Teaching and Mentoring Experience
Instructor
I teach Applied Analytics (AA), Information Systems and Analytics (ISA), and Data Science (DS) classes at Bryant University. I have experience teaching:
- AA 306: Data Mining for Effective Decision Making
- AA 640: Data Visualization and Text Mining
- ISA 330: Programming for Data Science
- MSDS 620: Natural Language Processing
Training
- First Year Teaching Techniques, Bryant University, 2024
- Equity-Minded Course Design, Bryant University, 2023
- ACUE Effective Teaching Practices, Bryant University, 2022-2023
- Project Advising 101: Early Career Faculty Workshop, WPI, 2021
- Future Faculty Workshop, Northeastern University, 2020
- Fundamentals of Scientific Teaching and Pedagogy, WPI, 2020
- Leaders Engaging in Advocacy and Diversity Program, WPI, 2020
- Supporting WPI in Effective and Equitable Teamwork Squad, WPI, 2019
- Student Support Network, WPI, 2017
- Graduate Teaching Assistant Training Seminar, WPI, 2016
- Leadership Seminar Series, UWEC, 2013
Research Mentor
My first research mentoring experience was for Math 380: Research Methods in Mathematics at UWEC in 2015. Since 2018, I’ve mentored 35+ students on the Emutivo research project at WPI. The student teams I’ve mentored on this project include:
- Katie Houskeeper, Dante Amicarella, Matthew Dzwil, “Named Entity Recognition”, Undergraduate Independent Study, B-C terms, 2021-2022
- Mairéad O’Neill, Nicholas Jurovich, Madeline Halley, Jyalu Wu, Brian Phillips, Lillian Garfinkel, “Deep Learning for Mental Health Screening using Smartphone Data”, Undergraduate Computer Science and Data Science Major Qualifying Project, A-C terms, 2021-2022
- Miranda Reisch (grad), Saskia Senn (grad), Soumya Joshi (postgrad), “Depression Classification with Transcripts”, Directed Research, Summer-D term, 2021-2022
- Nicholas Jurovich, Benjamin Litterer, Mahum Shah, Saitheeraj Thatigotla, “Passive Depression Screening with Text,” Research Experience for Undergraduates, Summer 2021
- Miranda Reisch (grad) and Katie Houskeeper (undergrad), “Data Collection and Curation”, Directed Research, D-B terms, 2021
- Kratika Agrawal (grad), Karthika Suresh (postgrad), Matthew Dzwil (undergrad), Junying Li (grad), “Text Generation, Anonymization, and Visualization”, Directed Research, A-D terms, 2020-2021
- Rimsha Kayastha, Veronica Melican, Hunter Caouette, Conner Bruneau, Miranda Reisch, “Mental Health with Machine Learning”, Undergraduate Computer Science and Data Science Major Qualifying Project, A-C terms, 2020-2021
- Rimsha Kayastha, Joshua Lovering, Nina Taurich, “Early Mental Health Uncovering”, Research Experience for Undergraduates, Summer 2020
- Adam Sargent, Joe Caltabiano, Myo Thant, Nicolas Pingal, Yosias Seifu, Yared Taye, “Mental Health Sensing Using Machine Learning”, Undergraduate Computer Science and Math Major Qualifying Project, A-C terms, 2019-2020
- Adonay Resom, Jerry Assan, Maurice Flannery, Yufei Gao, Yuxin Wu, “Machine Learning for Mental Health Detection”, Undergraduate Computer Science Major Qualifying Project, A-C terms, 2018-2019