Speaker:Hiroyuki Osada Venue:Room 256 Pharmaceutical Building

Let $(\lambda_f(n))_{n\geq 1}$ be the Fourier coefficients of a Hecke--Maass $f$ on $GL_2$. The classical Rankin--Selberg problem asks for a better error term in the asymptotic formula for $\sum_{n\leq X} \lambda_f(n)^2$, as $X\to \infty$.

The development of efficient methods for long-range systems plays important role in all-atom simulations of biomolecules and drug design. We present a random-batch Ewald (RBE) and a random-batch sum-of-Gaussians (SOG) methods for molecular dynamics simulations of particle systems with long-range Coulomb interactions.

Pan-Wei's example of Ricci limit space is isometric to half of the Grushin plane, a classical example in sub-Riemannian geometry. Inspired by this connection, we construct the Grushin hemisphere as a Ricci limit space with curvature >=1.

Recently, triangle configuration-based bivariate simplex splines (referred to as TCB-spline) have been introduced to the geometric computing community. TCB-splines retain many attractive theoretic properties of classical B-splines, such as the partition of unity, local support, polynomial reproduction, and automatic inbuilt high-order smoothness.

Functional data analysis has emerged as a powerful tool in response to the ever increasing resources and efforts devoted to collecting information about response curves or anything varying over a continuum.

Using firm-level earnings forecasts and managerial guidance data, we construct guidance surprises for analysts, i.e., differences between managerial guidance and analysts’ initial forecasts.

This lecture highlights using images to illustrate and organize research ideas, and using graphics to demonstrate key points in academic research, and will introduce related softwares (Corel and Autodesk).

Organized by the Zhejiang University , this seminar invites Alan Plattus, professor of Yale School of Architecture, to introduce the Advanced Studio at Yale as a teaching and research methodology, as well as share the past achievements and experiences of Yale School of Architecture's China studio.

Many models in machine learning and PDE-based inverse problems exhibit intrinsic spectral properties, which have been used to explain the generalization capacity and the ill-posedness of such problems. In this talk, we discuss weighted training for computational learning and inversion with noisy data. The highlight of the proposed framework is that we allow weighting in both the parameter space and the data space. The weighting scheme encodes both a priori knowledge of the object to be learned a

Jointly Hosted by the Sydney School of Pharmacy (USYD) and College of Pharmacy (ZJU), participated by University of Macau and Sun Yat-sen University, this workshop is to encourage constructive dialogues and explore collaborations to improve clinical outcomes in human eye diseases and cancers.

Dr. Lifan GUAN (Westlake University)

XIA Chao, Professor and Doctoral Director of Xiamen University, Fujian Province Minjiang Scholar.

Jiadong Gu, University of North Carolina

ZHOU Wenzhuo, postdoc fellow, the University of California Irvine

DAI Min, Chair Professor in Applied Statistics and Financial Mathematics, Department of Applied Mathematics, The Hong Kong Polytechnic University

BAO Chenglong, an Assistant Professor at Mathematical Sciences Center, Tsinghua University.

Prof. YANG Liu, University of Cambridge

Dr. Liu SHI is a Senior Researcher Scientist at the Department of Psychiatry at the University of Oxford. Her research focuses on using machine learning and artificial intelligence to analyze multi-omics data, with the aim to discover novel biomarkers and drug targets for Alzheimer's disease. In addition to research, she is enthusiastic about translating fundamental research into reality to ensure people benefit from science.

Prof. WU Jian, Chief Physician, School of Medicine, Zhejiang University