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: Statistics Group

See also the Statistics Seminar.
See Previous talks in the Data Science Seminar and even earlier talks.

• October 15, 2024
  Speaker: Dr. Yang Ning (Cornell University)
  Topic: Estimation and Inference in Multivariate Response Regression with Hidden Variables.
  Abstract

• November 5, 2024
  Speaker: Dr. Yunlong Feng from SUNY Albany
  Topic: .
  Abstract

• November 12, 2024
  Speaker: Jones Ben ()
  Topic: .
  Abstract

• January 23, 2024
  Speaker: Yili Zhang (MathWorks)
  Topic: Low-Code Machine Learning in SIMULINK & MATLAB APPS.
  Abstract

• March 26, 2024
  Speaker: Dr. Zeyu Ding (Department of Computer Science at Binghamton University)
  Topic: Differential Privacy in Practice: How the US Government Protects Your Sensitive Information in the 2020 Census.
  Abstract

• September 26, 2023
  Speaker: Dr. Marianthi Markatou (SUNY University at Buffalo)
  Topic: Distances and their role in statistical inference.
  Abstract

• October 3, 2023
  Speaker: Dr. HaiYing Wang (University of Connecticut)
  Topic: Rare Events Data and Maximum Sampled Conditional Likelihood.
  Abstract

• October 10, 2023
  Speaker: Dr. Yiming Ying (SUNY University at Albany)
  Topic: Interplay between Generalization and Optimization via Algorithmic Stability.
  Abstract

• October 17, 2023
  Speaker: Dr. Peter D. Hoff (Duke University)
  Topic: Core Shrinkage Covariance Estimation for Matrix-variate Data.
  Abstract

• October 24, 2023
  Speaker: Dr. Luis Carvalho (Boston University)
  Topic: Deviance Matrix Factorization.
  Abstract

• October 31, 2023
  Speaker: Dr. Ruiqi Liu (Texas Tech University)
  Topic: Estimation and Hypothesis Testing of Derivatives in Smoothing Spline ANOVA Models.
  Abstract

• November 14, 2023
  Speaker: Dr. Jiguo Cao (Simon Fraser University)
  Topic: Machine Learning for Functional Data.
  Abstract

• November 28, 2023
  Speaker: Dr. Li Zhang (University of California San Francisco)
  Topic: NAIR Software: Unlocking the Immune System's Secrets by Network Analysis and Advanced Machine Learning.
  Abstract

• December 5, 2023
  Speaker: Dr. Xuexia Wang (Florida International University)
  Topic: Genetic Association Test and Risk Prediction Modeling for Cardiomyopathy in Cancer Survivors.
  Abstract

• February 14, 2023
  Speaker: Dr. Yuan Fang (Binghamton University)
  Topic: Clustering disease trajectories: statistical method applications and evaluation.
  Abstract

• February 21, 2023
  Speaker: Dr. Xuming He (University of Michigan)
  Topic: How Good is Your Best Selected Subgroup.
  Abstract

• February 28, 2023
  Speaker: Dr. James D. Wilson (University of San Francisco)
  Topic: The Political Brain: Associations of Tasked-based Functional Connectivity Networks and Political Ideology.
  Abstract

• March 7, 2023
  Speaker: Dr. Sijian Wang (Rutgers, The State University of New Jersey)
  Topic: Dynamic Attention-Based Functional Data Analysis.
  Abstract

• March 14, 2023
  Speaker: Dr. Holger Dette (Ruhr-Universitaet Bochum)
  Topic: Functional data analysis on Banach spaces.
  Abstract

• March 21, 2023
  Speaker: Dr. Hamsa Bastani (University of Pennsylvania)
  Topic: Efficient and targeted COVID-19 border testing via reinforcement learning.
  Abstract

• March 28, 2023
  Speaker: Dr. Jie Peng (UC Davis)
  Topic: Statistical methods for diffusion MRI.
  Abstract

• April 11, 2023
  Speaker: Dr. Chris Haines (Internal)
  Topic: Independent Spacings Theorem with a Maximum Product Spacings Estimation Application.
  Abstract

• April 18, 2023
  Speaker: Dr. Konstantin G. Arbeev (Duke University)
  Topic: How Good is Your Best Selected SubgroupStochastic process models: Bringing biology to statistics to advance research on aging.
  Abstract

• April 27, 2023
  Speaker: Dr. Runze Li (Penn State University)
  Topic: Model-Free Conditional Feature Screening with FDR Control.
  Abstract

• September 20, 2022
  Speaker: Dr. Soumik Banerjee (Internal)
  Topic: Likelihood-based Approach for Testing the Homogeneity of Risk Difference in a Multicenter Randomized Clinical Trial.
  Abstract

• October 4, 2022
  Speaker: Dr. Chao Huang (Florida State University)
  Topic: Shape-on-Scalar Regression Models: Going Beyond Prealigned Non-Euclidean Responses.
  Abstract

• October 25, 2022
  Speaker: Dr. John Stufken (George Mason University)
  Topic: Musings on Subdata Selection.
  Abstract

• November 1, 2022
  Speaker: Dr. Jinchi Lv (University of Southern California)
  Topic: High-Dimensional Knockoffs Inference for Time Series Data.
  Abstract

• November 8, 2022
  Speaker: Dr. Rui Song (North Carolina State University)
  Topic: On statistical inference for sequential decision making.
  Abstract

• November 15, 2022
  Speaker: Dr. Rachael Hageman Blair (University at Buffalo)
  Topic: Harnessing stability estimation for module detection, clustering, and ensemble clustering.
  Abstract

• December 6, 2022
  Speaker: Dr. Alexander Franks (University of California, Santa Barbara)
  Topic: Sensitivity to Unobserved Confounding in Studies with Factor-structured Outcomes.
  Abstract

• Apr. 5, 2022
  Speaker: Dr. Soumik Banerjee (Internal)
  Topic: Multistage Minimum Risk Point Estimation (MRPE) with First-Order and Second-Order Asymptotic Properties.
  Abstract

• Apr. 26, 2022
  Speaker: Dr. Krishnakumar Balasubramanian (The University of California, Davis)
  Topic: Fractal Gaussian Networks: A sparse random graph model based on Gaussian Multiplicative Chaos.
  Abstract

• May 3, 2022
  Speaker: Dr. Hongtu Zhu (University of North Carolina)
  Topic: Challenges in Biobank-scale: Imaging Genetics and Beyond.
  Abstract

• May 10, 2022
  Speaker: Dr. Yao Zheng (University of Connecticut)
  Topic: Tensor methods for high-dimensional time series modeling.
  Abstract

• Sep. 14, 2021
  Speaker: Dr. Matthew Reimherr (Pennsylvania State University)
  Topic: KNG - A New Mechanism for Data Privacy.
  Abstract

• 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

• 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

• 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

• 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)

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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. 24, 2019 (1:15 pm, stat seminar time)
  Speaker: Doug Turnbull (Ithaca College)
  Topic: TBA
  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

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• March 05, 2019
  Speaker: Rebecca Nugent (Carnegie Mellon University)
  Topic: Before Teaching Data Science, Let’s First Understand How People Do It
  Abstract

• March 12, 2019
  Speaker: Subhadeep (Deep) Mukhopadhyay (Temple University)
  Topic: Graph Data Science
  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

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• 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

—-

• 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

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• 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