Friday5May 2017

Computational and Data Sciences Graduate Conference

Friday, May 5, 2017 9:00am - 5:00pm
2017-05-05 09:00 2017-05-05 17:00 America/Los_Angeles Computational and Data Sciences Graduate Conference BH 103 Bertea Hall 103 Practice Room Robin Pendergraft pendergr@chapman.edu

Free to attend

BH 103

Bertea Hall 103 Practice Room

Chapman Community

Students, staff, faculty and alumni

The Computational and Data Sciences Graduate Conference provides opportunities for graduate students in the Computational and Data Science (CADS) program to present their scholarly research before fellow students and faculty. 

The conference showcases the outstanding and varied research being done at Chapman University. This event provides a forum to exchange technical ideas and methods amongst researchers in an interdisciplinary program, spanning diverse fields, including: applied mathematics; high-performance computing; economic systems modeling;  Big Data, machine learning, and data mining; bioinformatics; earth systems modeling; and computational biology, chemistry, and physics. 

All are welcome to join. Drop in as your schedule allows.

Conference Presentations:
  • George Escalante: A Quantum Inspired Model of Radar Range and Range-Rate Measurements with Applications to Weak Value Measurements 
  • Shiva Barzili: Predicting Continuous Quantum Measurement Calibration Drifts with Neural Networks 
  • Nick LaHaye: Multi-Modal Object Tracking and Image Fusion Using Unsupervised Deep Learning: First Steps 
  • Jon Inoyue: A String Gas Cosmology Model with Variable Speed of Light during the Early Universe 
  • Domenic Donato: Using Adversarial Examples to Identify Important Image Features 
  • Alexis Ford: Automated Creation of ITS Modules Over a Broad Domain 
  • Kristen Whitney: Relation of Remote Sensing MODIS Data and Ground Based Observation Addressing Soil Salin-ity and Drought Over the San Joaquin Valley, CA 
  • Natalie Best: A Time Series Analysis of TravisTorrent Builds 
  • Justin Gapper: Global Survey of Depth Invariant Index using GIS Data 
  • Ismael de Paiva: Quantum Mechanics in Discrete Spacetime 
  • Chloe Martin-King: Utilizing Homogeneous Diffusion Inpainting for Image Compression in Damaged Region Inpainting Tasks 
  • James Wimberly: On The Representation Of Boolean Groupoids And Boolean Semilattices 
  • Steve Agajanian, Nathaniel Bischoff, Simrath Ratra, Yemi Odeyemi: Classifying Functional Importance of Cancer Mutations 
  • Eric Freda: Computational Searches for Fundamental Non-Classical Structures in Quantum Mechanics 
  • Kyle Anderson: Multivariate Analysis of Complex Survey Data 
  • Alex Barrett, Andrew Nguyen, Arjun Tummala: EKG classification: Automated Diagnosis of Atrial Fibrillation and Other Arrhythmias Us-ing Wavelets, Principal Component Analysis, and Multinomial Logistic Regression 
  • Arnold Zheng: Arrhythmia Classification By ECG Data 
  • Kayleigh Hyde: Preservation of Autism Subtypes Across Stand-ard Diagnostic Instruments 
  • Luciano Rodriguez: Long Term Ground Based Precipitation Data Analysis: Spatial and Temporal Variability 
  • Andrew Fontenot: Hurricanes, Aerosols, and Their Interactions 
 

You can contact the event organizer, Robin Pendergraft at pendergr@chapman.edu or (714) 997-6993.

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