Qi Chen

Qi Chen

Australian Institute for Machine Learning - Projects

Faculty of Sciences, Engineering and Technology

Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.

Dr. Qi Chen is currently a postdoctoral research fellow at the Australian Institute for Machine Learning (AIML), the University of Adelaide, working with Prof. Anton van den Hengel and A/Prof. Qi Wu. He focuses mainly on Controllable Generative AI for Multimodality, (Multimodal) Large Language Models (LLMs), and Multimodal AI for Real-world Applications/Domains (e.g., Medicine, Architecture, and the Internet). He has over 20 peer-reviewed publications, most in flagship journals/conference proceedings, including IEEE-TPAMI/TIP/TMM, CVPR, NeurIPS, ICCV, etc. He also serves as a reviewer for top-tier journals/conference proceedings, including Nature Communications, IEEE-TPAMI, IJCV, CVPR, ICML, NeurIPS, ICLR, ICCV, ECCV, etc.

  • Journals
    Year Citation
    2025 Ge, J., Zhang, B., Liu, A., Phan, V. M. H., Chen, Q., Shu, Y., & Zhao, Y. (2025). CIT: Rethinking class-incremental semantic segmentation with a Class Independent Transformation. Pattern Recognition, 167, 111707.
    DOI
    2025 Zeng, R., Zhuo, Y., Li, J., Yang, Y., Wu, H., Chen, Q., . . . Leung, V. C. M. (2025). Improving Video Moment Retrieval by Auxiliary Moment-Query Pairs With Hyper-Interaction. IEEE Transactions on Circuits and Systems for Video Technology, 35(5), 3940-3954.
    DOI
    2025 Tan, M., Chen, Q., Huang, Z., Wu, Q., Li, Y., & Zhou, J. (2025). Auto-3D-house Design from Structured User Requirements. MACHINE INTELLIGENCE RESEARCH, 22(2), 18 pages.
    DOI
    2025 Zhang, J., Chen, X., Yang, B., Guan, Q., Chen, Q., Chen, J., . . . Xia, Y. (2025). Advances in attention mechanisms for medical image segmentation. Computer Science Review, 56, 18 pages.
    DOI Scopus1
    2024 Chen, Q., Zhao, R., Wang, S., Phan, V. M. H., Hengel, A. V. D., Verjans, J., . . . Wu, Q. (2024). A Survey of Medical Vision-and-Language Applications and Their Techniques.. CoRR, abs/2411.12195.
    2024 Guo, Y., Tan, M., Deng, Z., Wang, J., Chen, Q., Cao, J., . . . Chen, J. (2024). Towards Lightweight Super-Resolution With Dual Regression Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12), 8365-8379.
    DOI Scopus1 Europe PMC1
    2022 Guo, Y., Zheng, Y., Tan, M., Chen, Q., Li, Z., Chen, J., . . . Huang, J. (2022). Towards Accurate and Compact Architectures via Neural Architecture Transformer. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(10), 6501-6516.
    DOI Scopus31 WoS5 Europe PMC6
    2021 Tan, M., Xu, S., Zhang, S., & Chen, Q. (2021). A review on deep adversarial visual generation. Journal of Image and Graphics, 26(12), 2751-2766.
    DOI Scopus2
    2020 Chen, Q., Wu, Q., Chen, J., Wu, Q., Van Den Hengel, A., & Tan, M. (2020). Scripted Video Generation with a Bottom-Up Generative Adversarial Network. IEEE Transactions on Image Processing, 29, 7454-7467.
    DOI Scopus28 WoS9
    2019 Guo, Y., Chen, Q., Chen, J., Wu, Q., Shi, Q., & Tan, M. (2019). Auto-Embedding Generative Adversarial Networks for High Resolution Image Synthesis. IEEE Transactions on Multimedia, 21(11), 2726-2737.
    DOI Scopus63 WoS44

  • Conference Papers
    Year Citation
    2025 Chen, Q., Xie, Y., Wu, B., Chen, X., Ang, J., To, M. -S., . . . Wu, Q. (2025). Act Like a Radiologist: Radiology Report Generation Across Anatomical Regions. In Lecture Notes in Computer Science Vol. 15477 LNCS (pp. 36-52). Hanoi, Vietnam: Springer Nature Singapore.
    DOI
    2025 Xu, H. M., Chen, Q., Wang, L., & Liu, L. (2025). Attention-Driven GUI Grounding: Leveraging Pretrained Multimodal Large Language Models Without Fine-Tuning. In Proceedings of the AAAI Conference on Artificial Intelligence Vol. 39 (pp. 8851-8859). Philadelphia, USA: Association for the Advancement of Artificial Intelligence (AAAI).
    DOI
    2024 Xie, Y., Chen, Q., Wang, S., To, M. S., Lee, I., Khoo, E. W., . . . Wu, Q. (2024). PairAug: What Can Augmented Image-Text Pairs Do for Radiology?. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 11652-11661). Seattle, Washington, USA: IEEE.
    DOI Scopus2
    2024 Huang, Z., Chen, Q., Sung, L., Yang, Y., Wang, N., Wu, Q., & Tan, M. (2024). G-NeRF: Geometry-enhanced Novel View Synthesis from Single-View Images. In 2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (pp. 10117-10126). WA, Seattle: IEEE COMPUTER SOC.
    DOI Scopus1
    2024 Chen, Q., Zhang, B., Wang, G., & Wu, Q. (2024). Weak-eval-Strong: Evaluating and Eliciting Lateral Thinking of LLMs with Situation Puzzles. In Advances in Neural Information Processing Systems Vol. 37.
    Scopus1
    2024 Chen, Q., Pitawela, D., Zhao, C., Zhou, G., Chen, H. T., & Wu, Q. (2024). WebVLN: Vision-and-Language Navigation on Websites. In Proceedings of the AAAI Conference on Artificial Intelligence Vol. 38 (pp. 1165-1173). Online: Association for the Advancement of Artificial Intelligence (AAAI).
    DOI Scopus3
    2023 Deng, C., Chen, Q., Qin, P., Chen, D., & Wu, Q. (2023). Prompt Switch: Efficient CLIP Adaptation for Text-Video Retrieval. In Proceedings of the IEEE International Conference on Computer Vision (pp. 15602-15612). Online: IEEE.
    DOI Scopus28
    2023 Chen, Q., Deng, C., & Wu, Q. (2023). Learning Distinct and Representative Modes for Image Captioning. In Advances in Neural Information Processing Systems Vol. 35 (pp. 14 pages). USA: Neural information processing systems foundation.
    Scopus16
    2023 Raymond, C., Chen, Q., Xue, B., & Zhang, M. (2023). Fast and Efficient Local-Search for Genetic Programming Based Loss Function Learning. In GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference (pp. 1184-1193). Lisbon Portugal: ACM.
    DOI
    2023 Chen, Q., Xue, B., Banzhaf, W., & Zhang, M. (2023). Relieving Genetic Programming from Coefficient Learning for Symbolic Regression via Correlation and Linear Scaling. In GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference (pp. 420-428). Lisbon, Portugal: ACM.
    DOI Scopus5
    2023 Zhang, H., Chen, Q., Xue, B., Banzhaf, W., & Zhang, M. (2023). A Double Lexicase Selection Operator for Bloat Control in Evolutionary Feature Construction for Regression. In GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference (pp. 1194-1202). Lisdbon, POortugal: ACM.
    DOI Scopus2
    2023 Guo, Y., Chen, Y., Zheng, Y., Chen, Q., Zhao, P., Huang, J., . . . Tan, M. (2023). Pareto-aware Neural Architecture Generation for Diverse Computational Budgets. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Vol. 2023-June (pp. 2248-2258). Vancouver, BC, Canada: IEEE.
    DOI Scopus3
    2023 Lin, J., Chen, Q., Xue, B., & Zhang, M. (2023). AMTEA-Based Multi-task Optimisation for Multi-objective Feature Selection in Classification. In J. Correia, S. Smith, & R. Qaddoura (Eds.), Conference Proceedings of the Applications of Evolutionary Computation 26th European Conference, EvoApplications 2023, Held as Part of EvoStar 2023. Vol. 13989 LNCS (pp. 623-639). Brno, Czech Republic: Springer Nature Switzerland.
    DOI Scopus2
    2023 Zhang, H., Chen, Q., Tonda, A., Xue, B., Banzhaf, W., & Zhang, M. (2023). MAP-Elites with Cosine-Similarity for Evolutionary Ensemble Learning. In G. Pappa, M. Giacobini, & Z. Vasicek (Eds.), Conference proceedings Genetic Programming. EuroGP 2023 Vol. 13986 (pp. 84-100). Brno, Czech Republic: Springer Nature Switzerland.
    DOI Scopus5
    2022 Chen, Q., Tan, M., Qi, Y., Zhou, J., Li, Y., & Wu, Q. (2022). V2C: Visual Voice Cloning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR, 2022) Vol. 2022-June (pp. 21210-21219). Online: IEEE.
    DOI Scopus21 WoS2
    2021 Chen, Y., Guo, Y., Chen, Q., Li, M., Zeng, W., Wang, Y., & Tan, M. (2021). Contrastive Neural Architecture Search with Neural Architecture Comparators. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 9497-9506). Nathville, TN, USA: IEEE.
    DOI Scopus68
    2021 Qiao, Y., Chen, Q., Deng, C., DIng, N., Qi, Y., Tan, M., . . . Wu, Q. (2021). R-GAN: Exploring Human-like Way for Reasonable Text-to-Image Synthesis via Generative Adversarial Networks. In MM 2021 - Proceedings of the 29th ACM International Conference on Multimedia (pp. 2085-2093). New York, NY, United States: Association for Computing Machinery.
    DOI Scopus17 WoS7
    2021 Al-Helali, B., Chen, Q., Xue, B., & Zhang, M. (2021). GP-based Feature Selection and Weighted KNN-based Instance Selection for Symbolic Regression with Incomplete Data. In Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (pp. 905-912). Canberra, ACT, Aust: IEEE.
    DOI Scopus2
    2021 Zheng, Y., Wen, Z., Tan, M., Zeng, R., Chen, Q., Wang, Y., & Wu, Q. (2021). Modular graph attention network for complex visual relational reasoning. In Proceedings of the 15th Asian Conference on Computer Vision (ACCV 2020), as published in Lecture Notes in Computer Science Vol. 12627 (pp. 137-153). Cham, Switzerland: Springer.
    DOI Scopus2
    2020 Chen, Q., Wang, W., Huang, K., De, S., & Coenen, F. (2020). Adversarial Domain Adaptation for Crisis Data Classification on Social Media. In Proceedings - IEEE Congress on Cybermatics: 2020 IEEE International Conferences on Internet of Things, iThings 2020, IEEE Green Computing and Communications, GreenCom 2020, IEEE Cyber, Physical and Social Computing, CPSCom 2020 and IEEE Smart Data, SmartData 2020 (pp. 282-287). Rhodes, Greece: IEEE.
    DOI Scopus4
    2020 Chen, Q., Wang, W., Huang, K., De, S., & Coenen, F. (2020). Multi-modal Adversarial Training for Crisis-related Data Classification on Social Media. In Proceedings - 2020 IEEE International Conference on Smart Computing, SMARTCOMP 2020 (pp. 232-237). Bologna, Italy: IEEE.
    DOI Scopus8
    2020 Chen, Q., Wu, Q., Tang, R., Wang, Y., Wang, S., & Tan, M. (2020). Intelligent home 3D: Automatic 3D-house design from linguistic descriptions only. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 12622-12631). online: IEEE.
    DOI Scopus37
    2020 Guo, Y., Chen, J., Wang, J., Chen, Q., Cao, J., Deng, Z., . . . Tan, M. (2020). Closed-Loop Matters: Dual Regression Networks for Single Image Super-Resolution. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 1-10). Seattle, WA, USA: IEEE.
    DOI Scopus351
    2020 Liu, L., Cao, J., Liu, M., Guo, Y., Chen, Q., & Tan, M. (2020). Dynamic Extension Nets for Few-shot Semantic Segmentation. In Proceedings of the 28th ACM International Conference on Multimedia (pp. 1-9). Seattle, WA, USA: ACM.
    DOI Scopus39
    2020 Al-Helali, B., Chen, Q., Xue, B., & Zhang, M. (2020). Data Imputation for Symbolic Regression with Missing Values: A Comparative Study. In 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (pp. 2093-2100). Canberra, ACT, Aust: IEEE.
    DOI Scopus2
    2020 Al-Helali, B., Chen, Q., Xue, B., & Zhang, M. (2020). Multi-Tree Genetic Programming-based Transformation for Transfer Learning in Symbolic Regression with Highly Incomplete Data. In 2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings (pp. 1-8). Glasgow, Scotland: IEEE.
    DOI Scopus6
    2020 Al-Helali, B., Chen, Q., Xue, B., & Zhang, M. (2020). Genetic Programming-Based Selection of Imputation Methods in Symbolic Regression with Missing Values. In M. Gallagher, N. Moustafa, & E. Lakshika (Eds.), Conference proceedings of AI 2020: Advances in Artificial Intelligence 33rd Australasian Joint Conference Vol. 12576 (pp. 163-175). Canberra, ACT, Aust: Springer International Publishing.
    DOI Scopus2
    2020 Al-Helali, B., Chen, Q., Xue, B., & Zhang, M. (2020). Genetic Programming-Based Simultaneous Feature Selection and Imputation for Symbolic Regression with Incomplete Data. In S. Palaiahnakote, G. Sanniti di Baja, L. Wang, & W. Yan (Eds.), Conference Proceedings Pattern Recognition 5th Asian Conference, ACPR 2019 Vol. 12047 LNCS (pp. 566-579). Auckland, New Zealand: Springer International Publishing.
    DOI Scopus6
    2019 Al-Helali, B., Chen, Q., Xue, B., & Zhang, M. (2019). A Genetic Programming-based Wrapper Imputation Method for Symbolic Regression with Incomplete Data. In Proceedings of the 2019 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 2395-2402). Xiamen, China: IEEE.
    DOI Scopus8
    2019 Chen, Q., Xue, B., & Zhang, M. (2019). Instance based Transfer Learning for Genetic Programming for Symbolic Regression. In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 3006-3013). Wellington, New Zealand: IEEE.
    DOI Scopus19
    2019 Guo, Y., Zheng, Y., Tan, M., Chen, Q., Chen, J., Zhao, P., & Huang, J. (2019). NAT: Neural architecture transformer for accurate and compact architectures. In Proceedings of the 33rd International Conference on Neural Information Processing Systems Vol. 32 (pp. 1-12). Red Hook, NY, USA: Curran Associates Inc.
    Scopus51
    2019 Chen, Q., & Wang, W. (2019). Multi-modal Neural Network for Traffic Event Detection. In Proceedings of the 2019 IEEE 2nd International Conference on Electronics and Communication Engineering, ICECE 2019 (pp. 26-30). Xi'an, China: IEEE.
    DOI Scopus8

  • Preprint
    Year Citation
    2025 Nguyen, D., Ho, M. K., Ta, H., Nguyen, T. T., Chen, Q., Rav, K., . . . Phan, V. M. H. (2025). Localizing Before Answering: A Hallucination Evaluation Benchmark for
    Grounded Medical Multimodal LLMs.
    2025 Huy, T. D., Huynh, D. A., Xie, Y., Qi, Y., Chen, Q., Nguyen, P. L., . . . Phan, V. M. H. (2025). Seeing the Trees for the Forest: Rethinking Weakly-Supervised Medical
    Visual Grounding.
    2024 Xu, H. -M., Chen, Q., Wang, L., & Liu, L. (2024). Attention-driven GUI Grounding: Leveraging Pretrained Multimodal Large
    Language Models without Fine-Tuning.
    2024 Chen, Q., Zhang, B., Wang, G., & Wu, Q. (2024). Weak-eval-Strong: Evaluating and Eliciting Lateral Thinking of LLMs with
    Situation Puzzles.
    2024 Chen, Q., Zhao, R., Wang, S., Phan, V. M. H., Hengel, A. V. D., Verjans, J., . . . Wu, Q. (2024). A Survey of Medical Vision-and-Language Applications and Their
    Techniques.
    2023 Chen, Q., Pitawela, D., Zhao, C., Zhou, G., Chen, H. -T., & Wu, Q. (2023). WebVLN: Vision-and-Language Navigation on Websites.
    2021 Chen, Q., Li, Y., Qi, Y., Zhou, J., Tan, M., & Wu, Q. (2021). V2C: Visual Voice Cloning.
    2020 Cao, J., Chen, Q., Guo, J., & Shi, R. (2020). Attention-guided Context Feature Pyramid Network for Object Detection.
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