Climate change and population growth pose unprecedented challenges to the transportation system. Meanwhile, the proliferation of crowdsensing techniques, such as mobile phones, vehicles, social media, and cameras, has generated vast spatiotemporal data for understanding human activities and their interaction with the external environment. Effectively managing such massive, multi-structured spatiotemporal data, extracting valuable travel information, and tailoring solutions to various transportation issues are more crucial than ever. In this talk, I will first delve into my...

The deep analysis of massive mass spectrometry data has long been a critical challenge in the field of proteomics. Traditional mass spectrometry data analysis methods often exhibit low identification rates due to their inability to effectively search for peptides with unexpected digestion patterns and modifications. We developed the pFind 3 method for deep analysis of mass spectrometry data, which expands the search space by five orders of magnitude, enabling effective searches for peptides with any...

The development of artificial general intelligence (AGI) and metaverse technologies hold great potential to enhance the effectiveness of smart cities and societies. we present a cyber-physical-social approach to integrating AGI into metaverse-based smart cities and societies, with a specific focus on Social Intelligence inspired methods. The proposed approach considers the interplay between the physical environment, digital systems, social dynamics, and emerging forms of parallel intelligence. By leveraging these forms of emerged intelligence, the integration of...

With the wide popularization of low-altitude economy, low-altitude intelligent transportation has received extensive attention. In low-altitude intelligent transportation, multiple intelligent networked unmanned aerial vehicles (UAVs) and autonomous vehicles are simultaneously deployed with communication devices and multi-modal sensors. In this case, the communication capability and sensing capability coexist symbiotically, which brings more opportunities for the development of intelligent networked low-altitude transportation. 

The modern energy system breaks through the dependence on traditional fossil fuel, integrates various forms of renewable energy such as solar and wind energy, and is equipped with other infrastructures like advanced energy storage systems, sensing, and communication equipment. These elements make all these aspects of the generation, grid, load and storage organic integration and collaborative operation. However, the intermittent generation characteristic of renewable energy, the close coupling of various heterogeneous energy sources, and the...

The transportation system is often disrupted by natural hazards and human-made accidents, which cause severe consequences to people’s mobility, the local economy, and the society in general. Particularly, the more and more frequent and severe impacts of climate change are posing great challenges and will continue to impact the globe for many years. Building resilient multimodal interconnected transportation systems under such attacks are critical for the safe and efficient movement of people and goods. However,...

The End-to-End (E2E) architecture has emerged in recent years as a novel and promising paradigm for autonomous driving. The robustness and safety issue in complex real-world environments pose significant challenge to the development of E2E autonomous driving system. The quantitative measure of confidence of intermediate features in E2E perception and prediction is missing, and the propagation of uncertainties among the modules of E2E framework requires explicit analysis. In addition, learning-based control techniques (e,g, Reinforcement Learning)...

This research seminar introduces human cognitive modeling with its applications in intelligent transportation systems (ITS) design. Human cognitive modeling is a growing and challenging area in human factors and cognitive systems engineering. It builds computational models based on the fundamental mechanisms of human cognition and human-system interaction, employs both mathematical and discrete event simulation methods in industrial engineering, and predicts human performance and workload in real-world transportation systems. It can be used to design, improve,...

The Hippo pathway has emerged as an evolutionarily conserved signaling network that regulates cell proliferation, tissue homeostasis, and tissue regeneration. We show that the tumor suppressor Merlin, an upstream regulator of the Hippo pathway, forms solid-like condensates that activate Hippo signaling in Drosophila tissues. Merlin condensation required phosphatidylinositol-4-phosphate (PI4P)-mediated plasma membrane targeting, and was antagonistically controlled by Pez and cytoskeletal tension through plasma membrane PI4P regulation. The solid-like material properties of Merlin condensates are essential...