Graduate Research Assistant
Virginia Tech, Mining & Minerals Engineering
I am a passionate and driven mathemetician, computer scientist and manager. Through my diverse professional experience, I have a honed a unique skillset that allows me to be comfortable researching complex computational mathematics and engineering problems and communicating that research in both a strategic and technical manner.
Virginia Tech, Mining & Minerals Engineering
Virginia Tech, Department of Mathematics
SUNGARD
RRI/SUNGARD
United States Navy, USS Boise (SSN 764)
Ph.D. in Mathematics
Virginia Tech
Master of Science in Mathematics
Virginia Tech
Bachelor of Science in Computer Science
Virginia Tech
Nominated by the Department of Mathematics for the annual award given to top graduate teaching assistant in an instructor of record position.
Given annually to the top graduate teaching assistant assigned as a teacher of record in the department, this award is based on student evaluations, faculty observations and student performance.
Given annually to the top graduating senior in Computer Science, Mathematics, or Statistics
Given annually to the most improved graduating senior in the Department of Computer Science at Virginia Tech.
Inducted Spring 2001.
Inducted Spring 2001.
Inducted Fall 2000.
Mentored new graduate students through the departmental teaching certification process. Instructed on the design of lesson plans and improvements for lecture presentation.
Job duties included acting as a mentor to fellow graduate students, organizing seminars for professional development and teaching improvement, running a peer mentor program for graduate teaching assistants, and assisting with the recruitment and orientation of new graduate teaching assistants.
Helped lead a workshop each fall titled "Teaching Confidence" aimed at instilling confidence in teachers allowing them to create confident learners.
Efficient real-time computational solutions for large-scale dynamical systems are critical in many areas such as control systems, prediction algorithms, decision-making tools, and stochastic algorithms, to name a few. These systems arise from mathematical partial differential equation models for many of the biological and physical processes of concern. Simplifications to the model domain, physics, or computational resolution often lead to computationally tractable solutions at the expense of model accuracy. In order to reduce the computational demands while maintaining the accuracy of the model, we look to mathematical model order reduction. In particular, these methods retain the underlying physics of the problem while allowing for much faster computational times for the models.
My research has focused on model reduction for large-scale nonlinear dynamical systems. For example, we have looked at ways to create input-independent model order reduction techniques. We have also looked at ways to extend the proper orthogonal decomposition (POD) technique by combining it with input-independent rational Krylov methods. We are also investigating methods of operator splitting in order to tackle the linear and nonlinear methods separately and more efficiently
Far from operating in a mathematical vacuum, we have actively sought real-world applications for these model reduction techniques. For example, we have applied this to building and mine airflow models, mine fire models, wildland fire models, and reaction kinetics models. The exciting aspect of this research is its applicability to so many different types of models.
I have been very fortunate in my academic career to work with exceptional mathematicians, scientists, and engineers. As an applied mathematician, I find that collaboration with knowledgeable experts across disciplines is instrumental to project success. These mentors have taught me not only aspects of their own research, but how to work together to solve problems that are beyond the capacity of one person to address.
At its core, teaching is simply the transfer of knowledge from one person to another. However, exceptional teaching occurs when one considers all the factors, both internal and external to the classroom, that affect the instructor’s ability to transfer that knowledge. Each semester I am assigned a course and given the task to teach mathematics to a group of students; more importantly, I am actually given the opportunity to shape the arc of learning for each of my students. If I cultivate a student’s thirst for knowledge, and develop a student’s confidence in learning, then the transfer of knowledge becomes simple. Further, by focusing teaching on the student, instead of the information itself, the student often undergoes a significant paradigm shift from passive to active learner that extends beyond the course that I am teaching.
Throughout my time as a graduate teaching assistant, I have had the opportunity to be the instructor of record for many different courses, ranging from the freshmen to senior undergraduate level. Further the class sizes have ranged from small classes of just a few students up to lectures given to as many 75 students. This varied experience has helped me to hone my skills as a teacher and motivator. These courses have allowed me the opportunity to create lesson plans, homework assignment, and tests. I have experience grading and assigning grades. Most importantly, it has given me a chance to work with students directly during office hours and help session. Because of this experience, I am a seasoned teacher prepared to teach at all levels of a college curriculum
Developed course contracts, determined classroom administrative policies, wrote homework assignments, prepared detailed lecture notes, wrote all tests and exams, assisted students during office hours, and assigned course grades for the following courses:
I have have been fortunate in my professional career to have had the opportunity to perform a wide variety of jobs. This diverse set of experiences includes training people to run nuclear power plants, being a nuclear chemist, developing high-performance data capture software, managing a group of software developers, and studying computational mathematics. Each of these positions helped shape my professional career in a positive way. Today, I have the technical acumen to perform leading edge computational mathematical research coupled with the social and communication skills to convey how that research can change the world.
I am passionate about my work. I am extremely dedicated to success in whatever job I am currently doing. I set high standards for myself and expect to achieve at that high level. I enjoy the challenge of new job roles and am always willing to take on different tasks as the need arises in a company. However, I am cautious to first understand the history and current state of those roles, before charging forth with a new plan. Once I have taken the time to understand the past and the present, I push confidently forward to the future. I am excited to move forward in the next phase of my professional. Whether I continue in my current research or pursue other exciting endeavors, I am confident that my varied experience has laid the groundwork for future success.
I believe that collaboration and conversation are critical to success in the field of applied computational mathematics. While seemingly outdated in the world of social media, I still feel the most important work is accomplished via one-on-one conversations. If you are curious about my research, intrigued by my teaching, or just want to talk over a cup of coffee, get in touch with me. I would love to have a conversation.
I have two offices on the campus of Virginia Tech, the Wright House and 463C McBryde Hall. I am almost always in one of those offices from noon to 2:00. I have flexibility to meet at other times, so feel free to contact me and I can meet you at a time and place that is convenient.
I usually work at the Interdisciplinary Center for Applied Mathematics (ICAM), located in the Wright House, during the evenings. If that is the best time for you to meet, let me know.
I spend every morning at the coffee shop working on my research. I love getting together with people to discuss their current research and to share my work. My favorite times are when the conversations lead to our research being pushed forward because we found new ways to look at our own work. So come grab a cup of coffee with me and let's find some common ground.