University of Vermont
I am currently a lecturer (adjunct) in the Department of Computer Science, in the College of Engineering and Mathematical Sciences at the University of Vermont. In spring semester 2021, I am teaching CS 124 Data Structures and Algorithms. In the past, I have taught CS 021 Introduction to Programming.
I have completed all requirements for a master’s degree in computer science under the supervision of Dr Alan Ling, and will graduate in May of 2021. While at UVM, I have served as a graduate research assistant in bioinformatics under Dr Hosna Jabbari, and graduate teaching assistant for CS 124 Data Structures and Algorithms, CS 125 Computability and Complexity, CS 166 Principles of Cybersecurity, CS 222 Computer Architecture, and CS 243 / MATH 243 Theory of Computation.
Courses

Computer science: data structures and algorithms, algorithm design and analysis, computability and complexity, theory of computation, combinatorial algorithms, computer architecture, machine learning, theory of programming languages, and deep learning.

Complex systems: bioinformatics algorithms, evolutionary computing, and modeling complex systems.

Mathematics: calculus, fundamentals, combinatorial theory, combinatorial graph theory, probabilistic combinatorics and random graphs, linear algebra, abstract algebra, geometric combinatorics (matroids and polytopes), topology, and complex analysis.

Philosophy: logic.
Projects and papers
 TripleGAN architecture for generation of music samples by genre (in process), Amanda Bertschinger, CC.
 New generator for RáczBubeck random graphs projected on hypersphere for NetworkX (in process), CC.
 Convolutional neural network for detection of saxophone in jazz ensemble context, Matthew Thompson, Brandon Gamble, CC, 2020.
 Multiparadigm modeling of Snf3Rgt2 glucosesensing pathway in Saccharomyces cerevisiae, Amir Barghi, CC, Michael Gilbert, 2019.
 Building a genetic algorithm to evolve a cellular regeneration mechanism, Caitlin Grasso, Connor Klopfer, CC, 2019.
 Replicating and testing an analysis pipeline for identifying structurally conserved RNAs, CC, Hosna Jabbari. Submitted to ACMBCB 2019 (rejected).