Researchers who combine machine learning and economics are studying the social impact of algorithms that determine payouts on digital marketplaces. In a recently published study, the team highlights the structural imbalance in digital labor markets and provides a blueprint for fairer market with better working conditions for gig workers.

The research team of Professor Kyoungjae Lee of the Department of Statistics at Sungkyunkwan University, through joint research with Professor Won Chang of Seoul National University and Professor Xuan Cao of the University of Cincinnati, developed Bayesian inference for the hidden dependence structures of multi-group high-dimensional data.

A new study outlines a comprehensive framework leveraging AI and big data to combat illegal plant trade, addressing global biodiversity threats with technological innovation.

Researchers have developed an ultrathin yet ultrastrong hydrogel membrane that enables robust and conformal integration between electronic devices and biological tissues. The ~10 μm-thick material combines high strength, exceptional toughness, and tissue-like softness through a biomimetic microfibrillar network design. It supports multimodal sensing and stimulation while maintaining stable contact with complex 3D tissues, offering new opportunities for wearable and implantable bioelectronics.

With the development of quantum chips, quantum communication is becoming essential for quantum computing and quantum networks. Flying Qubits, quantum information carried by photons, play a vital role in transferring data between nodes. Prof. Guofeng ZHANG, Professor of Department of Applied Mathematics of The Hong Kong Polytechnic University is dedicated to developing precise control methods for flying qubits, aiming to significantly improve the reliability and fidelity of quantum information transfer in future technologies.

When robots perform complex tasks, the pose accuracy of the end-effector is critical. However, errors from individual joints tend to accumulate along the kinematic chain, making it challenging to guarantee high pose precision at the end-effector. To address this issue, this study proposes a virtual-constraints-based end-effector pose compensator (VEPC). The method treats the actual angles of specific joints as known inputs and automatically adjusts the remaining joint angles in real time, effectively eliminating the pose errors of the end-effector caused by the joints. Experimental results demonstrate that the method can reduce the maximum end-effector position error by over 75%. Moreover, the method requires no additional sensors, offering low cost and high compatibility.