亚利桑那州立Jiaqi Gu组招PhD/Intern 26春/秋 (AI system/hardware/algorithm, EDA)
8430
导师简介：
Dr. Jiaqi Gu于2023年加入Arizona State University ECEE担任助理教授。Dr. Gu 2023年Ph.D.毕业于美国德克萨斯大学奥斯汀分校(UT Austin) ECE Prof. David Z. Pan组。研究兴趣包括(但不限于)：
其主要研究成果发表于设计与自动化(CAD/EDA), 机器学习(ML)等顶会顶刊(如DAC, ICCAD, DATE, ASP-DAC, IEEE TCAD, NeurIPS, CVPR, ICCV, ICLR, AAAI)。 曾获得2020 ASP-DAC, 2022 IEEE TCAD最佳论文, 2022 DAC, 2025 DATE最佳论文提名等。科研项目与nvidia, cadence等大公司, foundry, 以及EigenAI等startup有紧密合作，
招生信息：
现计划招收多名全奖博士生(Computer Engineering or Electrical Engineering; 2026 Spring/Fall), 实习生(可远程, 之前组里的intern均获得了strong推荐信 or phd offer, all with one or multiple first-authored paper publications)。
欢迎对emerging AI hardware design, efficient AI algorithm and system (LLM/VLM/Diffusion), hardware/software co-design, EDA, physics-driven AI/ML 感兴趣的同学来信咨询。欢迎填写这个表格(forms.gle), 也可直接将英文简历，成绩单，论文(if applicable)发往 1point3acres.com, 可简要介绍你对我们组里哪些topic有了解且感兴趣，本科或硕士期间相关科研经历。
Dr. Gu希望能与highly self-motivated且踏实务实的学生一起探索科研前沿，解决有挑战性(hardcore and impactful)的实际问题，打造融洽的课题组文化，培养学生research skills/taste, presentation/writing skills, leadership等综合能力, 并且鼓励且推荐学生暑假实习。
Dr. Jiaqi Gu于2023年加入Arizona State University ECEE担任助理教授。Dr. Gu 2023年Ph.D.毕业于美国德克萨斯大学奥斯汀分校(UT Austin) ECE Prof. David Z. Pan组。研究兴趣包括(但不限于)：
- Emerging AI Hardware (optics/photonics, post-CMOS electronics, etc.)
- 光子计算与互联系统(optical computing/interconnect)，光电混合系统设计与仿真(electronic-photonic heterogeneous AI system design/simulation/design space exploration), collaborate with hardware groups with multiple chip tapeout opportunities per year.
- 要求背景: architecture, circuit, optimization background.
- Efficient AI/ML Algorithms and System/Inference (LLM/VLM/Diffusion, etc.)
- 模型加速算法与部署（quantization, sparsity, distillation, kernel optimization, distributed deployment, etc.), collaborate with industry with sufficient computing resources and internship opportunities.
- 要求背景: AI system, AI algorithm, model compression, training/inference, python/CUDA coding
- Hardware/Software Co-Design for Emerging AI Hardware and Applications
- 软硬件协同设计，边缘部署，平衡优化多重目标(robustness, power, speed, scalability, reconfigurability, adaptability, security, etc.)
- 要求背景: strong in math/optimization, basic knowledge in hardware and AI.
- Electronic/Photonic Design Automation (EPDA), ML for EDA
- 光子芯片设计自动化(electronic-photonic design automation): synthesis/placement/routing/co-simulation/post-layout extraction/design-for-manufacturing, etc.
- 要求背景: strong skills in algorithm/data structure, python/c++ coding, basic hardware understanding.
- AI/ML for Physics, Physics-driven AI/ML
- 人工智能加速科学计算与物理系统优化设计(AI for physics, AI-accelerated scientific computing), AI-assisted PDE solving, optical structure inverse design, etc.
- 要求背景: prefer applied physics, strong physics background with AI/ML knowledge and experience.
其主要研究成果发表于设计与自动化(CAD/EDA), 机器学习(ML)等顶会顶刊(如DAC, ICCAD, DATE, ASP-DAC, IEEE TCAD, NeurIPS, CVPR, ICCV, ICLR, AAAI)。 曾获得2020 ASP-DAC, 2022 IEEE TCAD最佳论文, 2022 DAC, 2025 DATE最佳论文提名等。科研项目与nvidia, cadence等大公司, foundry, 以及EigenAI等startup有紧密合作，
- 课题组主页：scopex-asu.github.io
- Google Scholar: scholar.google.com
招生信息：
现计划招收多名全奖博士生(Computer Engineering or Electrical Engineering; 2026 Spring/Fall), 实习生(可远程, 之前组里的intern均获得了strong推荐信 or phd offer, all with one or multiple first-authored paper publications)。
欢迎对emerging AI hardware design, efficient AI algorithm and system (LLM/VLM/Diffusion), hardware/software co-design, EDA, physics-driven AI/ML 感兴趣的同学来信咨询。欢迎填写这个表格(forms.gle), 也可直接将英文简历，成绩单，论文(if applicable)发往 1point3acres.com, 可简要介绍你对我们组里哪些topic有了解且感兴趣，本科或硕士期间相关科研经历。
Dr. Gu希望能与highly self-motivated且踏实务实的学生一起探索科研前沿，解决有挑战性(hardcore and impactful)的实际问题，打造融洽的课题组文化，培养学生research skills/taste, presentation/writing skills, leadership等综合能力, 并且鼓励且推荐学生暑假实习。
