Tianyang Wang, Ph.D.

Assistant Professor
Department of Computer Science
The University of Alabama at Birmingham
Office: University Hall 4157
Phone: 205-934-0650
Email: tw2@uab.edu or toseattle@siu.edu

About me

I join the University of Alabama at Birmingham in August 2023, serving the department of computer science as a tenure-track assistant professor. I earned my Ph.D. degree in computer science from Southern Illinois University, and my master (computer science) and bachelor (software engineering) degrees from Jilin University, China. I was a visiting researcher at Baidu Research in 2019. I have been working as a remote researcher in the XuLab at Carnegie Mellon University (CMU) since 2020.

Ph.D. RA Positions: I am actively hiring Ph.D. students to join my group as research assistants. All the positions will be fully funded. The students will have a chance to be recommended to do a research internship at CMU, Oak Ridge National Laboratory, or Amazon during summer. Interested students are encouraged to email your CV to: tw2@uab.edu .

Research Collaborations: If you are interested in a research collaboration, please do not hesitate to contact me via: toseattle 'AT' siu 'DOT' edu. We are always open to various fashions of collaborations.


Research

My research interests include AI, machine (deep) learning, computer vision, and broad data science. I am especially interested in applying AI and machine learning for interdisciplinary research, such as biomedical informatics. Our current works mainly focus on multi-modal large foundation models and their parameter-efficient fine-tuning, deep active learning, deep transfer learning, and their applications in downstream challenges. Please refer to the publications for details.

Publications

[arXiv] Describe Anything in Medical Images, Link, 2025.

[arXiv] MagicID: Hybrid Preference Optimization for ID-Consistent and Dynamic-Preserved Video Customization, Link, 2025.

[arXiv] CAD-VAE: Leveraging Correlation-Aware Latents for Comprehensive Fair Disentanglement, Link, 2025.

[arXiv] 4D Multimodal Co-attention Fusion Network with Latent Contrastive Alignment for Alzheimer's Diagnosis, Link, 2025.

[IJCAI] Faster Annotation for Elevation-Guided Flood Extent Mapping by Consistency-Enhanced Active Learning, Link will be available after the conference in Aug, 2025.

[CVPRW] Visual Variational Autoencoder Prompt Tuning, Link, 2025.

[CVPRW] Multimodal Generalized Category Discovery, Link, 2025.

[MDPI Remote Sensing] Visual Prompt Learning of Foundation Models for Post-Disaster Damage, Link, 2025.

[ICASSP] TD-RD: A Top-Down Benchmark with Real-Time Framework for Road Damage Detection, Link, 2025.

[MICCAI] CryoSAM: Training-free CryoET Tomogram Segmentation with Foundation Models, Link, 2024.

[AAAI] Deep Active Learning with Noise Stability, Link, 2024.

[ICONIP] HGTDP-DTA: Hybrid Graph-Transformer with Dynamic Prompt for Drug-Target Binding Affinity Prediction, Link, 2024.

[ICTAI] Multi-dimension Transformer with Attention-based Filtering for Medical Image Segmentation, Link, 2024.

[IJCIS] MocFormer: A Two-Stage Pre-training-Driven Transformer for Drug–Target Interactions Prediction, Link, 2024.

[arXiv] Enhancing Weakly Supervised 3D Medical Image Segmentation through Probabilistic-aware Learning, Link, 2024.

[arXiv] Deep Active Learning with Manifold-preserving Trajectory Sampling, Link, 2024.

[arXiv] DenseMP: Unsupervised Dense Pre-training for Few-shot Medical Image Segmentation, Link, 2024.

[arXiv] Cycle-YOLO: An Efficient and Robust Framework for Pavement Damage Detection, Link, 2024.

[arXiv] LaDTalk: Latent Denoising for Synthesizing Talking Head Videos with High Frequency Details, Link, 2024.

[arXiv] Uncertainty-Aware Adapter: Adapting Segment Anything Model (SAM) for Ambiguous Medical Image Segmentation, Link, 2024.

[ICCV] Towards Inadequately Pre-trained Models in Transfer Learning, Link, 2023.

[ECML-PKDD] Overcoming Catastrophic Forgetting for Fine-tuning Pre-trained GANs, Link, 2023.

[ICASSP] Improving BERT Fine-tuning via Stabilizing Cross-layer Mutual Information, Link, 2023.

[TNNLS] Temporal Output Discrepancy for Loss Estimation-based Active Learning, Link, 2022.

[AAAI] Boosting Active Learning via Improving Test Performance, Link, 2022.

[ICIP] Deep Active Learning for Cryo-Electron Tomography Classification, Link, 2022.

[ICASSP] Parameter-Free Style Projection for Arbitrary Style Transfer, Link, 2022.

[IEEE Access] Deep-Precognitive Diagnosis: Preventing Future Pandemics by Novel Disease Detection with Biologically-inspired Conv-Fuzzy Network, Link, 2022.

[IEEE Access] Prolificacy Assessment of Spermatozoan via State-of-the-Art Deep Learning Frameworks, Link, 2022.

[ICCV] Semi-Supervised Active learning with temporal Output Discrepancy, Link, 2021.

[VISAPP] Single Image Super-resolution using Vectorization and Texture Synthesis, Link, 2021.

[CVIU] A Comparison of Methods for 3D Scene Shape Retrieval, Link, 2020.

[ICTAI] I2S2: Image-to-Scene Sketch Translation Using Conditional Input and Adversarial Networks, Link, 2020.

[Molecular Carcinogenesis] Protective Role of Histone Deacetylase 4 from Ultraviolet Radiation-Induced DNA Lesions, Link, 2020.

[IEEE MIPR] Semantic Tree-Based 3D Scene Model Recognition, Link, 2020.

[WACV] Instance-based Deep Transfer Learning, Link, 2019.

[ICIP] Temporal Interframe Pattern Analysis for Static and Dynamic Hand Gesture Recognition, Link, 2019.

[ICTAI] Rethink Gaussian Denoising Prior for Real-World Image Denoising, Link, 2019.

[3DOR] SHREC’19 Track: Extended 2D Scene Image-Based 3D Scene Retrieval, Link, 2019.

[3DOR] SHREC’19 Track: Extended 2D Scene Sketch-Based 3D Scene Retrieval, Link, 2019.

[ICTAI] Data Dropout: Optimizing Training Data for Convolutional Neural Networks, Link, 2018.

[ICTAI] Dilated Deep Residual Network for Image Denoising, Link, 2017.

[ICONIP] An ELU Network with Total Variation for Image Denoising, Link, 2017.

[ICDIP] A Visual Perceptual Descriptor with Depth Feature for Image Retrieval, Link, 2017.

[arXiv] Imbalanced Malware Images Classification: a CNN based Approach, Link, 2017.


Softwares

T. Wang, X. Li, P. Yang, G. Hu, X. Zeng, S. Huang, C. Xu, and M. Xu. AL-GradNorm.

S. Huang, T. Wang, H. Xiong, J. Huan, and D. Dou. TOD.

S. Huang, H. Xiong, T. Wang, B. Wen, Q. Wang, Z. Chen, J. Huan, and D. Dou. Stylepro_Artistic.


Services

I regularly serve academic journals and conferences as a reviewer. The venues are listed as follows.
Journal
  • IEEE Transactions on Multimedia (TMM)
  • Elsevier Journal of Pattern Recognition (PR)
  • Elsevier Journal of Computer Vision and Image Understanding (CVIU)
  • Elsevier Journal of Neurocomputing
  • Elsevier Journal of Knowledge-Based Systems (KBS)
  • Elsevier Journal of Computer-Aided Design (CAD)
  • International Journal on Artificial Intelligence Tools (IJAIT)
Conference
  • IEEE International Conference on Computer Vision (ICCV)
  • IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • The European Conference on Computer Vision (ECCV)
  • IEEE Winter Conference on Applications of Computer Vision (WACV)
  • IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • The European Conference on Artificial Intelligence (ECAI)
  • The British Machine Vision Conference (BMVC)

Ph.D. students

Xi Xiao, Spring 2024 - Current. Xi interns at Oak Ridge National Laboratory during Summer 2025.

Teaching

At the University of Alabama at Birmingham, I teach the following courses.
  • CS 420/520 Software Engineering, Fall.
  • CS 667/767 Machine Learning, Spring.
  • CS 665/765 Deep Learning, Fall.
Prior to joining the University of Alabama at Birmingham, I taught the following courses at the Austin Peay State University.
  • CSCI 1010 Introduction to Programming I
  • CSCI 2700 Data Communications and Networking
  • CSCI 3000 Data Modeling
  • CSCI 3400 Computer Organization I
  • CSCI 4450 Introduction to Artificial Intelligence
  • CSCI 5010 Database Management Concepts
  • CSCI 5015 Data Science in Python
  • CSCI 5040 Big Data Modeling and Management