Jesse Eickholt

According to our database, Jesse Eickholt authored at least 26 papers between 2009 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

An Ornithologist's Guide for Including Machine Learning in a Workflow to Identify a Secretive Focal Species from Recorded Audio.

Ming Liu, Qiyu Sun, Dustin E. Brewer, Thomas M. Gehring, Jesse Eickholt

Remote. Sens., 2022

Student-facing Learning Analytics Dashboard: Profiles of Student Use.

Jesse Eickholt, Jennifer L. Weible, Stephanie D. Teasley

Proceedings of the IEEE Frontiers in Education Conference, 2022

2021

Practical Active Learning Stations to Transform Existing Learning Environments Into Flexible, Active Learning Classrooms.

Jesse Eickholt, Matthew R. Johnson, Patrick Seeling

IEEE Trans. Educ., 2021

2020

TopQA: a topological representation for single-model protein quality assessment with machine learning.

John Smith, Matthew Conover, Natalie Stephenson, Jesse Eickholt, Dong Si, Miao Sun, Renzhi Cao

Int. J. Comput. Biol. Drug Des., 2020

Pedagogy and Classroom: How Can I Do This in That Space or Does it Even Matter?

Jesse Eickholt, Patrick Seeling

Proceedings of the 51st ACM Technical Symposium on Computer Science Education, 2020

Supporting Instructor Reflection on Employed Teaching Techniques via Multimodal Instructor Analytics.

Jesse Eickholt

Proceedings of the IEEE Frontiers in Education Conference, 2020

2019

Low-Cost Active Learning Benefits for Introductory Computer Science Courses.

Patrick Seeling, Jesse Eickholt, Quentrese Hinton, Matthew R. Johnson

Proceedings of the IEEE Frontiers in Education Conference, 2019

Advancing Adoption of Active Learning Pedagogy via New Avenues of Research and Training.

Jesse Eickholt, Lisa Gandy, Patrick Seeling, Matthew R. Johnson

Proceedings of the IEEE Frontiers in Education Conference, 2019

2018

Barriers to Active Learning for Computer Science Faculty.

Jesse Eickholt

CoRR, 2018

2017

Creating Economy Active Learning Classrooms for IT Students.

Quentrese Cole, Matthew R. Johnson, Jesse Eickholt

Proceedings of the 18th Annual Conference on Information Technology Education and the 6th Annual Conference on Research in Information Technology, 2017

Teaching Big Data and Cloud Computing with a Physical Cluster.

Jesse Eickholt, Sharad Shrestha

Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, 2017

Levels of active learning in programming skill acquisition: From lecture to active learning rooms.

Patrick Seeling, Jesse Eickholt

Proceedings of the 2017 IEEE Frontiers in Education Conference, 2017

Supporting active learning through commodity and open source solutions.

Jesse Eickholt, John Roush, Patrick Seeling, Thiruvarangan Vedantham, Matthew R. Johnson

Proceedings of the 2017 IEEE Frontiers in Education Conference, 2017

A distributed pipeline for DIDSON data processing.

Liling Li, Tyler Danner, Jesse Eickholt, Erin McCann, Kevin Pangle, Nicholas Johnson

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2015

A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.

Matt Spencer, Jesse Eickholt, Jianlin Cheng

IEEE ACM Trans. Comput. Biol. Bioinform., 2015

2014

Adopting the MapReduce framework to pre-train 1-D and 2-D protein structure predictors with large protein datasets.

Jesse Eickholt, Suman Karki

Proceedings of the 2014 IEEE International Conference on Bioinformatics and Biomedicine, 2014

2013

A study and benchmark of DNcon: a method for protein residue-residue contact prediction using deep networks.

Jesse Eickholt, Jianlin Cheng

BMC Bioinform., 2013

DNdisorder: predicting protein disorder using boosting and deep networks.

Jesse Eickholt, Jianlin Cheng

BMC Bioinform., 2013

2012

Recursive protein Modeling: a Divide and Conquer Strategy for protein Structure Prediction and its Case Study in CASP9.

Jianlin Cheng, Jesse Eickholt, Zheng Wang, Xin Deng

J. Bioinform. Comput. Biol., 2012

The MULTICOM toolbox for protein structure prediction.

Jianlin Cheng, Jilong Li, Zheng Wang, Jesse Eickholt, Xin Deng

BMC Bioinform., 2012

Predicting protein residue-residue contacts using deep networks and boosting.

Jesse Eickholt, Jianlin Cheng

Bioinform., 2012

2011

DoBo: Protein domain boundary prediction by integrating evolutionary signals and machine learning.

Jesse Eickholt, Xin Deng, Jianlin Cheng

BMC Bioinform., 2011

APOLLO: a quality assessment service for single and multiple protein models.

Zheng Wang, Jesse Eickholt, Jianlin Cheng

Bioinform., 2011

2010

MULTICOM: a multi-level combination approach to protein structure prediction and its assessments in CASP8.

Zheng Wang, Jesse Eickholt, Jianlin Cheng

Bioinform., 2010

2009

NNcon: improved protein contact map prediction using 2D-recursive neural networks.

Allison N. Tegge, Zheng Wang, Jesse Eickholt, Jianlin Cheng

Nucleic Acids Res., 2009

PreDisorder: ab initio sequence-based prediction of protein disordered regions.

Xin Deng, Jesse Eickholt, Jianlin Cheng

BMC Bioinform., 2009