
Speaker:Title: Scalable Dynamic Graph AlgorithmsVenue: CMSA Room G10CMSA Interdisciplinary Science Seminar Speaker: Quanquan Liu, Northwestern University Title: Scalable Dynamic Graph Algorithms Abstract: The field of dynamic graph algorithms seeks to understand and compute statistics on realworld networks that undergo changes with time. Some of these networks could have up to millions of edge insertions and deletions per second. In light of these highly dynamic networks, we propose various scalable and accurate graph algorithms for a variety of problems. In this talk, I will discuss new algorithms for various graph problems in the batchdynamic model in sharedmemory architectures where updates to the graph arrive in multiple batches of one or more updates. I’ll also briefly discuss my work in other dynamic models such as distributed dynamic… 

Speaker:Title: Exploring and Exploiting the Universality Phenomena in HighDimensional Estimation and LearningVenue: HybridInterdisciplinary Science Seminar Speaker: Yue M. Lu, Harvard University Title: Exploring and Exploiting the Universality Phenomena in HighDimensional Estimation and Learning Abstract: Universality is a fascinating highdimensional phenomenon. It points to the existence of universal laws that govern the macroscopic behavior of wide classes of large and complex systems, despite their differences in microscopic details. The notion of universality originated in statistical mechanics, especially in the study of phase transitions. Similar phenomena have been observed in probability theory, dynamical systems, random matrix theory, and number theory. In this talk, I will present some recent progresses in rigorously understanding and exploiting the universality phenomena in the context of statistical estimation and learning on highdimensional data. Examples include spectral methods for highdimensional projection… 

Speaker:Title: Recent Advances on Maximum Flows and MinimumCost FlowsVenue: virtualInterdisciplinary Science Seminar Speaker: Yang P. Liu Title: Recent Advances on Maximum Flows and MinimumCost Flows Abstract: We survey recent advances on computing flows in graphs, culminating in an almost linear time algorithm for solving minimumcost flow and several other problems to high accuracy on directed graphs. Along the way, we will discuss intuitions from linear programming, graph theory, and data structures that influence these works, and the resulting natural open problems. Bio: Yang P. Liu is a finalyear graduate student at Stanford University. He is broadly interested in the efficient design of algorithms, particularly flows, convex optimization, and online algorithms. For his work, he has been awarded STOC and ITCS best student papers. 

Speaker:Title: Statistical Mechanical theory for spatiotemporal evolution of Intratumor heterogeneity in cancers: Analysis of Multiregion sequencing dataVenue: CMSA Room G10CMSA Interdisciplinary Science Seminar Speaker: Sumit Sinha, Harvard University Title: Statistical Mechanical theory for spatiotemporal evolution of Intratumor heterogeneity in cancers: Analysis of Multiregion sequencing data (https://arxiv.org/abs/2202.10595) Abstract: Variations in characteristics from one region (subpopulation) to another are commonly observed in complex systems, such as glasses and a collection of cells. Such variations are manifestations of heterogeneity, whose spatial and temporal behavior is hard to describe theoretically. In the context of cancer, intratumor heterogeneity (ITH), characterized by cells with genetic and phenotypic variability that coexist within a single tumor, is often the cause of ineffective therapy and recurrence of cancer. Nextgeneration sequencing, obtained by sampling multiple regions of a single tumor (multiregion sequencing, MSeq), has vividly demonstrated the pervasive nature of… 

Speaker: Vaidehi S. Natu, Stanford UniversityTitle: Infantsâ€™ sensorymotor cortices undergo microstructural tissue growth coupled with myelinationVenue: VirtualAbstract: The establishment of neural circuitry during early infancy is critical for developing visual, auditory, and motor functions. However, how cortical tissue develops postnatally is largely unknown. By combining T1 relaxation time from quantitative MRI and mean diffusivity (MD) from diffusion MRI, we tracked cortical tissue development in infants across three timepoints (newborn, 3 months, and 6 months). Lower T1 and MD indicate higher microstructural tissue density and more developed cortex. Our data reveal three main findings: First, primary sensorymotor areas (V1: visual, A1: auditory, S1: somatosensory, M1: motor) have lower T1 and MD at birth than higherlevel cortical areas. However, all primary areas show significant reductions in T1 and MD in the first six months of life, illustrating profound tissue growth after birth…. 

Speaker: Ioannis Petrides, Harvard UniversityTitle: Topological and geometrical aspects of spinors in insulating crystalsVenue: VirtualAbstract: Introducing internal degrees of freedom in the description of crystalline insulators has led to a myriad of theoretical and experimental advances. Of particular interest are the effects of periodic perturbations, either in time or space, as they considerably enrich the variety of electronic responses. Here, we present a semiclassical approach to transport and accumulation of general spinor degrees of freedom in adiabatically driven, weakly inhomogeneous crystals of dimensions one, two and three under external electromagnetic fields. Our approach shows that spatiotemporal modulations of the system induce a spinor current and density that is related to geometrical and topological objects — the spinorChern fluxes and numbers — defined over the higherdimensional phasespace of the system, i.e., its combined… 

Speaker:Title: The phenotype of the last universal common ancestor and the evolution of complexityVenue: VirtualInterdisciplinary Science Seminar Speaker: Fouad El Baidouri, Broad Institute Title: The phenotype of the last universal common ancestor and the evolution of complexity Abstract: A fundamental concept in evolutionary theory is the last universal common ancestor (LUCA) from which all living organisms originated. While some authors have suggested a relatively complex LUCA it is still widely assumed that LUCA must have been a very simple cell and that life has subsequently increased in complexity through time. However, while current thought does tend towards a general increase in complexity through time in Eukaryotes, there is increasing evidence that bacteria and archaea have undergone considerable genome reduction during their evolution. This raises the surprising possibility that LUCA, as the ancestor… 

Speaker: Spyros Tserkis, HarvardTitle: Entanglement and its key role in quantum informationVenue: VirtualAbstract: Entanglement is a type of correlation found in composite quantum systems, connected with various nonclassical phenomena. Currently, entanglement plays a key role in quantum information applications such as quantum computing, quantum communication, and quantum sensing. In this talk the concept of entanglement will be introduced along with various methods that have been proposed to detect and quantify it. The fundamental role of entanglement in both quantum theory and quantum technology will also be discussed. Bio: Spyros Tserkis is a postdoctoral researcher at Harvard University, working on quantum information theory. Before joining Harvard in Fall 2021, he was a postdoctoral researcher at MIT and the Australian National University. He received his PhD from the University of Queensland. 

Speaker: Hui Jiang, University of MichiganTitle: Some new algorithms in statistical genomicsVenue: VirtualAbstract: The statistical analysis of genomic data has incubated many innovations for computational method development. This talk will discuss some simple algorithms that may be useful in analyzing such data. Examples include algorithms for efficient resamplingbased hypothesis testing, minimizing the sum of truncated convex functions, and fitting equalityconstrained lasso problems. These algorithms have the potential to be used in other applications beyond statistical genomics. Bio: Hui Jiang is an Associate Professor in the Department of Biostatistics at the University of Michigan. He received his Ph.D. in Computational and Mathematical Engineering from Stanford University. Before joining the University of Michigan, he was a postdoc in the Department of Statistics and Stanford Genome Technology Center at Stanford University. He is interested in… 

Speaker:Title: Surface hopping algorithms for nonadiabatic quantum systemsVenue: CMSA Room G10Interdisciplinary Science Seminar Speaker: Jianfeng Lu, Duke UniversityTitle: Surface hopping algorithms for nonadiabatic quantum systems Abstract: Surface hopping algorithm is widely used in chemistry for mixed quantumclassical dynamics. In this talk, we will discuss some of our recent works in mathematical understanding and algorithm development for surface hopping methods. These methods are based on stochastic approximations of semiclassical pathintegral representation to the solution of multilevel Schrodinger equations; such methodology also extends to other highdimensional transport systems. 

Speaker: Jaesik Park, Pohang University of Science and TechnologyTitle: Fast Point TransformerVenue: VirtualAbstract: The recent success of neural networks enables a better interpretation of 3D point clouds, but processing a largescale 3D scene remains a challenging problem. Most current approaches divide a largescale scene into small regions and combine the local predictions together. However, this scheme inevitably involves additional stages for pre and postprocessing and may also degrade the final output due to predictions in a local perspective. This talk introduces Fast Point Transformer that consists of a new lightweight selfattention layer. Our approach encodes continuous 3D coordinates, and the voxel hashingbased architecture boosts computational efficiency. The proposed method is demonstrated with 3D semantic segmentation and 3D detection. The accuracy of our approach is competitive to the best voxelbased method, and our network… 

Speaker: WaiTong Louis Fan, Indiana UniversityTitle: Extinction and coexistence for reactiondiffusion systems on metric graphsVenue: VirtualAbstract: In spatial population genetics, it is important to understand the probability of extinction in multispecies interactions such as growing bacterial colonies, cancer tumor evolution and human migration. This is because extinction probabilities are instrumental in determining the probability of coexistence and the genealogies of populations. A key challenge is the complication due to spatial effect and different sources of stochasticity. In this talk, I will discuss about methods to compute the probability of extinction and other longtime behaviors for stochastic reactiondiffusion equations on metric graphs that flexibly parametrizes the underlying space. Based on recent joint work with Adrian GonzalezCasanova and Yifan (Johnny) Yang. 

Speaker: Fatemeh Mohammadi, Ghent UniversityTitle: The geometry of conditional independence models with hidden variablesVenue: VirtualAbstract: Conditional independence (CI) is an important tool instatistical modeling, as, for example, it gives a statistical interpretation to graphical models. In general, given a list of dependencies among random variables, it is difficult to say which constraints are implied by them. Moreover, it is important to know what constraints on the random variables are caused by hidden variables. On the other hand, such constraints are corresponding to some determinantal conditions on the tensor of joint probabilities of the observed random variables. Hence, the inference question in statistics relates to understanding the algebraic and geometric properties of determinantal varieties such as their irreducible decompositions or determining their defining equations. I will explain some recent progress that arises by uncovering… 

Speaker: Justin Solomon, MITTitle: Geometric Models for Sets of Probability MeasuresVenue: VirtualAbstract: Many statistical and computational tasks boil down to comparing probability measures expressed as density functions, clouds of data points, or generative models. In this setting, we often are unable to match individual data points but rather need to deduce relationships between entire weighted and unweighted point sets. In this talk, I will summarize our team’s recent efforts to apply geometric techniques to problems in this space, using tools from optimal transport and spectral geometry. Motivated by applications in dataset comparison, time series analysis, and robust learning, our work reveals how to apply geometric reasoning to data expressed as probability measures without sacrificing computational efficiency. 

Speaker: Yang Yuan, Tsinghua University, IIISTitle: Qianfang: a typesafe and datadriven healthcare system starting from Traditional Chinese MedicineVenue: VirtualAbstract: Although everyone talks about AI + healthcare, many people were unaware of the fact that there are two possible outcomes of the collaboration, due to the inherent dissimilarity between the two giant subjects. The first possibility is healthcareleads, and AI is for building new tools to make steps in healthcare easier, better, more effective or more accurate. The other possibility is AIleads, and therefore the protocols of healthcare can be redesigned or redefined to make sure that the whole infrastructure and pipelines are ideal for running AI algorithms. Our system Qianfang belongs to the second category. We have designed a new kind of clinic for the doctors and patients, so that it will be able to collect high… 

Speaker:Title: Intersection number and systole on hyperbolic surfacesVenue: VirtualAbstract: Let X be a compact hyperbolic surface. We can see that there is a constant C(X) such that the intersection number of the closed geodesics is \leq C(X) times the product of their lengths. Consider the optimum constant C(X). In this talk, we describe its asymptotic behavior in terms of systole, length of the shortest closed geodesic on X. 

Speaker: Peihan Miao, University of Illinois ChicagoTitle: Secure MultiParty Computation: from Theory to PracticeVenue: VirtualAbstract: Encryption is the backbone of cybersecurity. While encryption can secure data both in transit and at rest, in the new era of ubiquitous computing, modern cryptography also aims to protect data during computation. Secure multiparty computation (MPC) is a powerful technology to tackle this problem, which enables distrustful parties to jointly perform computation over their private data without revealing their data to each other. Although it is theoretically feasible and provably secure, the adoption of MPC in real industry is still very much limited as of today, the biggest obstacle of which boils down to its efficiency. My research goal is to bridge the gap between the theoretical feasibility and practical efficiency of MPC. Towards this goal,… 

Speaker: Songpeng Zu, University of California, San DiegoTitle: SIMPLEs: a singlecell RNA sequencing imputation strategy preserving gene modules and cell clusters variationVenue: VirtualAbstract: A main challenge in analyzing singlecell RNA sequencing (scRNAseq) data is to reduce technical variations yet retain cell heterogeneity. Due to low mRNAs content per cell and molecule losses during the experiment (called ‘dropout’), the gene expression matrix has a substantial amount of zero read counts. Existing imputation methods treat either each cell or each gene as independently and identically distributed, which oversimplifies the gene correlation and cell type structure. We propose a statistical modelbased approach, called SIMPLEs (SInglecell RNAseq iMPutation and celL clustErings), which iteratively identifies correlated gene modules and cell clusters and imputes dropouts customized for individual gene module and cell type. Simultaneously, it quantifies the uncertainty of imputation and cell clustering via multiple imputations. In… 

Speaker: Ravi Vakil, Stanford UniversityTitle: The space of vector bundles on spheres: algebra, geometry, topologyVenue: VirtualAbstract: Bott periodicity relates vector bundles on a topological space X to vector bundles on X “times a sphere”. I’m not a topologist, so I will try to explain an algebraic or geometric incarnation, in terms of vector bundles on the Riemann sphere. I will attempt to make the talk introductory, and (for the most part) accessible to those in all fields, at the expense of speaking informally and not getting far. This relates to recent work of Hannah Larson, as well as joint work with (separately) Larson and Jim Bryan. 

Speaker: Christopher Eur, Harvard UniversityTitle: Compactification of an embedded vector space and its combinatoricsVenue: VirtualAbstract: Matroids are combinatorial abstractions of vector spaces embedded in a coordinate space. Many fundamental questions have been open for these classical objects. We highlight some recent progress that arise from the interaction between matroid theory and algebraic geometry. Key objects involve compactifications of embedded vector spaces, and an exceptional HirzebruchRiemannRoch isomorphism between the Kring of vector bundles and the cohomology ring of stellahedral varieties. 