For Prospective Students

In my research I borrow from various mathematical disciplines to create algorithms that process changing data from various engineering problems. How do you define where a “jet stream” in an ocean starts by looking at wave heights? When is a stirring device truly mixing a dye and when is it just sloshing it around? How do we distinguish irregular data due to a deterministic chaotic dynamics from just random noise?

I am looking for students who are interested in working on questions like these. Good matches will be those students who are comfortable with a programming language, e.g., MATLAB, who like to think about concrete problems, but who are also not afraid to think abstractly and engage with theoretical questions when needed.

For Undergraduates

Future engineers and mathematicians should have enough prerequisites to start working with me, but I am definitely open to working with anyone who fits the description above. In working with me I will give you enough structure so you don't feel lost, while at the same time leaving avenues open for your creativity and interests.

I am happy to talk to you more about my research if you are already Clarkson undergraduate. There is no lower-bound for starting research  —  you're welcome to contact me even if you are in Clarkson School or a 1st year student (even if you are in a Potsdam/Canton high school!). However, if you are graduating within less than 9 months, we likely won't have enough time together to start a meaningful research project. The exception are those Seniors who wish to enroll in Clarkson's PhD program, in which case see below.

For Prospective Graduate Students

If you are considering applying to Clarkson University's PhD program and are interested in my research, please indicate so in your cover letter and/or in your statement of interest. This will ensure that your application is brought to my attention  —  there is no need for separate e-mails to me. I cannot provide you with any “inside” information during the application process.

A successful applicant to Clarkson's PhD program will have a strong quantitative background, preferrably majoring in mathematics but other disciplines will be considered if there is sufficient coursework to back you up. Evidence of independent learning is always good to have, for example either undergraduate research project, thesis, or other experience outside the classwork mainstream. In seeking out professors to write letters of recommendation for you, find those who can positively speak to your in-class skills, independent learning projects, and potential for research.