen, Jordan Dotzel, Mohamed S. Abdelfattah FPT 2023 ↗
13. 13 Logic Synthesis Meets Machine Learning: Trading Exactness for Generalization S. Rai, W. L. Neto, …, Y. Zhou, Y. Zhang, J. Dotzel, Z. Zhang, … DATE 2021 ↗
14. 14 Enabling Design Methodologies and Future Trends for Edge AI: Specialization and Co-Design Cong Hao, Jordan Dotzel, Jinjun Xiong, Luca Benini, Zhiru Zhang, Deming Chen IEEE Design & Test 2021 ↗

* Equal contribution