Research Mentees

Luke Kurlandski (2021-2022)

• Research Topics: Impact of Stop Sets on Stopping Active Learning for Text Classification.
• Position while mentored: Student at TCNJ.
• Next Position: PhD Student at Rochester Institute of Technology.
• Awards:
• National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) (2024, accepted)
• National Defense Science and Engineering Graduate (NDSEG) Fellowship (2024, declined)
• Co-authored one peer-reviewed publication together: [1].

John Barry (2020)

• Research Topics: Mathematical Analysis of Stopping Active Learning and Investigation of Text Classification Forecasting Patterns During Machine Learning.
• Position while mentored: Student at TCNJ.
• Next Position: PhD Student at Drexel University.

Thomas Orth (2018-2019)

• Research Topics: Early Forecasting of Text Classification Accuracy and F-Measure with Active Learning.
• Position while mentored: Student at TCNJ.
• Next Position: Associate Machine Learning Engineer at Lockheed Martin.
• Co-authored one peer-reviewed publication together: [1].

Michael Altschuler (2018-2019)

• Research Topics: Stopping Active Learning based on Predicted Change of F Measure and Automated Outline Generation.
• Position while mentored: Student at TCNJ.
• Next Position: Software Engineer at AT&T.
• Co-authored one peer-reviewed publication together: [1].

Garrett Beatty (2017-2018)

• Research Topics: Impact of Batch Size on Stopping Active Learning and the Use of Unlabeled Data versus Labeled Data for Stopping Active Learning.
• Position while mentored: Student at TCNJ.
• Next Position: Software Engineer at Comcast NBCUniversal.
• Co-authored two peer-reviewed publications together: [1] and [2].

Brittany Reedman (2018)

• Research Topic: Mathematical Analysis of Performance Bounds During Active Learning.
• Position while mentored: Student at TCNJ.
• Next Position: Software Engineer at Facebook.

Keenan Sayers (2017)

• Research Topic: Analysis of Diminishing Returns of Input Training Data for Support Vector Machines.
• Position while mentored: Student at TCNJ.
• Next Position: Software Engineer at Tata Consultancy Services.

Ryan Haines (2017)

• Research Topic: Analysis of Diminishing Returns in Machine Learning Training Curves.
• Position while mentored: Student at TCNJ.
• Next Position: Programmer/Analyst at State of New Jersey Office of Legislative Services.

Trevor Fullman (2016)

• Research Topic: Statistical Sampling Algorithms for Machine Learning.
• Position while mentored: Student at TCNJ.
• Next Position: Software Engineering Associate at Lockheed Martin.

Kevin Wonus (2016)

• Research Topic: Social Media Text Filtering.
• Position while mentored: Intern at UMD.
• Next Position: Principal Engineer, The DarkStar Group, LLC.
• Co-authored one peer-reviewed publication together: [1].
• On the basis of our research project, Kevin successfully met the research internship requirements for his University of Washington Computational Linguistics Masters Degree

Benjamin Strauss (2012-2015)

• Research Topics: Translation Memory Systems, Statistical Anomaly Detection, and Machine Learning for Cell Biology.
• Position while mentored: Faculty Research Assistant at UMD.
• Next Position: PhD Student at The Ohio State University.
• Co-authored five peer-reviewed publications together: [1], [2], [3], [4], and [5].
• Co-authored two invention disclosures together, one of which was selected as a Finalist for Invention of the Year ([1]).

Jeremy Choi (2015)

• Research Topic: Translation Lexicon Induction.
• Position while mentored: Language Science Summer Scholar at UMD.
• Next Position: Student at University of Maryland.
• Jeremy was awarded a Language Science Summer Scholarship based on our research project.