Speaker: ZHANG JunjieVenue: Room 319/321, ZIBS Building, Haining Campus

Speaker: Minghua ChenVenue: 418, Teaching Building No.4, Yuquan CampusAbstract: The Optimal Power Flow (OPF) problem aims to minimize power generation costs while meeting grid demand and adhering to physical constraints, serving as a pivotal challenge in power system operations, its applications span electricity markets, reliability assessments, and grid modernization for carbon neutrality, with global annual operational costs reaching billions of USD. Traditional iterative solvers struggle with large-scale OPF due to its non-convex and NP hard nature.Recent advances in machine learning (ML)have accelerated OPF solutions by orders of magnitude through techniques like constraint classification, warm-start solutions, and direct load-to-solution mapping, while maintaining accuracy.This tutorial explores cutting-edge ML applications in OPF, including active constraint identification, solver strategy learning, and cross-domain optimization generalization.Future directions for enhancing computational efficiency and robustness under increasing renewable energy uncertainty are also discussed.

Venue: Lecture Hall, ZJU Museum of Art and Archaeology, Zijingang CampusSpeaker: Alba Di LietoProfessor Di Lieto served as executive architect for the City Museums of Verona, Italy, until 2022, where she was responsible for exhibition design and the Carlo Scarpa Archive. She has also collaborated on the restoration, conservation, and design of Verona’s museums, including the Archaeological Museum at the Roman Theater, the Towers of Castelvecchio, and the new wing and the garden of the Frescoes Museum “G.B. Cavalcaselle at Juliet's Tomb. Around the 1960s, the Venetian architect, Carlo Scarpa (1906-1978) carried out an innovative critical restoration of the monument, creating a spectacular exhibition design integrated and in continuity the museum's fine art collection. His museographical approach has since inspired contemporary artists and architects such as the American Peter Eisenmann, the German Herbert Hamak, the Polish Igor Mitoraj, and the Italians Maria Morganti and Giorgio Vigna. This lecture will be based on Professor Di Lieto`s direct experience during her service at the City Museums of Verona, Italy. Since the Eighties, she has collaborated with artists and architects on numerous exhibitions, many of which have been realized inside the Castelvecchio Museum, as well as in its garden. The talk titled “The Continuity of Exhibit-Design in the Castelvecchio Museum, (or in the City Museums) in Verona-Italy” explores the results of these experimental projects. Each site-specific art installation, despite its unique character, is conceived through the lens of Scarpa's design language, achieving a new balance between space, objects and innovative display solutions.

Speaker: YU JunVenue: Haina Court 2-203, Zijingang CampusAbstract: Given a semisimple real linear group, a zonal spherical function is matrix coefficient associated to the unique spherical vector with value 1 at identity element in a unitary spherical principal series, which are important object in representation theory and harminic analysis. Each zonal spherical function is a positive function. Hence, its Fourier transform along a maximal split torus is everywhere non-negative by a classical theorem of Bochner. In this talk we report a result in a recent joint work: the Fourier transform along a maximal split torus of any zonal spherical function takes positive value everywhere.

Speaker: CAI ShiqingVenue: 2A-203-3, ZJE Building, Haining CampusAbstract: Dr. Shi-Qing Cai obtained his PhDdegree from Shanghai Institute of Plant Physiology & Ecology, Chinese Academy of Sciences, and did his postdoctoral training at Robert Wood Johnson Medical School, Rutgers University, His postdoctoral work mainly focused on the oxidative regulation of potassium channels in the aging nervous system. He joined Institute of Neuroscience, Chinese Academy of Sciences, in 2009. Currently, his study aims to understand 1)the neural basis of healthy aging;2)the mechanism underlying ion channel biogenesis including folding, assembly and trafficking.

Speaker: Dr. Bo LuVenue: LTNA 226, Haining CampusAbstract: With the rapid development of surgical robot technology in recent years, specialized robotic platforms are gradually being adopted across various hospital departments.To enhance the efficiency of online diagnosis and treatment with surgical robots and reduce the clinical workload of surgeons, intelligent autonomous surgical robots have become a prominent research focus. This talk will address technologies such as surgical intelligent perception, autonomous navigation, skill learning, and autonomous manipulation. Focusing on application scenarios like laparoscopic surgery, gastrointestinal surgery, and panvascular surgery, it will explore key technologies including autonomous suturing and knot-tying, endoscopic autonomous control, intelligent surgical navigation, embodied learning, and robotic system generation. The report will also introduce specific applications of robotic intelligence in surgical subtasks and discuss future trends in AI + robotics technology.

Speaker: Thomas B. KornbergVenue: Report Hall 205, Comprehensive Building of Medical College, Zijingang CampusAbstract: Development creates a vast array of forms and patterns with elegant economy, using a small vocabulary of signaling proteins (BMPs, FGFS EGFs, Wnts, and Hhs) in similar ways to pattern many different tissues. Specialized filopodia called cytonemes transport these signaling proteins between cells, mediating cell-cell exchanges at contacts that are functionally similar to neuronal synapses. The roles and physical attributes of cytonemes have fascinating implications for the way sianaling proteins disperse across tissues to elicit specific responses in both normal development and disease contexts.

Speaker: LIU HuimeiVenue: Room 219/221, ZIBS Building, Haining Campus

Speaker: XU YongjiaVenue: LTN-A 301, Haining CampusAbstract: Intelligent desian and structural health monitoring of civil engineering structures are critical research fields atpresent. This presentation reports the recent progress in solving problems such as low utlization efticiency of existing design data and unstable quality in structural design by introducing generative intelligent design methods.Leveraging advanced generative Al algorithms the proposed methodologies extract key features and patterns from existing design data to acquire engineering structural design capabilities, fulfilling new design tasks efficiently while maintaining stable design quality. Additionallv, the civil enaineering tield has beaun transitioning from aconstruction-tocusedapproach toward emphasizino balanced construction and maintenance.To ensure the satety and functionality of existing structures, structural health monitoring has increasinaly gained importance. This presentation, therefore, introduces a Bidirectional Granhics-Based Diaital Twin (Bi-GBDT) structural health monitorna tramework, Supported by various technologies such as digtal twin, virtual environments, deep learning, and finite element analyss, the Bi-GBDT tramework integrates the data acquisition, external damage identification, and intrinsic damage evaluation to achieve accurate and efficient structural condition assessments.