REU: Mathematical, Statistical and Computational Methods for Problems in the Life Sciences

• The NSF-funded REU program, Mathematical, Statistical and Computational Methods for Problems in the Life Sciences, is an 8-week intensive program that actively engages undergraduate students in research projects designed to introduce students to mathematical, statistical, and computational methods in the study of life science problems.
• Students work individually or in groups of two or three under the supervision and guidance of three faculty mentors. The research projects cover a wide array of life science applications on the dynamics of populations, epidemics, organisms, cells, and proteins.
• The objectives of the program are to engage undergraduate students, especially those from underrepresented groups and academic institutions where research opportunities in STEM are limited, in innovative research projects; to expose them to active research environments; and to provide them with the necessary technical skills to do independent research.
• Through a series of educational and social activities, REU participants have opportunities to enhance their professional development and to form a network of partners among the participants and collaborators in the program. Faculty continue to mentor the REU participants after the 8-week program to guide them in writing their results for publication and to assist them as they transition into graduate school.
• The ultimate goal of the program is to motivate and inspire the REU participants to continue graduate study in mathematics, statistics, or a related field and to pursue academic or other research careers in STEM disciplines.
• The research projects of the REU 2021 program were held virtually. The program introduced undergraduate students to mathematical, statistical, and computational methods that enabled them to pursue independent research on current problems in the life sciences.
• Under the guidance of experienced faculty mentors, the student research projects built on current results and contributed to new mathematical, statistical, and computational methods, algorithm design, analysis, data collection, and implementation to address important and complex problems in the life sciences.
• Results from the research projects were disseminated through student participation in conferences and workshops and through publications in mathematical, statistical, and biological journals. In addition, code packages developed through the program were made available on the program’s website.

Poster Presentations

• Poster 1: Tick-Mouse Models for Lyme Disease with Seasonal Variation in Birth, Death, and Tick Feeding (PDF)
  REU students: Kateryna Husar, Ohio State University; Dana Pittman, Washington State University; Johnny Rajala, University of Maryland - College Park
  Mentor: Linda Allen
• Poster 2: Traveling Band Model for E. coli Transport in the Presence of Limited Immovable Food Using the Einstein Paradigm of Brownian Motion (PDF)
  REU student: Gillian Carr, St Mary’s College of Maryland
  Mentors: Akif Ibraguimov, Rahnuma Islam
• Poster 3: Finite Speed of Propagation in One Dimensional Degenerate Einstein Brownian Motion Model (PDF)
  REU student: Zac Bergeron, Kansas State University
  Mentors: Akif Ibraguimov, Isanka Garli Hevage
• Poster 4: Peaceman Model for Well-Block and Steady-State Einstein Paradigm of Brownian Motion (PDF)
  REU student: Jared Cullingford, TTU
  Mentor: Akif Ibraguimov
• Poster 5: Active Learning Based Error Sampling for High-Dimensional Nonlinear Partial Differential Equations (PDF)
  REU student: Wenhan Gao, Stony Brook
  Mentors: Chunmei Wang; Haizhao Yang, Purdue University
• Poster 6: Greedy Algorithms for Solving PDEs (PDF)
  REU student: Jasen Lai, Ohio State University
  Mentors: Chunmei Wang; Haizhao Yang, Purdue University
• Poster 7: Exploring Finite Element Methods with Numpy (PDF)
  REU student: Bryan Hatton, UCSD
  Mentors: Chunmei Wang; Gayani Balasuriya

Eligibility

• Continuing undergraduate student pursuing an undergraduate degree at a U.S. accredited university or college; current sophomore or junior level undergraduates preferred. An undergraduate degree should not be awarded prior to December 2021.
• A minimum of 3 semesters of calculus or equivalent mathematical training.
• U.S. citizen or permanent resident.

Stipend and Commitment

• Total of $4,400 ($550 per week)
• Commitment to 8 weeks

Student Application Requirements

The student application packet consists of completion of an online form and submission of the following items:

1. College transcripts
   Unofficial transcripts are acceptable. A legible scan of an official transcript is preferred.
   Your name and the institution’s name must be clearly displayed on the transcript.
   Official transcripts may be required upon admission to the program.
2. Resume
3. Cover letter including an essay of no more than two pages
   The essay should describe what you hope to gain from the REU experience and how this experience will contribute to the attainment of your future goals. In addition, provide an ordered list of the three research projects on which you prefer to work, with 1 indicating your preferred project. For your top two preferences, describe how these projects are appropriate to your mathematical or computational skills and interests.
4. Two reference letters
   Email contact information should be provided for two faculty members knowledgeable about the student’s research potential.

Applications from women and underrepresented minority students are welcomed and encouraged. Applications completed by April 15, 2021, will receive full consideration. Notification of awardees will be made by April 30, 2021, or until positions are filled.

Webmaster: giorgio.bornia@ttu.edu

Disclaimer: This material is based upon work supported by the National Science Foundation under Grant No. DMS-2050133. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.