MSSISS 2016 – MSSISS 2024


The MSSISS 2016 keynote speaker is Dr. Michael Jordan, Pehong Chen Distinguished Professor of Department of EECS and Department of Statistics at the University of California, Berkeley.

His research in recent years has focused on Bayesian nonparametric analysis, probabilistic graphical models, spectral methods, kernel machines and applications to problems in signal processing, statistical genetics, computational biology, information retrieval and natural language processing. Prof. Jordan was elected a member of the National Academy of Sciences (NAS) in 2010, of the National Academy of Engineering (NAE) in 2010, and of the American Academy of Arts and Sciences in 2011. He is a Fellow of the American Association for the Advancement of Science (AAAS). He has been named a Neyman Lecturer and a Medallion Lecturer by Institute of Mathematical Statistics (IMS). He is a Fellow of the IMS, a Fellow of the IEEE, a Fellow of the AAAI, and a Fellow of the ASA.

On the Computation/Statistics InterfaceJordan

There are many research challenges and open problems at the interface of computation and statistics. In this talk I’ll discuss some recent progress at this interface, including (1) the use of concurrency control mechanisms in the setting of statistical inference; (2) an analysis of the computational complexity of high-dimensional Bayesian variable selection; and (3) a new variational perspective on the mysterious phenomenon of Nesterov acceleration.

MSSISS 2016 Presentation Awards:

Best Oral Presentation:

Michael Hornsten (Statistics) – Efficient mean structure estimation using matrix variate data

Oral Presentation Honorable Mention:

Sayantan Das (Biostatistics) – Next generation imputation methods

Best Poster Presentation:

Teal Guidici (Statistics) – Detecting differentially expressed metabolic pathways with adjustments for macronutrient intake

Departmental Poster Presentation Winners:

  • Krithika Suresh (Biostatistics) – Evaluating use of a Cox regression model in landmark analysis to approximate an illness-dealth model
  • Michael Kovalcik (EECS) – Deep learning in mobile health
  • Tom Logan (IOE) – Predictive models in horticulture: a case study with royal gala apples
  • Nhat Ho (Statistics) – Singularity structures and parameter estimation in mixtures of skew normal distribution
  • Stephanie Stern (Survey Methodology) – Beverage-specific binge drinking patterns in young adults aged 19/20

MSSISS 2016 – Final Schedule

MSSISS 2016 – Program

MSSISS 2016 Student Organizing Committee

Wenting Cheng Biostatistics
Kristjan Greenewald EECS
Wenbo Sun IOE
Joon Ha Park Statistics
Felicitas Mittereder Survey Methodology

MSSISS 2016 Faculty Advisory Committee

Timothy Johnson Biostatistics
Clayton Scott EECS
Eunshin Byon IOE
Susan Murphy Statistics
Brady West Survey Methodology


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