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Data Science Seminar

The Data Science Seminar is evolved from the former Statistical Machine Learning Seminar which covered topics in statistical theory that was important for machine learning research as well as development and applications of machine learning techniques in interdisciplinary research. The scope of the Data Science Seminar has been broadened to facilitate dialogue among different communities in the data science circle.

It is listed as course MATH 568.

Location: Whitney 100E (See the directions to the department)
Time: Tuesday 12:00 pm –1:00 pm
Organizer: Guifang Fu

See also the Statistics Seminar.
An internal Machine Learning Working Group meeting is held when no seminar talk is scheduled.
See Previous talks in the Data Science Seminar and even earlier talks.

Fall 2021

  • Sep. 21, 2021
    Speaker: Dr. Haoda Fu (Eli Lilly and Company)
    Topic: Our Recent Development on Cost Constraint Machine Learning Models.
    Abstract
  • Sep. 28, 2021
    Speaker: Dr. Eric F. Lock (University of Minnesota)
    Topic: Bidimensional Linked Matrix Decomposition for Pan-Omics Pan-Cancer Analysis.
    Abstract
  • Oct. 19, 2021
    Speaker: Dr. Damla Senturk (UCLA)
    Topic: Multilevel Modeling of Spatially Nested Functional Data: Spatiotemporal Patterns of Hospitalization Rates in the U.S. Dialysis Population.
    Abstract
  • Oct. 26, 2021
    Speaker: Dr. Giles Hooker (UC Berkeley)
    Topic: There is No Free Variable Importance: Traps in Interpreting Black Box Functions.
    Abstract
  • Nov. 2, 2021
    Speaker: Dr. Yuanjia Wang (Columbia University)
    Topic: Machine Learning Approaches for Optimizing Treatment Strategies for Mental Disorders.
    Abstract
  • Nov. 9, 2021
    Speaker: Dr. Megan Johnson (Internal)
    Topic: The Interconnectivity Vector and the Betti Sequence: Finite-Dimensional Vector Representations of Persistent Homology.
    Abstract
  • Nov. 16, 2021
    Speaker: Dr. Cen Wu (Kansas State University)
    Topic: Robust Bayesian variable selection for gene-environment interactions.
    Abstract
  • Nov. 30, 2021
    Speaker: Dr. Antonio Linero (University of Texas at Austin)
    Topic: Bayesian Decision Tree Ensembling Strategies for Nonparametric Problems.
    Abstract
  • Dec. 7, 2021
    Speaker: Dr. Annie Qu (University of California Irvine)
    Topic: Correlation Tensor Decomposition and Its Application in Spatial Imaging Data.
    Abstract



Spring 2021

  • Mar. 02, 2021
    Speaker: Brian Franczak (MacEwan University)
    Topic: On using mixtures of shifted asymmetric Laplace distributions for model-based classification.
    Abstract
  • Mar. 23, 2021
    Speaker: Adam Ciarleglio (The George Washington University)
    Topic: Multiple imputation in functional regression with applications to EEG data in a depression study.
    Abstract
  • March 30, 2021
    Speaker: Wenshu Dai (Binghamton University)
    Topic: Finite Mixtures of Regression Models and Finite Mixtures of Regression Models with Concomitant Variables for Clustering Microbiome Data.
    Abstract
  • April. 13, 2021
    Speaker: Nalini Ravishanker (University of Connecticut)
    Topic: Biclustering Approaches for High-Frequency Time Series.
    Abstract
  • April. 27, 2021
    Speaker: Melody Ghahramani (The University of Winnipeg)
    Topic:Time Series Regression for Zero-Inflated and Overdispersed Count Data: A Functional Response Model Approach.
    Abstract
  • May 04, 2021
    Speaker: Zhou Wang (Binghamton University)
    Topic: Multiclass Anomaly Detector: the CS++Support Vector Machine
    Abstract

Fall 2020

  • Oct. 20, 2020
    Speaker: Sumanta Basu (Cornell University)
    Topic: Measuring Systemic Risk with Graphical Models of Time Series Data.
    Abstract
  • Oct. 27, 2020
    Speaker: Yuan Luo (Northwestern University)
    Topic: A Multidimensional Precision Medicine Approach Identifies an Autism Subtype Characterized by Dyslipidemia
    Abstract
  • Nov. 3, 2020
    Speaker: Shaofei Zhao (Binghamton University)
    Topic: Distribution-free and nonparametric multivariate feature screening via measure transportation for high dimensional response and predictor variables.
    Abstract

Spring 2020

  • Mar. 24, 2020
    CANCELLED AND POSTPONED
    Speaker: Sumanta Basu (Cornell University)
  • April. 21, 2020
    Speaker: Liang Li, Yunhui Liu and Han Zhang
    Topic: Capstone Project: Factors Affecting PhD Student Success.
    Abstract
  • April. 21, 2020
    CANCELLED AND POSTPONED
    Speaker: Adam Ciarleglio (George Washington University)
  • May. 05, 2020
    CANCELLED AND POSTPONED
    Speaker: Yuan Luo (Northwestern University)

Fall 2019

See the schedule of the Interdisciplinary Dean's Speaker Series in Data Science.

  • Oct. 9, 2019 (special day and time)
    Interdisciplinary Dean's Speaker Series in Data Science
    Speaker: Joseph W Hogan (Brown University)
    Topic: Using Electronic Health Records Data for Predictive and Causal Inference About the HIV Care Cascade
    Abstract
  • Oct. 11, 2019 (Special Date and time)
    Speaker: Paul McNicholas (McMaster University)
    Topic: Clustering Higher-Order Data
    Abstract
  • Oct. 22, 2019
    Speaker: Gen Li (Columbia University)
    Topic: Integrative multi-view regression: Bridging group-sparse and low-rank models.
    Abstract
  • Oct. 29, 2019
    Speaker: Wangshu Tu (Binghamton University)
    Topic: A family of mixture models for biclustering
    Abstract
  • Nov. 5, 2019
    Speaker: Wangshu Tu (Binghamton University)
    Topic: Non existence of fixed sample estimator for prescribed proportional closeness
    Abstract
  • Nov. 8, 2019
    Interdisciplinary Dean's Speaker Series in Data Science
    Speaker: Andrew Gordon Wilson (New York University; Courant Institute of Mathematical Sciences)
    Topic: How do we build models that learn and generalize?
    Abstract
  • Nov. 12, 2019
    Speaker: Kexuan Li (Binghamton University)
    Topic: A Hausman test for the presence of market microstructure noise in high frequency data
    Abstract
  • Nov. 19, 2019
    Interdisciplinary Dean's Speaker Series in Data Science
    Time: 10am-11:30am
    Location: UUW325
    Speaker: Arthur Spirling (New York University; Politics and Data Science)
    Topic: Word Embeddings: What works, what doesn’t, and how to tell the difference for applied research
    Abstract
  • Nov. 26, 2019
    Speaker: Wei Yang (Binghamton University)
    Topic: Random Covariance Matrix and the Marchenko-Pastur law
    Abstract

Spring 2019

  • March 05, 2019
    Speaker: Rebecca Nugent (Carnegie Mellon University)
    Topic: Before Teaching Data Science, Let’s First Understand How People Do It
    Abstract
  • March 26, 2019
    The Dean's Speaker Series in Statistics and Data Science
    Speaker: Regina Y. Liu (Rutgers University)
    Topic: Fusion Learning: Efficient Combination of Inferences from Diverse Data Sources
    Abstract
  • April 9, 2019
    Speaker: David Hunter (Pennsylvania State University)
    Topic: Multivariate Nonparametric Mixture Models
    Abstract
  • April 16, 2019
    The Dean's Speaker Series in Statistics and Data Science
    Speaker: David Madigan (Columbia University)
    Topic: Towards honest inference from real-world healthcare data
    Abstract
  • April 23, 2019
    Speaker: Daphney-Stavroula Zois (SUNY Albany)
    Topic: Spatiotemporal Quickest Change Detection for Traffic Accident Nowcasting
    Abstract
  • April 30, 2019
    Speaker: Lin Yao (Binghamton University)
    Topic: Dissertation Defense - JAMES-STEIN-TYPE OPTIMAL WEIGHT CHOICE FOR FREQUENTIST MODEL AVERAGE ESTIMATOR
    Special time and location: 3:30 pm at OR 100D
    Abstract

Fall 2018

  • October 9, 2018
    The Dean's Speaker Series in Statistics and Data Science
    Speaker: Sidney Resnick (Cornell University)
    Location: Old Champlain Atrium (unusual location)
    Topic: Fitting the Linear Preferential Attachment Model for Social Network Growth
    Abstract
  • October 23, 2018
    The Dean's Speaker Series in Statistics and Data Science
    Speaker: David Ruppert (Cornell University)
    Topic: Density Estimation with Noisy Data
    Abstract
  • November 13, 2018
    Speaker: Yudong Chen (Cornell University)
    Topic: Byzantine-Robust Distributed Learning with Non-converxity
    Abstract

—-

Spring 2018

  • January 30
    Speaker: Qiqing Yu (Binghamton University)
    Topic: Identifiability Conditions For The Linear Regression Model Under Right Censoring
    Abstract
  • February 20
    Speaker: Yinsong Chen (Binghamton University)
    Topic:The Conductance and Mixing Time
    Abstract
  • March 13
    Speaker: Jiexin Duan (Purdue University)
    Topic: Large-Scale Nearest Neighbor Classification with Statistical Guarantee
    Abstract
  • March 20
    Speaker: Yuan Fang (Binghamton University)
    Topic: Bayesian Approach to Parameter Estimation for the mixtures of Multivariate Normal Inverse Gaussian Distributions
    Abstract
  • April 10
    ​Speaker:​ Leila Setayeshgar (Providence College)
    Topic: Large Deviations for a Class of Stochastic Semilinear Partial Differential Equations
    Abstract
  • April 17
    Speaker: Wenbo Wang (Binghamton University)
    Topic: A look at distance-weighted discrimination
    Abstract
  • April 24
    Speaker: Haomiao Meng (Binghamton University)
    Topic: Multicategory Angle-based Large-margin Classification
    Abstract
  • May 1
    Speaker: Chen Liang (Binghamton University)
    Topic: Goodness of fit tests for clustered spatial point processes
    Abstract

—-

Fall 2017

  • September 19
    Speaker: Dan Yang (Rutgers University)
    Topic: Autoregressive Model for Matrix Valued Time Series
    Abstract
  • September 26
    Speaker: Ji Meng Loh (New Jersey Institute of Technology)
    Topic: Single-index model for inhomogeneous spatial point processes
    Abstract
  • November 14
    Speaker: Weijie Su (Wharton School of the University of Pennsylvania)
    Topic: TBA
    Abstract
seminars/datasci.txt · Last modified: 2021/11/25 10:38 by gfu