College of Science Research Exploration Courses
Expand Your Horizons.
Exploratory research courses are a terrific opportunity for College of Science students to delve into uncharted areas, enabling you to apply theoretical knowledge in practical settings while developing essential research skills. Engaging in exploratory research cultivates a sense of curiosity and adaptability, allowing you to refine your interests and identify potential career paths.
The collaborative nature of these courses promotes teamwork and communication, equipping you with the interpersonal skills necessary for success in both academic and professional environments. These experiences not only enhance your academic portfolios but also prepare you to tackle real-world challenges with confidence and innovation.
Explore the course offerings below to get started.
Course Title: Exploring Research in Speech, Language, and Hearing Sciences
Instructor: Robin Samlan (rsamlan@arizona.edu)
Research topic: Students in this participatory research experience will determine how voice and hearing differ between young and older adults. They will (1) record voice and conduct hearing screenings in college students; (2) record sound levels across their typical environments; (3) make acoustic measures of voice, kinematic measures of vocal fold vibration, and tabulate results of hearing status; and (4) compare results to those of older adults. Students will then consider how noise levels in a college environment influence both vocal and hearing health, identifying evidence-based recommendations for preserving voice and hearing.
Example activities: Acoustic recordings and acoustic voice analysis; Observing high-speed video recordings of vocal fold vibration and kinematic analysis of the recordings; Hearing screening; Measuring sound levels in the environment; Administering and scoring patient-reported-outcomes measures; literature search.
Prerequisites: None.
Course meeting times: W, 9:00-10:45 am. Students will spend additional time in the lab collecting data.
Course number: SLHS 392-068 (3 credits). Please obtain instructor permission to enroll in the course by emailing Dr. Robin Samlan at rsamlan@arizona.edu
Course location: SLHS 229
Course Title: Building and Programming Scientific Instruments for the Life-Sciences
Instructor: Ingmar Riedel-Kruse (ingmar@arizona.edu)
Research topic: Students will learn how to build, program, and operate simple scientific instruments, machines and robots – and how to use such robots to execute biology or chemistry experiments. We will be using the educational Lego robotics technology. Students will initially be introduced to the accessible Scratch programming language, as well as basic mechanical construction principles, motors, actuators, and liquid handling in the life-science. Another focus is on experimental design and performance characterization of scientific instruments. Based on interest, students can then choose to deepen their skills in one or more of different areas, such as python programming, engineering simple and complex machines, or designing and running their own scientific investigations on such devices. Students will also learn to document their progress in scientific notebooks, and how to write a final report. Students will typically work alone or in pairs.
Prerequisites: None. Students must bring a suitable laptop (typically, any laptop will do, and we can help in case of need).
Course meeting times: A significant part of instruction will take on place on some dedicated dates, e.g., weekends or evenings, rather than being spaced equally over the semester. This will allow for a more concentrated and naturalistic research experience. We also intend to enable students to work independently on their own time in the lab. Further details on logistics to be decided.
Course number: MCB 392 – 016 (3 credits). Please obtain instructor permission to enroll in the course by emailing Dr. Ingmar Riedel-Kruse at ingmar@arizona.edu
Course location: TBD
Course Title: Practical Introduction to Particle Physics
Instructor: Navin Mcginnis (nmcginnis@arizona.edu)
Research topic: From the ancient Greeks’ quest to understand fundamental aspects of matter to the groundbreaking discoveries of today, this course explores the fundamental particles of the universe. Dive into the heart of modern physics with the Large Hadron Collider, where high-energy collisions uncover quarks, leptons, and the fundamental forces that govern them. This course will introduce students to the landscape of modern particle physics research and will develop quantitative skills necessary to contribute to this field such as data analysis and theoretical interpretation of high-energy particle collisions. Using real data from the Large Hadron Collider we will explore hands-on projects to learn the tools and methods used by physicists to continue the age-old pursuit of understanding the building blocks of reality.
Example activities:
- Numerical programming projects for physics problems
- Hands on experience with data analysis used in modern particle physics research
- Analyze actual data sets of particle collisions from the Large Hadron Collider
- Communicating scientific results through oral presentations
- Introduction to AI in particle physics
Prerequisites:
Calculus-based Physics 1; Calculus 1; High school level Linear Algebra; Previous computer programming experience will be useful but not necessary.
Course meeting times: MW, 2:00 - 3:30pm.
Course number: PHYS 392-008 (3 credits). Please obtain instructor permission to enroll in the course by emailing Dr. Navin Mcginnis at nmcginnis@arizona.edu
Course location: TBD
Course Title: Introduction to Neural Networks and Their Math
Instructor: Arvind Suresh (arvindsuresh@arizona.edu)
Research topic: This course will provide a gentle introduction to neural networks, the machine learning models that form the basis of modern AI’s like ChatGPT. We will analyze some datasets, ask natural questions, and develop the necessary math (from probability theory, linear algebra, and vector calculus) to understand them. Classes will have a blend of math and programming, culminating in a machine learning final project (implemented in Python). By the end of the course, the students will be empowered to delve into a deeper study of neural networks and research ways to train and improve them.
Example activities: Students will learn the required math concepts from linear algebra, vector calculus, and basic statistics/probability, followed by hands-on implementation of machine-learning models.
Prerequisites: MATH 223 (can potentially be waived if student has sufficient experience with multivariable functions or matrices and vectors)
Course meeting times: MW, 11:00am – 12:15pm.
Course number: MATH 392-001 (3 credits). Please contact math-academics@arizona.edu to obtain assistance in enrolling in the course.
Course location: TBD
Course Title: Introduction to Mathematical Modeling in Water Science
Instructor: Jicai Zeng (jicai@arizona.edu)
Research Topic: Are you curious about how math can solve real-world problems, especially in water-related fields? Enroll in "Introduction to Mathematical Modeling" and discover how math helps us understand and solve challenges like predicting floods, managing water resources, and protecting drinking water. You'll learn hands-on techniques to tackle these real-world issues—no advanced math background is needed! By the end of this adventure, you'll be a mathematical modeler, ready to build your own models and answer pressing research questions.
Example activities:
- Students will pick up basic programming skills in MATLAB during the course.
- Hands-on prototyping of a mathematical model using the state-of-the-art modeling tool in simple steps.
- Design a simple water flow process and use the developed mathematical model to simulate it.
- Use the developed mathematical model and real data to estimate missing parameters.
- Give short oral presentations about the problem-solving process.
Prerequisites:
This course is designed for students with basic knowledge of Calculus 1—a strong interest in mathematical modeling and programming. Programming experience with MATLAB is a plus, but not required; students will pick up basic programming skills during the class.
Course meeting times: MW, 9:30-10:45am.
Course number: HAS 392-010. Please obtain the instructor's permission to enroll in this course by emailing Dr. Jicai Zeng at jicai@arizona.edu.
Course location: JW Harshbarger 203