Ziqing Wang

About Me

Hello! I am a Ph.D. student in the Reliable, Efficient, and Autonomous Learning (REAL) Lab, Department of Statistic and Data Science at Northwestern University, under the supervision of Prof. Kaize Ding. I completed my Bachelor of Engineering (B.E.) in Microelectronics from Sun Yat-sen University, under the guidance of Prof. Shanlin Xiao. Additionally, I had the opportunity to work as a research assistant at the Hong Kong University of Science and Technology (HKUST), Guangzhou campus, from 2022 to 2023, where I collaborated closely with Prof. Renjing Xu.

Other than my work, I am a big fan of the Golden State Warriors. My favorite basketball player is Steph Curry. Go Warriors!

Research Interests

I am interested in efficient AI. My current research primarily focus on how to achieve Pareto optimality between model performance and energy consumption. I also have a keen interest in generative AI, such as Diffusion Models and LLMs. I am highly intrigued by the potential crossover between efficient AI, generative AI, and the scientific realm like biomedicine.

Efficient AI: Efficient Transformer Training and Inference, Spiking Neural Networks, Quantization, Parameter Efficient Fine-tuning
Generative AI: Diffusion Models, Large Language Models
AI for Science: Molecule Generation, EEG Reconstruction

News

- [01/2025] My AAAI paper is selected as an oral paper. See you in Philadelphia!!
- [12/2024] Glad to receive a AAAI Travel Grant. Thank you AAAI!!
- [12/2024] One paper is accepted to AAAI 2025. See you in Philadelphia!!
- [12/2024] I will serve as a reviewer of ICML 2025.
- [09/2024] Two papers are accepted to NeurIPS 2024. See you in Vancouver!!
- [08/2024] One paper is accepted to IEEE Transactions on Artificial Intelligence.
- [08/2024] I will serve as a reviewer of ICLR 2025.
- [08/2024] I will serve as a reviewer of ICASSP 2025.
- [07/2024] One paper is accepted to ECCV 2024. See you in Milan!!
- [06/2024] I will serve as a reviewer of TNNLS.
- [06/2024] I will serve as an PC member of AAAI 2025.
- [05/2024] I will serve as a reviewer of NeurIPS 2024.
- [03/2024] Gave a talk at the Intel INRC lab.
- [02/2024] My ICASSP paper is selected as an oral paper. See you in Seoul!!
- [02/2024] I will serve as a reviewer of ECCV 2024.
- [01/2024] I will serve as a reviewer of MM 2024.
- [12/2023] One paper is accepted to ICASSP 2024.
- [11/2023] I will serve as a reviewer of CVPR 2024.
- [10/2023] One paper is accepted to WACV 2024.
- [08/2023] I will serve as an PC member of AAAI 2024.
- [07/2023] One paper is accepted to ICCV 2023.
- [06/2022] One paper is accepted to DSAA 2022.

Publications

ICCV

Masked Spiking Transformer

Ziqing Wang*, Yuetong Fang*, Jiahang Cao, Zhongrui Wang, Renjing Xu (*equal contribution)

International Conference on Computer Vision (ICCV), 2023.

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AAAI

Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Networks

Ziqing Wang*, Yuetong Fang*, Jiahang Cao, Renjing Xu (*equal contribution)

[Oral] AAAI Conference on Artificial Intelligence (AAAI), 2025.

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NeurIPS

Autonomous Driving with Spiking Neural Networks

Rui-jie Zhu*, Ziqing Wang*, Leilani Gilpin, Jason K. Eshraghian (*equal contribution)

NeurIPS Conference on Neural Information Processing Systems (NeurIPS), 2024.

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NeurIPS

Spiking Neural Network as Adaptive Event Stream Slicer

Jiahang Cao*, Mingyuan Sun*, Ziqing Wang*, Hao Cheng, Qiang Zhang, Renjing Xu (*equal contribution)

NeurIPS Conference on Neural Information Processing Systems (NeurIPS), 2024.

ECCV

Spiking Wavelet Transformer

Yuetong Fang*, Ziqing Wang*, Jiahang Cao, Renjing Xu (*equal contribution)

European Conference on Computer Vision (ECCV), 2024.

ICASSP

AutoST: Training-free Neural Architecture Search for Spiking Transformers

Ziqing Wang, Qidong Zhao, Jinku Cui, Xu Liu, Dongkuan Xu

[Oral] IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2024.

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WACV

Spiking Denoising Diffusion Probabilistic Models

Jiahang Cao*, Ziqing Wang*, Hanzhong Guo*, Hao Cheng, Qiang Zhang, Renjing Xu (*equal contribution)

IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024.

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DSAA

AMD-DBSCAN: An Adaptive Multi-density DBSCAN for datasets of extremely variable density

Ziqing Wang, Zhirong Ye, Yuyang Du, Yi Mao, Yanying Liu, Ziling Wu, Jun Wang

2022 IEEE 9th International Conference on Data Science and Advanced Analytics, (DSAA), 2022.

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