Samuel Byars- Sam worked with AI-Learners (https://ai-learners.com/), a Math tech company started by former Brooklyn Tech Mathematics Major Adele Smolansky ’19 that is designed to make math more accessible to elementary school students through personalized computer games and analytics.

Yihan He- Yihan created a YouTube channel to design math videos using animation and graphics to help explain complex math like Graph Theory, Number Theory, and other sophisticated math concepts.

Luke Opalack- Luke also worked with AI-Learners with the goal of spreading love for math.

Charlie O'Sullivan- Charlie also worked with AI-Learners, with a focus on helping children with disabilities learn math through AI games.

Lucas Papamitsakis- Lucas built his own Deep Learning and Mathematical Models to predict Multiple Sclerosis (MS) development based on MS patients' data and MRI scans. He worked with a Convolutional Neural Network, which helped him gain experience in Gradient Descent and Multivariable Calculus, as they are vital to maximize accuracy. Linear Algebra and Statistics will play a large role in feeding data into the model.

Sabina Wolfe- Sabina is involved in the Lang Science Program, which is a partnership with the American Museum of National History. As a part of this program, Sabina took classes instructed by scientists and work with mentors on research projects that are presented at an end-of-year symposium. In particular, last summer, Sabina participated in a field research intensive in mathematics, spending 30 hours/week at the Museum. Sabina was also involved with the FRESH (Fordham Regional Environmental Sensor for Healthy Air) Air Project, a citizen science initiative started by Fordham professor Stephen Holler, which focuses on the disproportionate asthma and respiratory disease rates of children in lower income public schools in all five boroughs. Results were monitored by Sabina and she developed curricula around the collected data.