Conference Schedule

Abstracts for all talks are available here.

Note: A program pamphlet with talk abstracts will also be available at the conference.

After the conference, please complete the survey here.

February 29: Open Problems and Discussions with Invited Speakers

8:30-9:30am

Registration/Check-in

Smith Center for Undergraduate Education (CUE) Atrium


9:30-10:15am

Keynote Address, CUE 203

A Career Path to Data Science and Generating Image Captions for New Articles

Emmanuel Yera, Primer AI


10:15-10:40am

Coffee Break, CUE Atrium


10:40am-12:10pm

Talks on Open Problems, Session 1A, CUE 203

10:40 Detecting a Deadly Disease Using Diverse Machine Learning Models

Leonard Apeltsin, Berkeley Institute of Data Science

11:00 Designing and Implementing Methods for Improving Iris Biometric Recognition

Ali Al-Sharadqah, California State University Northridge


11:20 Human-in-the-Loop Selection of Optimal Time Series Anomaly Detection Methods

Cynthia Freeman, Verint Intelligent Self-Service


11:40-12:10: Group Discussion of the three talks.


Talks on Open Problems, Session 1B, CUE 202

10:40 In Pursuit of the Grassmann Manifold Projection Mean

Justin Marks, Biola University

11:00 Simulation of Random Processes on Graphs: Reconstructing the Entire State Space as a Single Graph

Joseph Stover, Gonzaga University

11:20 Discovering Latent Metrics Behind Observed Metrics

Stephen J. Young, Pacific Northwest National Laboratory


11:40-12:10: Group Discussion of the three talks.


12:10-1:30pm

Lunch

(not provided, but options available on campus in the Compton Union Building, CUB)


1:30-3:00pm

Talks on Open Problems, Session 2A, CUE 203

1:30 Generating Synthetic Data Via Random Tensors

Emilie Purvine, Pacific Northwest National Laboratory


1:50 Mathematical Adventures in Multidimensional Data: From Incidence Tensors to Lattice-Valued Schema Hypergraphs

Cliff Joslyn, Pacific Northwest National Laboratory


2:10 Large-scale Unsupervised Image Discovery and Retrieval

Michael Henry, Pacific Northwest National Laboratory


2:30-3:00 Group Discussion of the three talks.


Talks on Open Problems, Session 2B, CUE 202

1:30 Geometric Data Analysis: Learning the Shape of Data

Dominique Zosso, Montana State University

1:50 The Gromov-Hausdorff Distance and its Use for Shape Matching

Vlad Oles, Independent Researcher


2:10 Where Are the Orcas, Where is the Salmon?

Valentina Staneva, eScience Institute, University of Washington


2:30-3:00 Group Discussion of the three talks.


3:00-3:30pm

Coffee Break, CUE Atrium


3:30-5:00pm

Talks on Open Problems, Session 3, CUE 203

3:30 Where’s my scikit-clean? Addressing the data prep problem

Matthew Sottile, Noddle.io & Washington State University

3:50 Some Challenges and Opportunities Arising from Rapid Advancements in Big Data and AI Technologies

Predrag Tosic, Whitworth University


4:10 Efficiently Sampling High-Dimensional Test Spaces for Function Interpolation and Failure Analysis.

Sharif Ibrahim, Intel

4:30-5:00 Group Discussion of the three talks.


5:00-7:30pm

Reception, CUE 518


March 1: Student/Early Career Presentations, Workshops, Panels


8:30-9:30am

Registration/Check-in

Lobby of Smith Center for Undergraduate Education (CUE)


Concurrent Workshops

8:30-9:20am

1) Intro to Research in Data Science and Image Analysis, CUE 219

Matthew Sottile, Noddle.io & Washington State University

In this tutorial we will talk about performing research in data science, with special attention to image-based data problems. We will discuss the foundations that you should build to start to effectively perform research in this area, and walk through some example problems to motivate the discussion.


8:30-9:20am

2) What is data science? CUE 209

Valentina Staneva, University of Washington

In this tutorial we will go on a tour through the concepts and tools one needs to master to become a successful data scientist. We will cover topics such as data and code organization, mining complex and heterogeneous data sets, scalable computing, literate programming, evaluation, ethics. Although most concepts are programming language agnostic, I will share some Python tools and resources along the way.


9:30-10:30am

Back-to-Back Panel Discussions, CUE 202

1) Internships in Data Science and Image Analysis

2) Career Skills and Job Search Tips

Panelists:

Emmanuel Yera, Primer AI

Emilie Purvine, PNNL

Cynthia Freeman, Verint

Leonard Apeltsin, Berkeley Institute of Data Science

Moderator:

Viktoria Taroudaki, Eastern Washington University


10:30-10:50pm

Coffee Break, CUE Atrium


10:50am-1:10pm

Student/Early Career Presentations (SECP)


SECP Session 1, CUE 209

10:50 Using Neural Networks to Classify PDEs

Julia Balukonis, Providence College

Haley Rosso, University of Houston

Sabrina Fuller, University of Virginia

11:10 Improving X-ray Analysis Throughput using Transfer Learning and Object Detection

Edgar Ramirez, Pacific Northwest National Laboratory

11:30 Data set reduction in TDA

Johannes Krotz, Oregon State university

11:50 Social Network Influencers’ Data Augmenting Recommender Systems

Ashrf Althbiti, University of Idaho

12:10 A Fast Convergence Algorithm for Band-limited Extrapolation by Sampling

Weidong Chen, Minnesota State University, Mankato


12:30 Neuro-sensory integration in the nematode C. elegans as a nonlinear dynamical system with control

Megan Morrison, University of Washington

12:50 Snowfall and Climate Change in Washington

Rebecca Martin, Central Washington University


SECP Session 2, CUE 207

10:50 On combining data from distinct non-linear predictive models

Amrina Ferdous, Boise State University


11:10 Introduction to Homology Theory for Topological Data Analysis

Danny Wentland, Oregon State University

11:30 An Introduction to Cubical Homology

Chung-Ping Lai, Oregon State University

11:50 Computing Homology Groups

Arthur Mills, Oregon State University

12:10 Continuous monitoring of chronic wounds: Application of multilayer perceptron for image-based classification of wounds

Qi Wei, Oregon State University

12:30 Bending Loss Regularized Network for Nuclei Segmentation in Histopathology Images

Haotian Wang, University of Idaho

12:50 STAN: Small Tumor-Aware Network for Breast Ultrasound Image Segmentation

Bryar Shareef, University of Idaho


SECP Session 3, CUE 216

10:50 Anomaly Detection in Sequences of Short Text

Cynthia Freeman, Verint Intelligent Self-Service


11:10 RayNN: Sampling of point clouds with rays and applications to 3D classification

Liangchen (Lewis) Liu, University of British Columbia

11:30 A linear NBVP in Singular Perturbation Theory

Evangelos Nastas, Syracuse University

11:50 CNN-Based Iterative Image Reconstruction Techniques for Sparse-View and Limited-angle CT Images

Yiran Jia, University of Washington, Bothell

12:10 Deep Learning Methods for Detecting Structural Variants in Related Individuals

Erica Sawyer, California State University, Fresno


12:30 Machine Learning for Image Forgery Detection

Lubna Azlamil, Central Washington University

12:50 Improving Global Ground Freeze-Thaw Classification with Machine Learning

Fredrick Bunt, University of Montana

Kellen Donahue, University of Montana


SECP Session 4, CUE 219

10:50 Archetypal Analysis Applied to Neuronal Cellular Signaling

Catherine Potts, Montana State University

11:10 Accelerating Graph-based Geometric Data Analysis

Xingzi Xu, Montana State University

11:30 Spatial Statistics in Histology Images

Dominic Bair, Montana State University

11:50 Crop Identification and Segmentation Through Image Analysis

Nicolaas VanSteenbergen, University of Nebraska, Omaha


12:10 Using NLP to describe and classify rap lyrics

Morgan Burrell, Central Washington University


12:30 Observing the Sensitivity of Step Sizes in a Neural Network

Alexis Harris, Oregon Institute of Technology


12:50 Is the #Metoo Movement an "Echo Chamber"? The impact of social movements on the general population

Thet Nyein, San Francisco State University

Jason Baik, San Francisco State University


SECP Session 5, CUE 218

10:50 An Analytical Examination of Vegetarian Diets on Health

Aletha Marie Kleis, Central Washington University


11:10 Medical Imaging with Electrical Impedance Tomography Part I

Scott Campbell, Gonzaga University

Fisher Ng, Gonzaga University

11:30 Medical Imaging with Electrical Impedance Tomography Part II

Benjamin Bladow, Gonzaga University

11:50 Data-driven System Identification for Robots in Granular Medium

Suresh Ramasamy, Oregon State University

12:10 Diffeomorphic registration of varifolds

Hsi-Wei Hsieh, Johns Hopkins University

12:30 Geometric Measure Theory and Soft Matter Interface Feature Identification

Enrique Alvarado, Washington State University

12:50 The Euler Line

Kelly Hoffman, Marian University–WI


Tentative 1:10 Computationally feasible approaches based on Krylov subspace methods

Mirjeta Pasha, Kent State University & John Carroll University

1:10-2:30pm

Lunch Provided CUE 518

Conclusion


Please contact the organizers at datascienceconference@gmail.com with any questions.

Inclusion Statement

In an effort to make the conference accessible to all attendees, we ask for your cooperation in being fragrance-free. Please refrain from using fragranced personal care products–such as perfumes, colognes, perfumed lotions, etc.–on the day of the event. We thank you in advance for your efforts to support your colleagues. If we can support your inclusion at the conference in any way, please contact us at datascienceconference@gmail.com with any questions or requests for disability-related accommodations. We are committed to doing all that we can to support your full participation.