Summer Research Involvement

There are a plethora of summer research opportunities for St. Lawrence students involving math, computer science, or statistics. Many of our students are awarded SLU Fellowships or McNair Scholarships to do research on campus or participate in REU Programs all over the country and the world. The list below gives a sampling of the on-campus research projects in which our students participated.

Summer 2022

2022 Summer Research Students


  • Alexandra Hill (Class of 2023), “The Interaction Between Mental Health and Positionality in Literature: A Mathematical Analysis” (mentor: Dan Look)

Computer Science

  • Laura Bolduc (Class of 2024), “Using Game Camera Images to Build a Training Set and Identify Animal Presence” (mentor: Lisa Torrey)
  • Grace Cicchinelli (Class of 2023), “Denoising Protein Images with Deep Learning” (mentor: Lisa Torrey)
  • Cai Lemieux-Mack (Class of 2023), “Sensor Data Transplantation for Resilient Drone Operation” (mentor: Kevin Angstadt)
  • Glendalys Medina (Class of 2024), “Bias in Computer Systems” (mentor: Kevin Angstadt)


  • Trent Meyer (Class of 2023), “Water station usage analysis at SLU” (mentor: Matt Higham)
  • Hailey Quintavalle (Class of 2024) “Assessing Campus Climate Through Shiny” (mentor: Jessica Chapman)
  • Grace Bridge (Class of 2024), “ ‘You’re a [Data] Wizard, Harry!’ - A Data Science Approach to Analyzing the Harry Potter series” (mentor: Ivan Ramler)
  • Hope Donoghue (Class of 2024), “What Characterizes a Winning Combination? Network Analysis using Sports Data” (mentor: Ivan Ramler)
  • Matthew Abell (Class of 2023), “Building sports data modules for introductory statistics and data science courses.” (mentor: Michael Schuckers)

Summer 2021


  • Stefan Dragicevic, “Random Walks on Undirected Graphs” (mentor: Natasha Komarov)
  • Alexandra Hill, “Sentimental Analysis: The Mathematical Analysis of Mental Health in Literature” (mentor: Dan Look)
  • Alyssa Bigness, “Using R Studio to Explore 40 Years of Winning Results: The Statistics Behind the New York Lottery” (mentor: Dan Look)

Computer Science

  • Cameron Kessler, “Using Machine Learning to Detect and Locate Brain Tumors” (mentor: Lisa Torrey)
  • Kim Merchant, “Improving Accessibility for Web-based Software Applications” (mentors: Patti Lock, Robin Lock, Ed Harcourt and Kevin Angstadt)
  • Cai Lemieux Mack, “Mid-Mission Restart of UAV Control Software” (mentor: Kevin Angstadt)


  • Aaron Burns, “Classification of Winners and Losers in National Hockey League games based upon in-game events” (mentor Michael Schuckers)
  • Emma Donohue & Will Hagan, “Data Analysis of AirBnB and VRBO data for St. Lawrence County Chamber of Commerce” (mentor Michael Schuckers)
  • Alex Emmons, “Using Statistical Learning Methods to predict National Football League draft outcomes” (mentor Michael Schuckers)

Summer 2020


Computer Science


Summer 2019

  • Abigail Collins, Clare Booth Luce Program , “An Investigation of the Applications of Cluster Analysis in the Field of Dendrochronology” (mentor: Jessica Chapman)
  • Therese Lupariello, Clare Booth Luce Program, “Simulating the Alaskan Driftwood Phenomenon” (mentor: Jessica Chapman)
  • Gabrielle Collins, Clare Booth Luce Program, “Investigating the Matrix Properties of the Design Weighted Regression Adjusted Plus Minus model” (mentor: Michael Schuckers)
  • Skylar Ratcliffe, CSTEP Scholar, "An Expository Approach to the Banach-Tarski Paradox” (mentor: Danny Cryster)
  • Susan Liu, CSTEP Scholar, “Optimizing Card Choices in Clash Royale” (mentor: Ivan Ramler)
  • Ruoya Ding, SLU Fellowship Program, “Learning Computer Architecture with a Raspberry-Pi: (mentor: Ed Harcourt)
  • Sai Wei, SLU Fellowship Program, “Novice-User-Oriented Guidance Mini Program in WeChat” (mentor: Choong-Soo Lee)
  • Haojing Jia, SLU Fellowship Program, “Creating a Statistical Model for Evaluating the Concentration of Smog in China” (mentor: Ivan Ramler)
  • Xin Tao, SLU Fellowship Program, “Building an All-Voice Reminder System” (mentor: Lisa Torrey)
  • Catherine Buck, SLU PIC Internship – St. Lawrence County Planning Office

Summer 2018

* Emily Casey-Wagemaker, 2019, Dan Look (joint with Jessica Sierk in Education), "Racism, Classism, and Education Policy: A sociopolitical analysis of disciplinary policies in the Greater Capital District" (CSTEP)

Xuanming (Sammy) Cui, 2020, Choong-Soo Lee, "Application of Gesture Control on Digital Screen Display" (SLU Fellow)

Guinevere Gilman, 2019, Choong-Soo Lee, "High Bandwidth Mode in Overwatch" (SLU Fellow)

Seongwon (Ryan) Im, 2019, Schuckers, "Design Weighted Regression Adjusted Plus-Minus" (Schuckers Statistics Scholar)

Khang Le, 2019, Ed Harcourt, “Upgrades to StatKey software” (StatKey Locksmith Fellow)

* Remi LeBlanc, 2020, Schuckers, "Peterson Data Fellow" (PQRC)

Yuexin Li, 2019, Lisa Torrey, "Text Extraction and Translation from Camera Captured Images" (SLU Fellow)

Emily Viehl, 2019, Ivan Ramler, "Developing a Recommendation System for Books on Project Gutenberg" (SLU Fellow)

* Xizhao (Amber) Liu, 2019, Dan Look (Amber is not a formal research student) "Interest in exploring R and Stylometry"

Summer 2015

  • Janelle Fredericks '16. Statistics Major / Faculty Mentor: Ivan Ramler - Using Non-Linear Regression to Model the Carbon Density in the Amazon Rainforest
  • Sean Goddard '16. Computer Science Major / Faculty Mentor: Choong-Soo Lee - !knot: Bringing the Web Browser to the 21st Century
  • Bayard Roberts '16. Mathematics Major / Faculty Mentor: Choong-Soo Lee - Exploring Game Balance and Competitiveness

Summer 2014

  • Jacob Hurlbut '15. Computer Science Major / Faculty Mentor: Michael Schuckers - Applying Software Engineering to the Total Hockey Rating System
  • Skyler Ng '16. Computer Science Major / Faculty Mentor: Lisa Torrey - P.H.O.E.N.I.X: A Linux Virtual Assistant 

Summer 2013

Four St. Lawrence University Fellows and two professors presented their research at Los Alamos National Labs in New Mexico. Those presenting were Assistant Professor of Statistics Jessica Chapman, Chelsey Legacy, Sarah Koallick, Katie Abramski, Kathryn Christensen, and Assistant Professor of Statistics Ivan Ramler. The student projects are all co-sponsored with Los Alamos National Labs.

  • Katherine Abramski '14. Mathematics Major / Faculty Mentor: Jessica Chapman - Improving the Statistical Method for Classifying Geomagnetic Storms
  • Juan Chang '14. Mathematics Major / Faculty Mentor: Ivan Ramler - Predicting Owner Tendencies in Fantasy Football Drafts
  • Kathryn Christensen '14. Mathematics and Economics Major / Faculty Mentor: Ivan Ramler - Predicting the Lifetime of Plutonium Fuel Cells for the Los Alamos National Laboratory
  • Keith Goode '14. Computer Science Major / Faculty Mentor: Ed Harcourt - What it takes to Win: A Linear Regression Analysis of Variables in the NFL and their Contribution to Points Scored and Wins/Losses
  • Chelsey Legacy  '14. Mathematics Major / Faculty Mentor: Ivan Ramler - Evaluating Recently Developed Plutonium Management Models for Use by the Los Alamos National Laboratory to Monitor the Stockpile
  • Sarah Koallick '14. Computer Science Major / Faculty Mentor: Ed Harcourt - Integrating Software Tools for Experimental Designs with Pareto Fronts

Summer 2012

  • Jose Alejandro '13. Computer Science Major / Faculty Mentor: Lisa Torrey - Developing an Application for Android-Powered Devices
  • Kevin Angstadt '14. Computer Science and Mathematics Major / Faculty Mentor: Ed Harcourt - Developing Interactive Web Tools for Statistics Students
  • Kerrin Ehrensbeck '13. Mathematics Major / Faculty Mentor: Ivan Ramler - Improving Plutonium Management at the Los Alamos National Laboratory
  • Ryan Goddard '13. Computer Science Major/ Faculty Mentor: Lisa Torrey - Artificial Intelligence for Conversational Agents
  • Johanna Kelley '13. Mathematics Major / Faculty Mentor: Michael Schuckers - Ridge Regression, LASSO Regression, and Ordinary Least Squares Regression in Evaluating Collinear NHL and Fantasy Football Data

Summer 2011

  • Jim Curro '12. Mathematics Major / Faculty Mentors: Michael Schuckers and Ed Harcourt - NHL Statistical Analysis on Expected Value of Players
  • Shelley Kandola '13. Computer Science and Mathematics Major /Faculty Mentor: Lisa Torrey - Simple and Efficient Compact Graph Generation for Geochemical Data