(last week of classes)
Rina Akiyama (Kaleigh Rudge)
Tyler Han (Mitch Majure)
Weixi Chen (Minghao Zhao)
Nathan Lin (Josiah Lim)
Sahana Raja (Ben Brindle)
Ian Ruiz (Rui Chen)
Timothy Ventura (Kaleigh Rudge)
Hailey Yim (Barbara Fiedorowicz)
Tiger Ni (Ben Brindle)
Nora Zhang (Ben Brindle)
David Luna (Ben Brindle)
Jonlucas Loredo (Ben Brindle)
Sri Nippani (Ben Brindle)
Lingxi Kong (Aaron Zoll)
Darius Kim (Aaron Zoll)
Full Project Proposals with detailed abstracts can be found here.
Lie groups beyond an introduction
Mentor: Rui Chen
Mentee: Ian Ruiz
Prerequisites: Required: some group theory
Introduction to p-adic Analysis
Mentor: Mitch Majure
Mentee: Tyler Han
Prerequisites: Required: calculus 2. Recommended: topology and algebra
Positivity in algebraic geometry
Mentor: Minghao Zhao
Mentee: Weixi Chen
Prerequisites: Recommended: intersection theory and birational geometry
(No specific topic, will be paired with student of similar interest)
Mentor: Barbara Fiedorowicz
Mentee: Hailey Yim
Interests: Combinatorial Optimization, Graph Theory, Combinatorics, Optimization Algorithms (Branch and Cut, Max Flow, etc.), Applications in Electrical Engineering and Physics
Exploring Numerical Methods
Mentor: Kaleigh Rudge
Mentees: Rina Akiyama, Timothy Ventura
Prerequisites: Required: calculus. Recommended: programming and differential equations
Quantitative Interview Questions
Mentor: Ben Brindle
Mentees: Sahana Raja, Tiger Ni, Nora Zhang, David Luna, Sri Nippani, Jonlucas Loredo
Prerequisites: Required: calculus, linear algebra, probability, and statistics. Recommended: programming and stochastic processes
What Makes Gradient Descent Work (well)?
Mentor: Aaron Zoll
Mentees: Lingxi Kong, Darius Kim
Prerequisites: Calculus 3 and linear algebra
Convolutional Neural Networks for Medical Imaging
Mentor: Josiah Lim
Mentees: Nathan Lin
Topic self proposed by mentee
Full Project Proposals with detailed abstracts can be found here.
Organizers: Ben Brindle (AMS)