Courses Taught
Courses Taught
Introduction to Hardware & Algorithms of Quantum Computing - Graduate PHYS 85200-3. Theory and Use of Quantum Computers: hardware and how it works, algorithms needed to solve problems, applications in cryptography and machine learning.
Physics Applications of Machine Learning and Data Science - Undergraduate PHYS 270. A practical introduction to using machine learning to analyze experimental data and theoretical models in physics, chemistry, biology, and earth sciences. Provides contemporary skills valuable for careers in technology.
Introduction to Modern Physics - Undergraduate PHYS 260. Special relativity and quantum mechanics.
Physics for Computer Science 2 - Undergraduate PHYS 204. Networks, statistical physics, chaos, electricity & magnetism, electric circuits, quantum mechanics, quantum cryptography, quantum computing, encryption, quantum atoms, quantum materials.
The Science of Fractals and Its Applications - Undergraduate PHYS 8. Uses spreadsheets, graphs, algebra, numerical methods, folding pieces of paper, and in-class experiments to learn mathematical concepts and apply them to physical, biological, and social systems. Students build projects at the Queens College Maker Space as part of the NSF funded grant: An Interdisciplinary Design Program Incorporating Design-Make-Play Methods in Undergraduate General Education.
General Physics I - Undergraduate Lecture PHYS1214. Vectors, linear and circular motion, forces, gravity, energy, momentum, fluids, heat, and the applications of physics.
General Physics II - Undergraduate Lecture PHYS 1224. Electricity, magnetism, optics, special relativity, quantum mechanics.
General Astronomy Laboratory - Undergraduate ASTR 2.
General Physics II Laboratory - Undergraduate PHYS 122.
Principles of Physics I Laboratory - Undergraduate Physics PHYS 145.
Methods in Complex Systems - Graduate Interdisciplinary ISC 6450. Linear, parametric, non-parametric, and nonlinear analysis of experimental data: The stuff that they told you and that they didn't tell you in undergraduate statistics. This course helps you to understand the assumptions used in these statistical methods and which statistical methods are best for analyzing different types of data. Required for the Ph.D. program in Complex Systems and Brain Sciences.
Complexity for the Life Sciences - Graduate Psychology PSY 5930. Most things are made up of many pieces that interact strongly with each other. Yet much of science has tried to study things by tearing them apart and studying only their tiny separate, noninteracting pieces. Here we will learn how the science of "complexity" is able to help us see, analyze, and understand complex entities in physics, chemistry, biology, and psychology.
Fractals and Chaos for the Life Sciences - Graduate Interdisciplinary ISC 5451. Mathematics of fractals and chaos applied to cellular, physiological, and psychological systems.
Psychology and the Internet - Undergraduate Psychology PSY 4930. This course will: Tell you what the internet is, how it works, and how it came to be. Describe the social space and processes that happen over the internet and how the internet is changing social interactions, businesses, politics, and the military.
Fractals in Psychology - Undergraduate PSY 3502. How fractal methods can be used to analyze experimental data and gain a better understanding of the physiology and psychology of perception and behavior.
The Mathematics and Science of Fractals - Undergraduate Mathematics MAT 1932. Mathematics for undergraduate students who never liked and never did well in math.