Clemson University | HPCC Systems

Clemson University

Understand how to deploy, monitor and tune data-intensive systems.

Big Data research at Clemson University includes the development of computational science applications, evaluation of software and hardware infrastructure systems to support Big Data, and design and development of data analytics platforms. We are proud to have Clemson University as one of our long-time academic partners and continue to support their use of HPCC Systems on several big data analytics projects through their Data Intensive Computing Ecosystems (DICE) lab.

Amy Apon, Ph.D.
C. Tycho Howle Director, School of Computing
Clemson University

Tech Talk: Deploying HPCC Systems on Microsoft Azure

Tech Talk: Asking the Right Questions with Machine Learning

Tech Talk: Using HPCC Systems Machine Learning to Map Public Record Data Descriptions to Standardized Categories

Tech Talk: An Investigation into Time Series Analysis

Tech Talk: Extending the YinYang K-Means Machine Learning Algorithm in ECL

Tech Talk: Automatically Cluster Your Data with the HPCC Systems Massively Scalable K-Means Machine Learning Bundle

Poster Presentation: Analyzing Clustered Latent Dirichlet Allocation (CLDA)

Poster Presentation: Representativeness of Latent Dirichlet Allocation Topics Estimated from Data Samples with Application to Common Crawl

Tech Talk: Domain Based Common Words List Using High Dimensional Representation of Words

Tech Talk: Equivalence Terms for Text Search Bundle

Blog: Deploying HPCC Systems on Microsoft Azure

Blog: Featuring Farah Al Shanik’s 2018 Poster Presentation

Press Release: LexisNexis supports big data research at Clemson

Blog: DBSCAN -- A Density Based Clustering Method

Blog: Featuring Lili Xu's 2016 Intern Project

Blog: Automatically Cluster your Data with Massively Scalable K-Means

Webcast : Interview with Amy Apon

Videos: Professors and student discuss their work with HPCC Systems

Webcast : Interview with Lili Xu

View academic publications and papers