Publications (35)
OmniFysics: Towards Physical Intelligence Evolution via Omni-Modal Signal Processing and Network Optimization
Minghao Han, Dingkang Yang, Yue Jiang +2
The autonomous evolution of networked AI systems relies heavily on robust environmental perception. However, physical understanding remains brittle in current models because key ph…
Deep Neural Koopman Operator-based Economic Model Predictive Control of Shipboard Carbon Capture System
Minghao Han, Xunyuan Yin
Shipboard carbon capture is a promising solution to help reduce carbon emissions in international shipping. In this work, we propose a data-driven dynamic modeling and economic pre…
Fusing Pixels and Genes: Spatially-Aware Learning in Computational Pathology
Minghao Han, Dingkang Yang, Linhao Qu +5
Recent years have witnessed remarkable progress in multimodal learning within computational pathology. Existing models primarily rely on vision and language modalities; however, la…
Causal Context Adjustment Loss for Learned Image Compression
Minghao Han, Shiyin Jiang, Shengxi Li +4
In recent years, learned image compression (LIC) technologies have surpassed conventional methods notably in terms of rate-distortion (RD) performance. Most present learned techniq…
Reinforcement Learning for Control with Probabilistic Stability Guarantee: A Finite-Sample Approach
Minghao Han, Lixian Zhang, Chenliang Liu +3
This paper presents a novel approach to reinforcement learning (RL) for control systems that provides probabilistic stability guarantees using finite data. Leveraging Lyapunov's me…
FeatureBench: Benchmarking Agentic Coding for Complex Feature Development
Qixing Zhou, Jiacheng Zhang, Haiyang Wang +9
Agents powered by large language models (LLMs) are increasingly adopted in the software industry, contributing code as collaborators or even autonomous developers. As their presenc…
Machine learning-based hybrid dynamic modeling and economic predictive control of carbon capture process for ship decarbonization
Xuewen Zhang, Kuniadi Wandy Huang, Dat-Nguyen Vo +3
Implementing carbon capture technology on-board ships holds promise as a solution to facilitate the reduction of carbon intensity in international shipping, as mandated by the Inte…
Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling
Mingxue Yan, Minghao Han, Adrian Wing-Keung Law +1
In this paper, we propose a physics-informed learning-based Koopman modeling approach and present a Koopman-based self-tuning moving horizon estimation design for a class of nonlin…
Neural Stereo Video Compression with Hybrid Disparity Compensation
Shiyin Jiang, Zhenghao Chen, Minghao Han +1
Disparity compensation represents the primary strategy in stereo video compression (SVC) for exploiting cross-view redundancy. These mechanisms can be broadly categorized into two…
Reinforcement Learning Control of Constrained Dynamic Systems with Uniformly Ultimate Boundedness Stability Guarantee
Minghao Han, Yuan Tian, Lixian Zhang +2
Reinforcement learning (RL) is promising for complicated stochastic nonlinear control problems. Without using a mathematical model, an optimal controller can be learned from data e…
VGAT: A Cancer Survival Analysis Framework Transitioning from Generative Visual Question Answering to Genomic Reconstruction
Zizhi Chen, Minghao Han, Xukun Zhang +4
Multimodal learning combining pathology images and genomic sequences enhances cancer survival analysis but faces clinical implementation barriers due to limited access to genomic s…
Multi-Scale Heterogeneity-Aware Hypergraph Representation for Histopathology Whole Slide Images
Minghao Han, Xukun Zhang, Dingkang Yang +4
Survival prediction is a complex ordinal regression task that aims to predict the survival coefficient ranking among a cohort of patients, typically achieved by analyzing patients'…
Forging a Dynamic Memory: Retrieval-Guided Continual Learning for Generalist Medical Foundation Models
Zizhi Chen, Yizhen Gao, Minghao Han +4
Multimodal biomedical Vision-Language Models (VLMs) exhibit immense potential in the field of Continual Learning (CL). However, they confront a core dilemma: how to preserve fine-g…
Differentiable Vector Quantization for Rate-Distortion Optimization of Generative Image Compression
Shiyin Jiang, Wei Long, Minghao Han +3
The rapid growth of visual data under stringent storage and bandwidth constraints makes extremely low-bitrate image compression increasingly important. While Vector Quantization (V…
FysicsWorld: A Unified Full-Modality Benchmark for Any-to-Any Understanding, Generation, and Reasoning
Yue Jiang, Dingkang Yang, Minghao Han +6
Despite rapid progress in multimodal large language models (MLLMs) and emerging omni-modal architectures, current benchmarks remain limited in scope and integration, suffering from…
MSCPT: Few-shot Whole Slide Image Classification with Multi-scale and Context-focused Prompt Tuning
Minghao Han, Linhao Qu, Dingkang Yang +3
Multiple instance learning (MIL) has become a standard paradigm for the weakly supervised classification of whole slide images (WSIs). However, this paradigm relies on using a larg…
Towards Unified Molecule-Enhanced Pathology Image Representation Learning via Integrating Spatial Transcriptomics
Minghao Han, Dingkang Yang, Jiabei Cheng +4
Recent advancements in multimodal pre-training models have significantly advanced computational pathology. However, current approaches predominantly rely on visual-language models,…
Beyond Pixel Simulation: Pathology Image Generation via Diagnostic Semantic Tokens and Prototype Control
Minghao Han, Yichen Liu, Yizhou Liu +5
In computational pathology, understanding and generation have evolved along disparate paths: advanced understanding models already exhibit diagnostic-level competence, whereas gene…
PersonaAnimator: Personalized Motion Transfer from Unconstrained Videos
Ziyun Qian, Runyu Xiao, Shuyuan Tu +7
Recent advances in motion generation show remarkable progress. However, several limitations remain: (1) Existing pose-guided character motion transfer methods merely replicate moti…
FasterPy: An LLM-based Code Execution Efficiency Optimization Framework
Yue Wu, Minghao Han, Ruiyin Li +5
Code often suffers from performance bugs. These bugs necessitate the research and practice of code optimization. Traditional rule-based methods rely on manually designing and maint…
Generative Image Compression by Estimating Gradients of the Rate-variable Feature Distribution
Minghao Han, Weiyi You, Jinhua Zhang +3
While learned image compression (LIC) focuses on efficient data transmission, generative image compression (GIC) extends this framework by integrating generative modeling to produc…
Lyapunov-based reinforcement learning for distributed control with stability guarantee
Jingshi Yao, Minghao Han, Xunyuan Yin
In this paper, we propose a Lyapunov-based reinforcement learning method for distributed control of nonlinear systems comprising interacting subsystems with guaranteed closed-loop…
Reduced-order Koopman modeling and predictive control of nonlinear processes
Xuewen Zhang, Minghao Han, Xunyuan Yin
In this paper, we propose an efficient data-driven predictive control approach for general nonlinear processes based on a reduced-order Koopman operator. A Kalman-based sparse iden…
A Prescriptive Dirichlet Power Allocation Policy with Deep Reinforcement Learning
Yuan Tian, Minghao Han, Chetan Kulkarni +1
Prescribing optimal operation based on the condition of the system and, thereby, potentially prolonging the remaining useful lifetime has a large potential for actively managing th…
Adaptive Reinforcement for Open-ended Medical Reasoning via Semantic-Guided Reward Collapse Mitigation
Yizhou Liu, Dingkang Yang, Zizhi Chen +5
Reinforcement learning (RL) with rule-based reward functions has recently shown great promise in enhancing the reasoning depth and generalization ability of vision-language models…
Actor-Critic Reinforcement Learning for Control with Stability Guarantee
Minghao Han, Lixian Zhang, Jun Wang +1
Reinforcement Learning (RL) and its integration with deep learning have achieved impressive performance in various robotic control tasks, ranging from motion planning and navigatio…
MAKO: Meta-Adaptive Koopman Operators for Learning-based Model Predictive Control of Parametrically Uncertain Nonlinear Systems
Minghao Han, Kiwan Wong, Adrian Wing-Keung Law +1
In this work, we propose a meta-learning-based Koopman modeling and predictive control approach for nonlinear systems with parametric uncertainties. An adaptive deep meta-learning-…
Modeling and Control of an Omnidirectional Micro Aerial Vehicle Equipped with a Soft Robotic Arm
Róbert Szász, Mike Allenspach, Minghao Han +2
Flying manipulators are aerial drones with attached rigid-bodied robotic arms and belong to the latest and most actively developed research areas in robotics. The rigid nature of t…
MVAR: Visual Autoregressive Modeling with Scale and Spatial Markovian Conditioning
Jinhua Zhang, Wei Long, Minghao Han +2
Essential to visual generation is efficient modeling of visual data priors. Conventional next-token prediction methods define the process as learning the conditional probability di…
VLM-based Prompts as the Optimal Assistant for Unpaired Histopathology Virtual Staining
Zizhi Chen, Xinyu Zhang, Minghao Han +6
In histopathology, tissue sections are typically stained using common H&E staining or special stains (MAS, PAS, PASM, etc.) to clearly visualize specific tissue structures. The rap…
Machine learning-based input-augmented Koopman modeling and predictive control of nonlinear processes
Zhaoyang Li, Minghao Han, Dat-Nguyen Vo +1
Koopman-based modeling and model predictive control have been a promising alternative for optimal control of nonlinear processes. Good Koopman modeling performance significantly de…
Efficient Economic Model Predictive Control of Water Treatment Process with Learning-based Koopman Operator
Minghao Han, Jingshi Yao, Adrian Wing-Keung Law +1
Used water treatment plays a pivotal role in advancing environmental sustainability. Economic model predictive control holds the promise of enhancing the overall operational perfor…
Model-free Reinforcement Learning with Robust Stability Guarantee
Minghao Han, Yuan Tian, Lixian Zhang +2
Reinforcement learning is showing great potentials in robotics applications, including autonomous driving, robot manipulation and locomotion. However, with complex uncertainties in…
SatireDecoder: Visual Cascaded Decoupling for Enhancing Satirical Image Comprehension
Yue Jiang, Haiwei Xue, Minghao Han +5
Satire, a form of artistic expression combining humor with implicit critique, holds significant social value by illuminating societal issues. Despite its cultural and societal sign…
Economic zone data-enabled predictive control for connected open water systems
Xiaoqiao Chen, Xuewen Zhang, Minghao Han +2
The real-time operation of open water systems is essential for ensuring operational safety, satisfying operational requirements, and optimizing energy usage. However, existing rule…