• Properties of redistricting Markov chains (Sarah Cannon, CMC)

    Davidson Lecture Hall, CMC 340 E 9th St, Claremont, CA, United States

    Markov chains have become widely-used to generate random political districting plans. These random districting plans can be used to form a baseline for comparison, and any proposed districting plans that […]

  • Frequentist Model Averaging in the Generalized Multinomial Logit Model (Prof. Tonia Zeng)

    Humanities Auditorium, Scripps College, and Zoom Claremont, CA, United States

    Title: Frequentist Model Averaging in the Generalized Multinomial Logit Model Speaker: Tonia Zeng, Applied Business Sciences and Economics, University of La Verne Abstract: The generalized multinomial logit (GMNL) model accommodates scale heterogeneity to the random parameters logit (RPL) model. It has been often used to study people's preferences and predict people's decisions in many areas, […]

  • Applied Math Seminar: Anna Nelson (Duke)

    Shanahan 2407 at Harvey Mudd College Claremont, CA, United States

    Title: Mathematical modeling of polymerization processes in physiology Abstract: Polymerization, or aggregation, is essential for many physiological systems. For example, the emergence of a fibrin polymer mesh during the formation of […]

  • Prof. Josiah Park

    Humanities Auditorium, Scripps College, and Zoom Claremont, CA, United States

    Title: Packing lines, minimizing energy, and applications to communications Speaker: Josiah Park, Department of Mathematics, Texas A&M University Abstract: Structured geometric point sets play important roles in coding theory, mathematical biology, computational chemistry, wireless communications, compressed sensing, and 'big data' applications due to their often desirable statistical properties for measurement and transmission. Best packings of […]

  • GEMS November 5th Session

    Shanahan 1480, Harvey Mudd College 301 Platt Blvd., Claremont, CA, United States
  • The Sceptical Mathematician: How John Wallis Saved Mathematics for the Royal Society (Amir Alexander, UCLA)

    Fletcher 110, Pitzer College 1050 N Mills Ave, Claremont, CA, United States

    The members of the “Invisible College” and the early Royal Society championed an experimental approach to the study of nature as the proper path to the advancement of knowledge and the preservation of civic peace. Mathematics, while admired, was also viewed with suspicion, as potentially dogmatic and coercive. John Wallis, the leading mathematician in the […]

  • Applied Math Seminar: Angel Chavez (Pomona)

    Shanahan 2407 at Harvey Mudd College Claremont, CA, United States

    Title: Randomized Sums of Graph Spectra Abstract: The adjacency matrix of an Erdős-Rényi-Gilbert graph is a random symmetric matrix whose entries are Bernoulli random variables. These entries, modulo the constraints […]

  • Prof. Edouard Oudet

    Humanities Auditorium, Scripps College, and Zoom Claremont, CA, United States

    Title: Shape Optimization: Old and New Speaker: Edouard Oudet,  LJK, Université Grenoble Alpes Abstract: We first introduce what is shape Optimization and the most classical problems of the field like the isoperimetric problem, the study of minimal surfaces, the characterization of irrigation networks, etc. In a second step we focus on a more recent question related […]

  • Norms on self-adjoint symmetric tensor power of linear operators on Hilbert spaces (Yunied Puig de Dios, CMC)

    Roberts North 105, CMC 320 E. 9th St., Claremont, CA, United States

    We introduce a family of norms on the space of self-adjoint trace class symmetric tensor power of linear operators acting on an infinite-dimensional Hilbert space. Our technique is to extend to infinite dimension an original and nice idea of a very recent result by K. Aguilar,  Á. Chávez, S. R. Garcia and J. Volčič, in […]

  • Applied Math Seminar: Jahrul Alum (Memorial University of Newfoundland)

    Shanahan 2407 at Harvey Mudd College Claremont, CA, United States

    Title: Data-driven large eddy simulation of atmospheric turbulence Abstract: Over the last few years, machine learning has been critical in science and engineering and emerged as a data-driven turbulence model. […]