Can Qin 秦灿
Ph.D. Candidate
Electrical and Computer Engineering Department, Northeastern University, Boston, MA, USA.
Office: Richard Hall, 360 Huntington Ave, Boston, MA 02115
Email : qin.ca [at] husky.neu.edu   qin.ca [at] northeastern.edu     Github     LinkedIn     Google Scholar

About Me

I am a fifth-year Ph.D. candidate in the Smile Lab of Department of Electrical and Computer Engineering, Northeastern University (NEU) under the supervision of Prof. Yun Raymond Fu. I received my B.E. degree from the School of Microelectronics, Xidian University (XDU), China, in 2018. My research interests broadly include the theories and applications in machine learning, computer vision and data mining, with the high focus on data efficiency and model efficiency.
I am actively looking for opportunities in industry, and please feel free to contact me (qin.ca@northeastern.edu) if interested.

Research Interests

  • Transfer Learning, Knowledge Distillation and Domain Adaptation.
  • Self-supervised/Semi-supervised/Few-shot/Zero-shot/Incremental Learning.
  • Efficient Deep Learning for Image Classification, Segmentation and 3D Vision.

News

  • 2022.09: One paper is accepted by ICDM 2022 and one paper is accepted by IEEE Transactions on Image Processing (TIP).
  • 2022.08: I have been invited as a PC member for AAAI 2023 and a reviewer for ICLR 2023 .
  • 2022.08: We have two papers accepted by CIKM 2022.
  • 2022.05: We have a paper accepted by KDD 2022. Thanks to all the mentors from Adobe Research.
  • 2022.05: I start my summer internship at Salesforce Research at Palo Alto, CA.
  • 2022.04: We have two papers accepted by IJCAI 2022.
  • 2022.02: The official code of PointMLP is released. I have been invited as the reviewer for TPAMI and TMLR.
  • 2022.01: We have two papers accepted by ICLR 2022. Congrats to Xu and Yulun.
  • 2022.01: I have been invited as a reviewer for ICML 2022 .
  • 2021.12: The manuscript of our new paper - Semi-supervised Domain Adaptive Structure Learning has been uploaded.
  • 2021.11: I have been invited as a reviewer for CVPR 2022 and TNNLS .
  • 2021.11: Our paper about AI + Science (i.e., Topology Optimization) has been accepted by Nature Communications .
  • 2021.10: Our new paper - AdaMomentum for a general-purpose deep learning optimizer has been uploaded.
  • 2021.09: We have two papers accepted by NeurIPS 2021, with one Poster and one Spotlight respectively.
  • 2021.09: We have a paper accepted by IEEE Transactions on Image Processing (TIP) .
  • 2021.08: We have a paper accepted by International Conference on Data Mining (ICDM) 2021 .
  • 2021.07: We have a paper accepted by International Conference on Computer Vision (ICCV) 2021 .
  • 2021.07: I have been invited as a program committee (PC) member for IJCAI 2022 .
  • 2021.07: Our paper is accepted by ACM Multimedia (MM) 2021 .
  • 2021.06: I have been invited as a reviewer for ICLR 2022 .
  • 2021.04: I have received the SIAM Student Travel Award to support the paper presentation at SDM 2021.
  • 2021.04: I have been invited as a reviewer for NeurIPS 2021.
  • 2021.03: Our journal extension of the unbiased Face Recognition paper is uploaded to the arXiv.
  • 2021.03: Our new Neural Pruning survey paper is uploaded to the arXiv.
  • 2021.03: I have been invited as a reviewer for IEEE Robotics and Automation Letters (RA-L) .
  • 2021.02: I have been invited as a reviewer for ICCV 2021.
  • 2021.01: I have been invited as a reviewer for IEEE Transactions on Image Processing (TIP) .
  • 2021.01: Our Neural Pruning paper is accepted by ICLR 2021 as Poster.
  • 2020.12: Our Semi-supervised DA paper is accepted as a regular paper by SDM 2021 .
  • 2020.12: Our new Face Synthesis paper is uploaded to the arXiv.
  • 2020.12: I will start my 2021 summer intern at Adobe Research remotely.
  • 2020.12: I have been invited as a reviewer for CVPR 2021 .
  • 2020.11: I have been promoted as a senior program committee (SPC) member for IJCAI 2021 .
  • 2020.09: I have been invited as a program committee (PC) member for AAAI 2021 .
  • 2020.08: I have been invited as a program committee (PC) member for IJCAI 2021 .
  • 2020.07: Our paper is accepted by ECCV 2020 as Poster.
  • 2020.05: Our paper is accepted by CVPR Workshop on Fair, Data Efficient and Trusted Computer Vision, 2020.
  • 2019.12: I have been invited as a program committee (PC) member for IJCAI-PRICAI 2020 .
  • 2019.11: Our paper is accepted by AAAI 2020 as Poster.
  • 2019.10: Our paper is awarded as the Best Paper of ICCV Workshop on RLQ, 2019.
  • 2019.09: Our paper is accepted by NeurIPS 2019 as Poster.
  • 2019.08: Our paper is accepted by ICCVW on RLQ, 2019 as Oral.
  • 2019.06: Start my internship at Adobe in San Jose.
  • 2018.09: Begin my journey in Smile Lab, Northeastern University at Boston.

Experiences

    SMILE Lab, Northeastern University, Boston, USA

    Research Assistant,   Sep. 2018 ~ Now

    Supervisor: Prof. Yun Raymond Fu

    Salesforce Research, Palo Alto, USA

    Research Intern,   May 2022 ~ Dec. 2022

    Mentors: Dr. Ning Yu, Dr. Chen Xing, Dr. Shu Zhang, Prof. Stefano Ermon, Dr. Caiming Xiong and Dr. Ran Xu

    Adobe Research, San Jose, USA

    Research Intern,   June 2021 ~ Sep. 2021

    Mentors: Dr. Sungchul Kim, Dr. Handong Zhao, Dr. Tong Yu and Dr. Ryan Rossi

    Adobe, San Jose, USA

    Data Science Intern,   June 2019 ~ Aug. 2019

    Mentors: Dr. Jie Zhang, Dr. Yiwen Sun and Dr. Bo Peng

    OMEGA Lab, Xidian University, Xi'an, China

    Visiting Research Assistant,   Sep. 2017 ~ June 2018

    Mentors: Prof. Maoguo Gong and Prof. Yue Wu

Selected Conference Papers

Making Reconstruction-based Method Great Again for Video Anomaly Detection
Yizhou Wang, Can Qin, Yue Bai, Yi Xu, Xu Ma, Yun Fu
IEEE International Conference on Data Mining (ICDM), 2022.
[Paper] [Code]
Robust Semi-supervised Domain Adaptation against Noisy Labels
Can Qin, Yizhou Wang, Yun Fu
ACM International Conference on Information and Knowledge Management (CIKM), 2022.
[Paper] [Code]
Self-supervision Meets Adversarial Perturbation: A Novel Framework for Anomaly Detection
Yizhou Wang, Can Qin, Rongzhe Wei, Yi Xu, Yue Bai, Yun Fu
ACM International Conference on Information and Knowledge Management (CIKM), 2022.
[Paper] [Code]
External Knowledge Infusion for Tabular Pre-training Models with Dual-adapters
Can Qin, Sungchul Kim, Handong Zhao, Tong Yu, Ryan Rossi, Yun Fu
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2022.
[Paper] [Code]
Emerging Paradigms of Neural Network Pruning
Huan Wang, Can Qin, Yue Bai, Yulun Zhang, Yun Fu
International Joint Conference on Artificial Intelligence (IJCAI), 2022.
[arXiv] [Code]
Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework
Xu Ma, Can Qin, Haoxuan You, Haoxi Ran and Yun Fu
International Conference on Learning Representations (ICLR), 2022.
[Paper] [Code]
Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation
Can Qin, Handong Zhao, Lichen Wang, Huan Wang, Yulun Zhang and Yun Fu
Advances in Neural Information Processing Systems (NeurIPS), 2021.
[Paper] [Code]
Neural Pruning via Growing Regularization
Huan Wang, Can Qin, Yulun Zhang, Yun Fu
International Conference on Learning Representations (ICLR), 2021.
[Paper] [arXiv] [Code] [BibTex]
Contradictory Structure Learning for Semi-supervised Domain Adaptation
Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, Yun Fu
SIAM International Conference on Data Mining (SDM), 2021.
[Paper] [arXiv] [Code] [BibTex]
PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation
Can Qin*, Haoxuan You*, Lichen Wang, C.-C. Jay Kuo, Yun Fu. (* equal contribution)
Advances in Neural Information Processing Systems (NeurIPS), 2019.
[Paper] [Code] [BibTex]
Generatively Inferential Co-Training for Unsupervised Domain Adaptation
Can Qin, Lichen Wang, Yulun Zhang, Yun Fu.
ICCV Workshop on Real-World Recognition from Low-Quality Images and Videos, 2019. (Best Paper Award )
[Paper] [BibTex]

Journal Papers

Semi-supervised Domain Adaptive Structure Learning
Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, Yun Fu
IEEE Transactions on Image Processing (TIP), 2022.
[Paper] [arXiv] [Code]
Self-Directed Online Machine Learning for Topology Optimization
Changyu Deng, Yizhou Wang, Can Qin, Yun Fu, Wei Lu
Nature Communications (Nature Comm), 2022.
[Paper]

Pre-print Papers

Adapting Stepsizes by Momentumized Gradients Improves Optimization and Generalization
Yizhou Wang, Yue Kang, Can Qin, Yi Xu, Huan Wang, Yulun Zhan, Yun Fu
arXiv:2106.11514, 2021.
[arXiv]
Balancing Biases and Preserving Privacy on Balanced Faces in the Wild
Joseph P Robinson, Can Qin, Yann Henon, Samson Timoner, Yun Fu
arXiv:2103.09118, 2021.
[arXiv]

Awards

  • SIAM Student Travel Award, 2021
  • Best Paper Award of ICCV Workshop on RLQ, 2019
  • The Star of Graduates in Class 2018 (Highest Honor in XDU), 2018
  • The First Prize Scholarship in XDU, 2016, 2017
  • Meritorious Winner of the Interdisciplinary Contest in Modeling, 2016
  • Outstanding Student Leader in XDU, 2015

Professonal Activities

  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Reviewer
  • Transactions on Machine Learning Research (TMLR), Reviewer
  • ACM Transactions on Knowledge Discovery from Data (TKDD), Reviewer
  • IEEE Robotics and Automation Letters (RA-L), Reviewer
  • IEEE Transactions on Image Processing (TIP), Reviewer
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Reviewer
  • IEEE Computational Intelligence Magazine, External Reviewer
  • International Joint Conference on Artificial Intelligence (IJCAI), SPC 21, PC 20, 22
  • AAAI Conference on Artificial Intelligence (AAAI), PC 21, 22
  • Conference on Neural Information Processing Systems (NeurIPS), Reviewer 21, 22, 23
  • International Conference on Learning Representations (ICLR), Reviewer 22, 23
  • International Conference on Machine Learning (ICML), Reviewer 22
  • The Conference on Computer Vision and Pattern Recognition (CVPR), PC 21, Reviewer 22
  • International Conference on Computer Vision (ICCV), PC 21
  • European Conference on Computer Vision (ECCV), Reviewer 22
  • IEEE International Conference on Automatic Face and Gesture Recognition (FG), Volunteer 18, Reviewer 21
  • 5th Recognizing Families In the Wild (RFIW), [White Paper Link], with FG21, Program Co-Chair

Project Demos

Project: Optical Character Recognition (OCR) for Banner Images
Tools: Tesseract OCR, OpenCV
Methods: EAST (Text Localization), LSTM (Text Recognition)
Pipeline: RGB -> Gray -> Gaussian Filtering -> Binarization -> OCR
Full Demo: Link

Programming Skills

  • Language: Python, MATLAB, C/C++, LATEX, Markdown and others.
  • Machine Learning Frameworks: PyTorch, TensorFlow, Keras, PyG, AllenNLP, Sklearn, OpenCV and others.