Lale Asik

Dedicated and experienced college-level mathematics educator with a strong track record of integrating technology into curriculum design, instruction, and assessment. Committed to fostering inclusive, student-centered learning environments that support academic growth and engagement. Skilled in using innovative teaching strategies—including active learning, collaborative tools, and real-world applications—to promote deep understanding and long-term student success.

Foundational & Core Mathematics:

• College Algebra
• Precalculus
• Calculus I
• Calculus II
• Contemporary Mathematics
• Higher Mathematics for Engineers and Scientists I

Advanced Mathematics & Modeling:

• Differential Equations
• Mathematical Modeling
• Introduction to Numerical Analysis
• Introduction to Mathematical Analysis II

Statistics & Data Science:

• Introduction to Probability and Statistics
• Introduction to Data Science
• Capstone in Data Science

Computational & Interdisciplinary Courses:

• Computational Programming for Mathematics, Science, and Engineering

Applying the QM Rubric (APPQMR): Completed the Quality Matters Rubric course with a focus on online and blended learning quality assurance, accessibility, and instructional design best practices.

Mathematical and computational biology with a focus on ecological stoichiometry, disease ecology, and dynamical systems modeling of host–pathogen and environmental interactions.

• Member, Society for Industrial and Applied Mathematics (SIAM)
• Member, American Mathematical Society (AMS)
• Member, Mathematical Association of America (MAA)
• Member, Society for Mathematical Biology (SMB)
• Association for Women in Mathematics (AWM)
  • Committee Member, M. Gweneth Humphreys Award Committee (2025)
  • Reviewer, Student Chapters Award Selection Committee (2025)
  • Fact Checker, Notable Women in Mathematics Playing Card Project (2025)

Instructional Tools & Course Management:
Canvas, Blackboard, MyLab Math, WebAssign, WileyPLUS, LockDown Browser, WebWork, Gradescope

Engagement & Assessment Tools:
Desmos, GeoGebra, Poll Everywhere, Lessonspace, Kahoot, Proctorio

Mathematical & Statistical Software:
MATLAB, Maple, Mathematica, Python, R, MySQL, XPP/XPPAUT, SIAN, DAISY, Jupyter Notebooks

Data Science & Visualization:
Google Colab, Tableau, Excel

Document Preparation & Collaboration:
LaTeX, Overleaf, Git, GitHub, Microsoft Word, PowerPoint, Outlook, Zoom, Teams, Slack

Curriculum Development & Teaching:
Course design, syllabus development, classroom management, student needs assessment, inclusive pedagogy

• Provost's Legacy in Teaching Award – University of the Incarnate Word, 2022 & 2025
  Honored for outstanding teaching effectiveness, student engagement, and innovative pedagogy across undergraduate math and data science courses.
• Section Project NExT Fellowship – Mathematical Association of America, 2021
  Selected for a national professional development program focused on teaching excellence, mentoring, and student-centered course design

(Peer-reviewed research in mathematical biology and applied modeling, informing interdisciplinary and real-world instruction.)

• Van de Waal, D.B., White, L.A., Everett, R., Asik, L., et al. (2023). Reconciling contrasting effects of nitrogen on host immunity and pathogen transmission using stoichiometric models. Ecology.
  Focuses on nutrient-pathogen dynamics using ecological stoichiometry—supports integration of biology and mathematics in teaching.
• Saucedo, O., Laubmeier, A., Tang, T., Levy, B., Asik, L., et al. (2024). Comparative analysis of practical identifiability methods for an SEIR model. AIMS Mathematics.
  Applies mathematical tools to epidemiological modeling, relevant to courses in differential equations and public health math.
• Asik, L., Peace, A. (2019). Dynamics of a producer–grazer model incorporating effects of phosphorus loading. Bulletin of Mathematical Biology.
  Models aquatic ecosystems through differential equations—ideal for showing real-world applications in mathematical modeling classes.

• Nuur al-Hudaa B. Abdallah – HDR DSC: National Data Mine Network, Purdue University (Spring 2022)
  Project: House Price Prediction in San Antonio
  Guided a student through exploratory data analysis, machine learning modeling, and technical presentation. Focused on practical applications of data science in real-world contexts.
• Gabriella Valdez & Brenda Diaz Martinez – University of the Incarnate Word (Fall 2022)
  Project: Effects of Excess Food-Nutrient Content on the Coexistence of Competing Consumer Species
  Supervised an undergraduate research project on ecological modeling, system stability, and nonlinear differential equations. Emphasized interdisciplinary thinking and applied problem-solving.
• Alexa Garcia & Paula Shanahan – CIMA-LSAMP Summer Research Program, Alamo Colleges District (Summer 2021)
  Project: Pathogen-Mediated Nutrient Dynamics on a Discrete Time Scale
  Mentored students from underrepresented groups in STEM, supporting model development, simulations, and interpretation of mathematical biology systems under an NSF-funded initiative.Nuur al-Hudaa B. Abdallah, Spring 2022, House Price Prediction in San Antonio, Purdue University, West Lafayette, IN
• Gabriella Valdez & Brenda Diaz Martinez, Fall 2022, Effects of Excess Food-Nutrient Content on the Coexistence of Competing Consumer Species, University of the Incarnate Word, San Antonio, TX

• Dr. Zhanbo Yang
  Department of Mathematics and Statistics
  University of the Incarnate Word
  📧 yang@uiwtx.edu
• Dr. Suleyman Tek
  Department of Mathematics and Statistics
  University of the Incarnate Word
  📧 tek@uiwtx.edu
• Dr. Amanda A. Rakowitz
  Department of Mathematics and Statistics
  University of the Incarnate Word
  📧 arakowi1@uiwtx.edu
• Dr. Angela Peace
  Department of Mathematics and Statistics
  Texas Tech University
  📧 a.peace@ttu.edu