Date:26 January 2018, Friday
Location:S16-06-118, DSAP Seminar Room
Time:03:00pm - 04:00pm
Tackling Protein Folding with Data Science: Fast Exploration of Conformations with Sequential Monte CarloThe problem of predicting the 3-D structure of a protein from its amino acid sequence using computer algorithms has…
Date:25 January 2018, Thursday
Location:S16-05-96, Computer Lab 4
Time:03:00pm - 04:00pm
Sequential Monte Carlo for Bayesian InferencePHD ORAL PRESENTATION: Hidden Markov models are a class of statistical models that are widely used in a variety…
Date:22 January 2018, Monday
Location:S16-06-118, DSAP Seminar Room
Time:03:00pm - 04:00pm
Some New Foundational Principles and Fast Algorithms in Data AnalyticsRapid developments in communications, networking, AI robots, 3D printing, genomics, blockchain, novel materials, and powerful computation platforms are rapidly…
Date:17 January 2018, Wednesday
Location:S16-06-118, DSAP Seminar Room
Time:03:00pm - 04:00pm
Big Data in Computer ExperimentsBig data is everywhere. In computer experiments, it’s being used to emulate complex systems being simulated in computer codes….
Date:10 January 2018, Wednesday
Location:S16-06-118, DSAP Seminar Room
Time:03:00pm - 04:00pm
A Two-Stage Design for Comparative Clinical Trials: The Heteroscedastic SolutionWe consider a hybrid selection and testing design for comparing the means of several experimental normal populations among themselves…
Date:10 January 2018, Wednesday
Location:S16-06-118, DSAP Seminar Room
Time:04:30pm - 05:30pm
Controlled Sequential Monte CarloSequential Monte Carlo (SMC) methods are a set of simulation-based techniques used to approximate high-dimensional probability distributions and their…
Date:06 December 2017, Wednesday
Location:S-16-06-118, DSAP Seminar Room
Time:03:00pm - 04:00pm
On Steady-State Performance Characteristics of Control Charts -Meaning and NumericsAt first sight, the defination of a reasonable steady-state measure of control chart detection performance seems to be both…
Date:04 December 2017, Monday
Location:03:00pm - 04:00pm
Time:S16-06-118, DSAP Seminar Room
Statistical Learning of Ultra High-Dimensional Potts Models in GenomicsThe potential for genome-wide modeling of epistasis has recently surfaced given the possibility of sequencing densely sampled populations and…
Date:24 November 2017, Friday
Location:03:00pm - 04:00pm
Time:S16-06-118, DSAP Seminar Room
Models for Imputing Non-ignorable Missing Data,There are two relatively standard approaches for imputing missing data, one based on “selection” models and one based on…
Date:21 November 2017, Tuesday
Location:S16-05-96, Computer Lab 4
Time:02:00pm - 03:00pm
Some new methods for supervised classification for functional dataPhd Oral Presentation Functional data are getting prevalent in many research and industrial fields in recent decades. It is…