快速定量容积成像在研究三维复杂系统中具有重要意义，包括细胞生物学、肿瘤、神经科学研究等。光片显微镜和光学投影断层扫描是实现快速定量容积成像的两种典型方法，但这两种技术都需要荧光标记才能识别复杂系统的三维化学成分信息。拉曼光谱解决了荧光标记带来的问题，可无标记识别和观察复杂系统中的化学成分。基于拉曼散射效应和投影断层成像技术的发展，将投影断层成像策略与拉曼光谱技术相结合，可实现大体积复杂系统的高速、...

人工神经网络已对社会发展产生了巨大变革，也同时对算力、能耗和计算效率等问题带来了巨大挑战。物理神经网络充分利用了物理体系的优异特性来实现人工神经网络的训练和计算，可潜在突破传统计算机的限制，且大幅提高计算效率。在低维尺度下，磁性材料不仅具有记忆和存储功能，还具备强的热涨落、丰富的磁畴态和动力学过程，展现出很强的可塑性、随机性、非线性和振荡性等特征，是实现物理神经网络的极佳选择。本报告将介绍课题组利...

In the last decade, deep learning has played an indispensable role in the human world. At the core, general matrix multiplication (GEMM) has prompted extensive optimization efforts on conventional binary encoding, to democratize the transformative capabilities. However, binary computing does not offer optimal efficiency. To yield unprecedented hardware efficiency in new applications, my research l...

This talk explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agents. To address the challenges of achieving autonomous cooperation, we propose a novel communicative agent framework named CAMEL. We showcase how role-playing can be used to generate conversational data for studying the behaviors and capabilities of a society of agents. In p...

报告人简介： Lakshminarayana Polavarapu is the principal investigator at the Centro De Investigaciones Biomédicas (CINBIO), University of Vigo, Spain. He obtained PhD in 2011 from the National University of Singapore and received the Alexander von Humboldt postdoctoral fellowship in 2015 at the Ludwig-Maximilians-University of Munich (Germany). He Joined University of Vigo, Spain in 2020. His gro...

By 2030, up to 95% of new vehicles sold globally are expected to be connected, increasing vulnerability to hacking targeting critical functions like steering and braking. This lecture examines modern vehicle architecture, security challenges, hacking incidents with demonstrations, and cryptographic countermeasures, including symmetric/asymmetric encryption and hashing. It also explores security te...