Li Ang   李昂

Publication

1. On the Reliability of Computer Use Agents. 2026. bib
   Gonzalo Gonzalez-Pumariega, Saaket Agashe, Jiachen Yang, Ang Li, Xin Eric Wang

   
   @misc{gonzalez2026reliability,
         title={On the Reliability of Computer Use Agents},
         author={Gonzalo Gonzalez-Pumariega and Saaket Agashe and Jiachen Yang and Ang Li and Xin Eric Wang},
         year={2026},
         eprint={2604.17849},
         archivePrefix={arXiv},
         primaryClass={cs.AI}
   }

2. Retrospective Feature Estimation for Continual Learning. TMLR 2026 Featured Certification (presented at ICML 2026). bib
   Nghia D. Nguyen, Hieu Trung Nguyen, Ang Li, Hoang Pham, Viet Anh Nguyen, Khoa D. Doan

   
   @article{nguyen2026retrospective,
         title={Retrospective Feature Estimation for Continual Learning},
         author={Nghia D. Nguyen and Hieu Trung Nguyen and Ang Li and Hoang Pham and Viet Anh Nguyen and Khoa D. Doan},
         journal={Transactions on Machine Learning Research},
         year={2026},
         note={Presented at ICML 2026},
         eprint={2406.17381},
         archivePrefix={arXiv},
         primaryClass={cs.LG},
         url={https://arxiv.org/abs/2406.17381},
   }

3. Scaling Agents for Computer Use (Agent S3). TMLR 2026. bib
   Gonzalo Gonzalez-Pumariega, Vincent Tu, Chih-Lun Lee, Jiachen Yang, Ang Li, Xin Eric Wang

   
   @article{gonzalez2026scaling,
         title={Scaling Agents for Computer Use},
         author={Gonzalo Gonzalez-Pumariega and Vincent Tu and Chih-Lun Lee and Jiachen Yang and Ang Li and Xin Eric Wang},
         journal={Transactions on Machine Learning Research},
         year={2026},
         eprint={2510.02250},
         archivePrefix={arXiv},
         primaryClass={cs.AI}
   }

4. Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agents. COLM 2025. bib
   Saaket Agashe, Kyle Wong, Vincent Tu, Jiachen Yang, Ang Li, Xin Eric Wang

   
   @inproceedings{agashe2025agents2,
         title={Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agents},
         author={Saaket Agashe and Kyle Wong and Vincent Tu and Jiachen Yang and Ang Li and Xin Eric Wang},
         booktitle={Conference on Language Modeling (COLM)},
         year={2025},
         eprint={2504.00906},
         archivePrefix={arXiv},
         primaryClass={cs.AI}
   }

5. Agent S: An Open Agentic Framework that Uses Computers Like a Human. ICLR 2025. bib
   Saaket Agashe, Jiuzhou Han, Shuyu Gan, Jiachen Yang, Ang Li, Xin Eric Wang

   
   @inproceedings{agashe2025agents,
         title={Agent S: An Open Agentic Framework that Uses Computers Like a Human},
         author={Saaket Agashe and Jiuzhou Han and Shuyu Gan and Jiachen Yang and Ang Li and Xin Eric Wang},
         booktitle={International Conference on Learning Representations (ICLR)},
         year={2025},
         eprint={2410.08164},
         archivePrefix={arXiv},
         primaryClass={cs.AI}
   }

6. Building an open-vocabulary video CLIP model with better architectures, optimization and data. PAMI 2024. bib
   Zuxuan Wu, Zejia Weng, Wujian Peng, Xitong Yang, Ang Li, Larry S. Davis, Yu-Gang Jiang

   
   @misc{wu2023building,
         title={Building an Open-Vocabulary Video CLIP Model with Better Architectures, Optimization and Data}, 
         author={Zuxuan Wu and Zejia Weng and Wujian Peng and Xitong Yang and Ang Li and Larry S. Davis and Yu-Gang Jiang},
         year={2023},
         eprint={2310.05010},
         archivePrefix={arXiv},
         primaryClass={cs.CV}
   }
                                   

7. PolicyCleanse: Backdoor Detection and Mitigation for Competitive Reinforcement Learning. ICCV 2023. bib
   Junfeng Guo, Ang Li, Cong Liu.

   
   @misc{guo2022backdoor,
         title={PolicyCleanse: Backdoor Detection and Mitigation for Competitive Reinforcement Learning}, 
         author={Junfeng Guo and Ang Li and Cong Liu},
         year={2023},
         eprint={2202.03609},
         archivePrefix={arXiv},
         primaryClass={cs.LG}
   }
                                   

8. Transforming CLIP to an Open-vocabulary Video Model via Interpolated Weight Optimization. ICML 2023. bib
   Zejia Weng, Xitong Yang, Ang Li, Zuxuan Wu, Yu-Gang Jiang

   
   @misc{weng2023openvclip,
     doi = {10.48550/ARXIV.2302.00624},
     url = {https://arxiv.org/abs/2302.00624},
     author = {Weng, Zejia and Yang, Xitong and Li, Ang and Wu, Zuxuan and Jiang, Yu-Gang},
     keywords = {Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences},
     title = {Transforming CLIP to an Open-vocabulary Video Model via Interpolated Weight Optimization},
     publisher = {arXiv},
     year = {2023},
     copyright = {arXiv.org perpetual, non-exclusive license}
   }
   

9. Hyperspherical Federated Learning. ECCV 2022. bib
   Xin Dong, Sai Qian Zhang, Ang Li, H.T. Kung

   
   @misc{dong2022fed,
         title={Hyperspherical Federated Learning}, 
         author={Xin Dong and Sai Qian Zhang and Ang Li and H.T. Kung},
         year={2022},
         archivePrefix={arXiv},
         primaryClass={cs.CV}
   }

10. Semi-Supervised Vision Transformers. ECCV 2022. bib
    Zejia Weng, Xitong Yang, Ang Li, Zuxuan Wu, Yu-Gang Jiang.

    
    @misc{weng2021semisupervised,
          title={Semi-Supervised Vision Transformers}, 
          author={Zejia Weng and Xitong Yang and Ang Li and Zuxuan Wu and Yu-Gang Jiang},
          year={2021},
          eprint={2111.11067},
          archivePrefix={arXiv},
          primaryClass={cs.CV}
    }

11. Neural Mean Discrepancy for Efficient Out-of-Distribution Detection. CVPR 2022. bibtex
    Xin Dong, Junfeng Guo, Ang Li, Wei-Te Ting, Cong Liu, H.T. Kung.

    
    @misc{dong2022neural,
          title={Neural Mean Discrepancy for Efficient Out-of-Distribution Detection}, 
          author={Xin Dong and Junfeng Guo and Ang Li and Wei-Te Ting and Cong Liu and H. T. Kung},
          year={2022},
          eprint={2104.11408},
          archivePrefix={arXiv},
          primaryClass={cs.LG}
    }

12. Information-theoretic Online Memory Selection for Continual Learning. ICLR 2022. bibtex
    Shengyang Sun, Daniele Calandriello, Huiyi Hu, Ang Li, Michalis Titsias.

    
    @InProceedings{sun2022cl,
          title={Information-theoretic Online Memory Selection for Continual Learning}, 
          author={Shengyang Sun and Daniele Calandriello and Huiyi Hu and Ang Li and Michalis Titsias},
          year={2022},
          booktitle = {International Conference on Learning Representations (ICLR)},
    }
                        

13. AEVA: Black-box Backdoor Detection Using Adversarial Extreme Value Analysis. ICLR 2022. code bibtex
    Junfeng Guo, Ang Li, Cong Liu.

    
    @misc{guo2021aeva,
          title={AEVA: Black-box Backdoor Detection Using Adversarial Extreme Value Analysis}, 
          author={Junfeng Guo and Ang Li and Cong Liu},
          year={2021},
          eprint={2110.14880},
          archivePrefix={arXiv},
          primaryClass={cs.LG}
    }
    				    

14. One Pass ImageNet. NeurIPS 2021 Workshop on ImageNet. bibtex
    Huiyi Hu, Ang Li, Daniele Calandriello, Dilan Gorur.

    
    @misc{hu2021opin,
          title={One Pass ImageNet}, 
          author={Huiyi Hu and Ang Li and Daniele Calandriello and Dilan Gorur},
          year={2021},
          eprint={2111.01956},
          archivePrefix={arXiv},
          primaryClass={cs.LG}
    }

15. ETA Prediction with Graph Neural Networks in Google Maps. CIKM 2021. bibtex
    Austin Derrow-Pinion, Jennifer She, David Wong, Oliver Lange, Todd Hester, Luis Perez, Marc Nunkesser, Seongjae Lee, Xueying Guo, Brett Wiltshire, Peter Battaglia, Vishal Gupta, Ang Li, Zhongwen Xu, Alvaro Sanchez-Gonzalez, Yujia Li, Petar Veličković.

    
    @article{gnngmaps2021,
      author    = {Austin Derrow{-}Pinion and
                   Jennifer She and
                   David Wong and
                   Oliver Lange and
                   Todd Hester and
                   Luis Perez and
                   Marc Nunkesser and
                   Seongjae Lee and
                   Xueying Guo and
                   Brett Wiltshire and
                   Peter W. Battaglia and
                   Vishal Gupta and
                   Ang Li and
                   Zhongwen Xu and
                   Alvaro Sanchez{-}Gonzalez and
                   Yujia Li and
                   Petar Velickovic},
      title     = {{ETA} Prediction with Graph Neural Networks in Google Maps},
      journal   = {CoRR},
      volume    = {abs/2108.11482},
      year      = {2021},
      url       = {https://arxiv.org/abs/2108.11482},
      eprinttype = {arXiv},
      eprint    = {2108.11482},
      timestamp = {Fri, 27 Aug 2021 15:02:29 +0200},
      biburl    = {https://dblp.org/rec/journals/corr/abs-2108-11482.bib},
      bibsource = {dblp computer science bibliography, https://dblp.org}
    }
    				    

16. Task-agnostic Continual Learning with Hybrid Probabilistic Models. ICML 2021 workshop. bibtex
    Polina Kirichenko, Mehrdad Farajtabar, Dushyant Rao, Balaji Lakshminarayanan, Nir Levine, Ang Li, Huiyi Hu, Andrew Gordon Wilson, Razvan Pascanu.

    
    @article{polina2021hybridcl,
      author    = {Polina Kirichenko and
                   Mehrdad Farajtabar and
                   Dushyant Rao and
                   Balaji Lakshminarayanan and
                   Nir Levine and
                   Ang Li and
                   Huiyi Hu and
                   Andrew Gordon Wilson and
                   Razvan Pascanu},
      title     = {Task-agnostic Continual Learning with Hybrid Probabilistic Models},
      journal   = {CoRR},
      volume    = {abs/2106.12772},
      year      = {2021},
      url       = {https://arxiv.org/abs/2106.12772},
      archivePrefix = {arXiv},
      eprint    = {2106.12772},
      timestamp = {Wed, 30 Jun 2021 16:14:10 +0200},
      biburl    = {https://dblp.org/rec/journals/corr/abs-2106-12772.bib},
      bibsource = {dblp computer science bibliography, https://dblp.org}
    }
    

17. The Effectiveness of Memory Replay in Large Scale Continual Learning. CVPR 2021 Workshop on Continual Learning. bibtex
    Yogesh Balaji, Mehrdad Farajtabar, Dong Yin, Alex Mott, Ang Li.

    
    @misc{balaji2020taskonomycl,
        title={The Effectiveness of Memory Replay in Large Scale Continual Learning},
        author={Yogesh Balaji and Mehrdad Farajtabar and Dong Yin and Alex Mott and Ang Li},
        year={2020},
        eprint={2010.02418},
        archivePrefix={arXiv},
        primaryClass={cs.LG}
    }
                                    

18. PredCoin: Defense against Query-based Hard-label Attack. 2021.
    Junfeng Guo, Yaswanth Yadlapalli, Thiele Lothar, Ang Li, Cong Liu
19. Learning to Incentivize Other Learning Agents. NeurIPS 2020. bibtex code
    Jiachen Yang, Ang Li, Mehrdad Farajtabar, Peter Sunehag, Edward Hughes and Hongyuan Zha.

    
    @misc{yang2020learning,
        title={Learning to Incentivize Other Learning Agents},
        author={Jiachen Yang and Ang Li and Mehrdad Farajtabar and Peter Sunehag and Edward Hughes and Hongyuan Zha},
        year={2020},
        eprint={2006.06051},
        archivePrefix={arXiv},
        primaryClass={cs.LG}
    }
                                    

20. SOLA: Continual Learning with Second-Order Loss Approximation. ICML 2020 Workshop on Continual Learning. bibtex
    Dong Yin, Mehrdad Farajtabar, Ang Li.

    
    @misc{yin2020sola,
        title={SOLA: Continual Learning with Second-Order Loss Approximation},
        author={Dong Yin and Mehrdad Farajtabar and Ang Li},
        year={2020},
        eprint={2006.10974},
        archivePrefix={arXiv},
        primaryClass={cs.LG}
    }
                            

21. The AVA-Kinetics Localized Human Actions Video Dataset. 2020. data bibtex
    Ang Li, Meghana Thotakuri, David A. Ross, Joao Carreira, Alexander Vostrikov, Andrew Zisserman.

    
    @misc{li2020avakinetics,
        title={The AVA-Kinetics Localized Human Actions Video Dataset},
        author={Ang Li and Meghana Thotakuri and David A. Ross and João Carreira and Alexander Vostrikov and Andrew Zisserman},
        year={2020},
        eprint={2005.00214},
        archivePrefix={arXiv},
        primaryClass={cs.CV}
    }
                                    

22. Hybrid Models for Open Set Recognition. ECCV 2020 Oral. bibtex
    Hongjie Zhang, Ang Li, Jie Guo, Yanwen Guo.

    
    @misc{zhang2020hybrid,
        title={Hybrid Models for Open Set Recognition},
        author={Hongjie Zhang and Ang Li and Jie Guo and Yanwen Guo},
        year={2020},
        eprint={2003.12506},
        archivePrefix={ECCV 2020},
        primaryClass={cs.CV}
    }
                                    

23. PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving. CVPR 2020. bibtex
    Zelun Kong, Junfeng Guo, Ang Li, Cong Liu.

    
    @misc{kong2019physgan,
        title={PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving},
        author={Zelun Kong and Junfeng Guo and Ang Li and Cong Liu},
        year={2019},
        eprint={1907.04449},
        archivePrefix={arXiv},
        primaryClass={cs.CV}
    }
                                    

24. Orthogonal Gradient Descent for Continual Learning. AISTATS 2020. bibtex
    Mehrdad Farajtabar, Navid Azizan, Alex Mott, Ang Li.

    
    @misc{farajtabar2019orthogonal,
        title={Orthogonal Gradient Descent for Continual Learning},
        author={Mehrdad Farajtabar and Navid Azizan and Alex Mott and Ang Li},
        year={2019},
        eprint={1910.07104},
        archivePrefix={arXiv},
        primaryClass={cs.LG}
    }}
                                

25. Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control. ICLR 2020. bibtex
    Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui.

    
    @misc{levine2019prediction,
        title={Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control},
        author={Nir Levine and Yinlam Chow and Rui Shu and Ang Li and Mohammad Ghavamzadeh and Hung Bui},
        year={2019},
        eprint={1909.01506},
        archivePrefix={arXiv},
        primaryClass={cs.LG}
    }
                                

26. Improved Knowledge Distillation via Teacher Assistant. AAAI 2020. Bibtex
    Seyed-Iman Mirzadeh, Mehrdad Farajtabar, Ang Li, Nir Levine, Akihiro Matsukawa, Hassan Ghasemzadeh.

    
    @article{DBLP:journals/corr/abs-1902-03393,
      author    = {Seyed{-}Iman Mirzadeh and
                   Mehrdad Farajtabar and
                   Ang Li and
                   Nir Levine and
                   Akihiro Matsukawa and
                   Hassan Ghasemzadeh},
      title     = {Improved Knowledge Distillation via Teacher Assistant: Bridging the
                   Gap Between Student and Teacher},
      journal   = {AAAI 2020},
      volume    = {abs/1902.03393},
      year      = {2020},
      url       = {http://arxiv.org/abs/1902.03393},
      archivePrefix = {arXiv},
      eprint    = {1902.03393},
      timestamp = {Tue, 21 May 2019 18:03:39 +0200},
      biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1902-03393},
      bibsource = {dblp computer science bibliography, https://dblp.org}
    }
                                

27. Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing. NeurIPS 2019 workshop. bibtex
    Ge Liu, Heng-Tze Cheng, Rui Wu, Jing Wang, Jayiden Ooi, Lihong Li, Ang Li, Sibon Li, Craig Boutilier.

@misc{liu2020data,
      title={Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing}, 
      author={Ge Liu and Rui Wu and Heng-Tze Cheng and Jing Wang and Jayden Ooi and Lihong Li and Ang Li and Wai Lok Sibon Li and Craig Boutilier and Ed Chi},
      year={2020},
      eprint={2002.05229},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}
				    

28. Cross-View Policy Learning for Street Navigation. ICCV 2019. bibtex
    Ang Li*, Huiyi Hu*, Piotr Mirowski, Mehrdad Farajtabar.

@InProceedings{streetair_iccv2019,
author = {Ang Li and Huiyi Hu and Piotr Mirowski and Mehrdad Farajtabar},
title = {Cross-View Policy Learning for Street Navigation},
booktitle = {International Conference on Computer Vision (ICCV)},
year = {2019}
}

29. A Generalized Framework for Population Based Training. KDD 2019. youtube bibtex
    Ang Li, Ola Spyra, Sagi Perel, Valentin Dalibard, Max Jaderberg, Chenjie Gu, David Budden, Tim Harley, Pramod Gupta.

    @InProceedings{li_pbt_kdd2019,
    author = {Ang Li and Ola Spyra and Sagi Perel and Valentin Dalibard and Max Jaderberg and Chenjie Gu and David Budden and Tim Harley and Pramod Gupta},
    title = {A Generalized Framework for Population Based Training},
    booktitle = {KDD},
    year = {2019}
    }
    

30. SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-task Learning. AAAI 2019.
    Jiaqi Ma, Zhe Zhao, Jilin Chen, Ang Li, Lichan Hong, Ed H. Chi.
31. Improving Open Set Domain Adaptation Using Image-to-Image Translation. ICME 2019.
    Hongjie Zhang, Ang Li, Xu Han, Zhaoming Chen, Yang Zhang, Yanwen Guo.
32. Layout-induced Video Representation for Recognizing Agent-in-Place Actions. ICCV 2019. bibtex
    Ruichi Yu, Hongcheng Wang, Ang Li, Jingxiao Zheng, Vlad I. Morariu, Larry S. Davis.

    @article{Yu2018RepresentingVB,
      title={Layout-induced Video Representation for Recognizing Agent-in-Place Actions},
      author={Ruichi Yu and Hongcheng Wang and Ang Li and Jingxiao Zheng and Vlad I. Morariu and Larry S. Davis},
      journal={CoRR},
      year={2018},
      volume={abs/1804.01429}
    }
                                

33. C-WSL: Count-guided Weakly Supervised Localization. ECCV 2018. bibtex
    Mingfei Gao, Ang Li, Ruichi Yu, Vlad I. Morariu, Larry S. Davis.

    @InProceedings{gao2017cwsl,
      title={C-WSL: Count-guided Weakly Supervised Localization.},
      author={Mingfei Gao and Ang Li and Ruichi Yu and Vlad I. Morariu and Larry S. Davis},
      booktitle={European Conference on Computer Vision (ECCV)},
      year={2018}
    }
                                    

34. NISP: Pruning Networks using Neuron Importance Score Propagation. CVPR 2018. bibtex
    Ruichi Yu, Ang Li, Chun-Fu Chen, Jui-Hsin Lai, Vlad I. Morariu, Xintong Han, Mingfei Gao, Ching-Yung Lin, Larry S. Davis.

    @InProceedings{Yu_2018_CVPR,
    author = {Yu, Ruichi and Li, Ang and Chen, Chun-Fu and Lai, Jui-Hsin and Morariu, Vlad I. and Han, Xintong and Gao, Mingfei and Lin, Ching-Yung and Davis, Larry S.},
    title = {NISP: Pruning Networks Using Neuron Importance Score Propagation},
    booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    month = {June},
    year = {2018}
    }
                                        

35. Dynamic Zoom-in Network for Fast Object Detection in Large Images. CVPR 2018. bibtex
    Mingfei Gao, Ruichi Yu, Ang Li, Vlad I. Morariu, Larry S. Davis.

    @InProceedings{Gao_2018_CVPR,
    author = {Gao, Mingfei and Yu, Ruichi and Li, Ang and Morariu, Vlad I. and Davis, Larry S.},
    title = {Dynamic Zoom-In Network for Fast Object Detection in Large Images},
    booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    month = {June},
    year = {2018}
    }
                                                

36. Learning Visual N-Grams from Web Data. ICCV 2017. bibtex
    Ang Li, Allan Jabri, Armand Joulin and Laurens van der Maaten.
37. Visual Relationship Detection with Internal and External Linguistic Knowledge Distillation. ICCV 2017. bibtex
    Ruichi Yu, Ang Li, Vlad I. Morariu and Larry S. Davis.
38. Generating Holistic 3D Scene Abstractions for Text-based Image Retrieval. CVPR 2017. poster data code bibtex
    Ang Li, Jin Sun, Joe Yue-Hei Ng, Ruichi Yu, Vlad I. Morariu and Larry S. Davis.
39. Towards Unified Data and Lifecycle Management for Deep Learning. ICDE 2017. bibtex
    Hui Miao, Ang Li, Larry S. Davis and Amol Deshpande
40. On Model Discovery For Hosted Data Science Projects. SIGMOD 2017 workshop. bibtex
    Hui Miao, Ang Li, Larry S. Davis and Amol Deshpande.

    @inproceedings{Miao:2017:MDH:3076246.3076252,
     author = {Miao, Hui and Li, Ang and Davis, Larry S. and Deshpande, Amol},
     title = {On Model Discovery For Hosted Data Science Projects},
     booktitle = {Proceedings of the 1st Workshop on Data Management for End-to-End Machine Learning},
     series = {DEEM'17},
     year = {2017},
     isbn = {978-1-4503-5026-6},
     location = {Chicago, IL, USA},
     pages = {6:1--6:4},
     articleno = {6},
     numpages = {4},
     url = {http://doi.acm.org/10.1145/3076246.3076252},
     doi = {10.1145/3076246.3076252},
     acmid = {3076252},
     publisher = {ACM},
     address = {New York, NY, USA},
    } 
                                                                    

41. Selective Encoding for Recognizing Unreliably Localized Faces. ICCV 2015 spotlight. youtube code bibtex
    Ang Li, Vlad I. Morariu and Larry S. Davis.
42. Efficient Discriminative Nonorthogonal Binary Subspace with its Application to Visual Tracking. 2015. bibtex
    Ang Li, Feng Tang, Yanwen Guo and Hai Tao.

    @article{Li2015EfficientDN,
      title={Efficient Discriminative Nonorthogonal Binary Subspace with its Application to Visual Tracking},
      author={Ang Li and Feng Tang and Yanwen Guo and Hai Tao},
      journal={CoRR},
      year={2015},
      volume={abs/1509.08383}
    }
                                                                            

43. Planar Structure Matching Under Projective Uncertainty for Geolocation. ECCV 2014. youtube bibtex
    Ang Li, Vlad I. Morariu and Larry S. Davis.
44. Object Tracking Using Learned Feature Manifolds. CVIU 2013. bibtex
    Yanwen Guo, Ye Chen, Feng Tang, Ang Li, Weitao Luo, and Mingming Liu.
45. Bag of Textons for Image Segmentation via Soft Clustering and Convex Shift. CVPR 2012. bibtex
    Zhiding Yu, Ang Li, Oscar C. Au and Chunjing Xu.
46. Discriminative Nonorthogonal Binary Subspace Tracking. ECCV 2010. bibtex
    Ang Li, Feng Tang, Yanwen Guo and Hai Tao.

Talks & Interviews

• AGI Playground 2026. Gardens by the Bay, Singapore, August 2026.
• How AI Redefines Time. IC Your Trade, IC Markets with Bloomberg Media Studios, July 2026.
• SNU AIIS × Simular Computer-Use Agents Research Forum. Seoul National University AI Institute, July 2026.
• The Autonomous Computer: Full-stack Infrastructure for Computer Use Agents. Workshop at AI Engineer World's Fair 2026, San Francisco, June 2026.
• Xoogler Meetup with Simular's Ang Li. Xoogler and Singapore Global Network with SGInnovate, June 2026.
• Computer-use agents for governments and enterprises. The World Bank Group, June 2026.
• One Society, or Two? The Age of Autonomous Computers. SuperAI Summit 2026, Singapore, June 2026.
• The 100x Company: Rebuilding the Business Around AI. Panel at SuperAI Summit 2026, Singapore, June 2026.
• Simular: Innovating in Autonomous Computing with Ang Li. theCUBE + NYSE Wired, SiliconANGLE, April 2026.
• Industry Lightning Talk. UCSB CRML Agentic AI Summit, January 2026.
• StartX Demo Day. Stanford StartX, 2026.
• Google for Startups Accelerator: AI First Demo Day. Google Cloud, NY Tech Week, June 2025.
• AI Gatherings at Google I/O. Google, May 2025.
• How computer-use agents will take over everything we do. Second Order Effect, Episode 1, May 2025.
• Is the Defensible Moat a Myth in AI?. Fund/Build/Scale, January 2025.
• Computer use agents that think fast and slow. AI at Princeton, November 2024.
• The Race to AGI. Panel at Ai4 2024, Las Vegas, August 2024.
• Simular demo. SPC Demo Faire, South Park Commons, December 2023.

Press Coverage

• Simular sees Korea's hardware edge in AI agent era. The Korea Herald.
• Simular's AI agent wants to run your Mac, Windows PC for you. TechCrunch.
• Simular raises $21.5M for AI agent that controls your PC. The Tech Buzz.
• Former Google DeepMind engineer behind Simular says other AI agents are doing it wrong. The Register.
• Meet Simular, the startup that wants to build autonomous computers. IBM Think.
• Meet the AI Agent With Multiple Personalities. WIRED.
• Baidu Apollo Day: Expanded robotaxi operations and new autonomous driving software and hardware. Autonomous Driving International.
• Baidu Announces Plan to Build the World's Largest Fully Driverless Ride-Hailing Service Area in 2023. PR Newswire.
• DeepMind’s One Pass ImageNet: A New Benchmark for Resource Efficiency in Deep Learning. Synced Review
• ETA Prediction with Graph Neural Networks in Google Maps (Paper Explained). The AI Epiphany.
• An algorithm that evolved Starcraft bots is also training self-driving cars. MIT Technology Review
• Waymo and DeepMind mimic evolution to develop a new, better way to train self-driving AI. TechCrunch
• How evolutionary selection can train more capable self-driving cars. DeepMind Blog.
• Using automated data augmentation to advance our Waymo Driver. Waymo Blog
• How Google Maps uses DeepMind’s AI tools to predict your arrival time. The Verge.
• DeepMind claims its AI improved Google Maps travel time estimates by up to 50%. VentureBeat
• Traffic prediction with advanced Graph Neural Networks. DeepMind Blog
• DeepMind’s AI uses aerial and ground-view data to navigate unseen areas. VentureBeat

Academic Service

• Area Chair: NeurIPS Workshop on Meta Learning, 2021–2022.
• Senior Program Committee: AAAI 2021, IJCAI 2020–2021, AAMAS 2020.
• Session Chair: IJCAI 2021.
• Program Committee: ICLR, NeurIPS, ICML, CVPR, ICCV, ECCV, IJCAI, AISTATS, ACM Multimedia.
• Journal Reviewer: TPAMI, TNNLS, TIP, IEEE Transactions on Cybernetics, The Visual Computer, SPIE Journal of Electronic Imaging, Robotics and Autonomous Systems, Machine Learning.