User talk:Ben G. Fitzpatrick
Hi Dr. Fitzpatrick, Sorry it's taken so long for me to leave you a message, I was wondering what was your favorite aspect of math that you've studied? I ask only because I'm interested in exploring my math minor. Nicholas A. Rohacz 18:43, 24 January 2011 (EST)
Hey there Dr. Fitzpatrick! How did you become interested in biology and math? What inspired you to teach both? Sarah Carratt 16:58, 16 January 2011 (EST)
- Ben G. Fitzpatrick 17:18, 16 January 2011 (EST) My dad's a veterinarian, so I have long experience in "applied biology," especially biological waste products. I went to college planning to study engineering, but I found math (and the math professors) a lot more interesting. I returned to an interest in biology as a grad student. My adviser was collaborating with some biologists and agricultural engineers, and those problems were very cool. When I came to LMU, the math department was eager to re-energize biomathematics, and the faculty in bio seemed interested in collaborating. In both disciplines, puzzling out the structure and function of things is at the heart of inquiry. Such questions always seem to draw me in. Bringing biology concepts into math courses seems very natural to me in that regard.
Hello Dr. Fitzpatrick! I was wondering what was your hardest math class as an undergrad? Carmen E. Castaneda 08:38, 16 January 2011 (EST)
- Ben G. Fitzpatrick 13:52, 16 January 2011 (EST) Math 520 at Auburn, Real Analysis, like our 321, was the hardest, at least for the first 4 weeks. The course was taught by Professor Ed Moise in the R. L. Moore style, so that the teacher provided definitions, problems, and theorem statements ONLY. Students had to work out the proofs, detect incorrect theorems and provide counterexamples, and solve the problems. The library was off-limits. I had taken a year of modern algebra before this course, so I have some sense of proof (we didn't have a 248 equivalent). It took me a while to get the hang of it, but after taking two years of (undergrad and grad) real analysis this way, I found it very helpful in my future work.
Hi Dr. Fitzpatrick! I was wondering how many women were studying Math when you were an undergrad and/or in grad school?Alondra Vega 12:01, 16 January 2011 (EST)
- Ben G. Fitzpatrick 13:52, 16 January 2011 (EST) My undergraduate class was about 25% women, and the grad program at Auburn (where I got my master's) was about the same. The strongest student in that program (by far) was a woman who was hired onto the Auburn faculty after getting her PhD. It's pretty unusual for a department to hire one of its own grads. In my PhD studies we had very few women, probably around 10% of the students. In my previous faculty positions, there were not so many women. At UT Knoxville, I worked a lot with Suzanne Lenhart, who was pretty much my mentor when I was starting out as a fresh assistant professor. She's a great mathematician, a great person, and a super role model for anyone in the profession. If you were to change your mind about nursing and get interested in biomath grad programs, I'd have you get in touch with her.
Hello Dr. Fitzpatrick. What do you think future has in store for biomathematicians? Thanks, James C. Clements 00:34, 17 January 2011 (EST)
- Ben G. Fitzpatrick 02:05, 17 January 2011 (EST) Wowsers, that's a tough one. Folks at the interface of computer science, applied math, and molecular biology have a lot of work cut out for them. Sorting through all the genomics and proteomics data being collected, figuring out the interoperability of genes and proteins, that's going to keep people busy for awhile. Another area that is going to be very interesting is the brain. There are a lot of math/ee/bio people trying to understand how the brain works. I'll think about this matter and add more later... old people like me start to poop out at 11pm. Ben G. Fitzpatrick 11:39, 17 January 2011 (EST) A few more thoughts this a.m. For people who with impaired hearing or sight, for people with missing limbs, integrated approaches to connecting devices to the brain will require not only good engineering, but good science as well. The successful teams will have biologists, mathematicians, physicists, chemists, and engineers that are very capable of collaborating.