Speaker: Palle Jorgensen, Dept. of Mathematics

Speaker: John Manak, Depts. of Biology and Pediatrics and the Roy J. Carver Center for Genomics

Speaker: Laurent Jay, Dept. of Mathematics

Speaker: Shaoping Xiao, Dept. of Mechanical Engineering

Speaker: Caglar Koylu, Department of Geographical and Sustainability Sciences

Speaker: Buddhika Nettasinghe, Dept. of  Business Analytics

Speaker: Jun Wang, Department of Chemical and Biochemical Engineering

Speaker: Ann Campbell, Dept. of Business Analytics

Speaker: Qihang Lin, Dept. of  Business Analytics

Speaker: Wayne Polyzou, Dept. of Physics and Astronomy

Speaker: Yannick Meurice, Dept. of Physics and Astronomy

Speaker: Xueyu Zhu, Dept. of Mathematics

Speaker: Yangbo Ye, Dept. of Mathematics

Speaker: Rodica Curtu, Dept. of Mathematics

Speaker: Isabel Darcy, Dept. of Mathematics

Iñigo Urteaga (Columbia University) on "Probabilistic machine learning for predictive models of mobile health data: a use case on menstrual cycle length prediction"

Speaker: Palle Jorgensen, Dept. of Mathematics

Speaker: Yannick Meurice, Dept. of Physics and Astronomy

The symposium will be held at the University of Northern Iowa, Maucker Union, Rooms A & B for those who want to attend in person and online via Zoom for anyone who wants to attend virtually. You must register to receive the link to the virtual event. Registration is free and open to industry professionals, academic faculty and students interested in the fields of data science, analytics, computer science, statistics, mathematics, engineering, and business. University of Iowa Computer Science...

Speaker: Weimin Han, Dept. of Mathematics

Speaker: Mathews Jacob, Dept. of Electrical and Computer Engineering

Speaker: Tong Wang, Dept. of Business Analytics

Speaker: Atulya Iyengar, Dept. of Biology

Speaker Yueqi Chen Abstract Despite significant efforts on cybersecurity, we are observing an increasing number of attacks in recent years. The reason for this harsh reality is all our efforts aim at individual incidents and there is no deep understanding of attack surfaces in software systems. As a result, software systems are integrated with too many individual patches and ad-hoc mitigations, which slows down systems significantly without introducing substantial security benefits. In this...

Speaker: Zahra Aminzare, Dept. of Mathematics

Speaker: Beste Basciftci, Dept. of Business Analytics

Speaker: Yangyang Wang, Department of Mathematics

Speaker: David Stewart, Department of Mathematics

Speaker: Ariel Aloe, Department of Psychological and Quantitative Foundations

Speaker: Xueyu Zhu, Department of Mathematics.

Speaker: Shaoping Xiao, Department of Mechanical Engineering

Speaker: Laurent Jay, Department of Mathematics

Abstract This talk will focus itself on games. Some basic games will be introduced and their strategies analyzed. We will scratch the surface of combinatorial game theory, a lovely, playful, and often overlooked branch of mathematics. In the process we will stumble upon the surreal numbers and explore the very nature of “numbers”. This talk will be accessible for all audiences. There is no prerequisite knowledge needed, just an open mind. We will have milk and cookies! Remember to bring your...

Speaker Marco Gaboardi (Boston University) Abstract Data analysts aim at guaranteeing that the result of a data analysis run on sample data does not differ too much from the result one would achieve by running the analysis over the entire population. To achieve this goal, they have developed several techniques to control the generalization errors of their data analyses. In this talk, I will discuss how programming language techniques can help data analysts to design adaptive data analyses...

Speaker Yingyu Liang Abstract An important characteristic of neural networks is their ability to learn representations of the input data with effective features for prediction, which is believed to be a key factor to their superior empirical performance. To better understand the source and benefit of feature learning in neural networks, we consider learning problems motivated by practical data, where the labels are determined by a set of class relevant patterns and the inputs are generated...

Abstract We introduce quivers, path algebras and their representations. Then, in the case when our ground field is algebraically closed, we discuss a particular Morita invariant of path algebras arising from finite quivers, the Ext quiver of the category. Through examples we see how to compute the Ext quiver using quiver representations and techniques from linear algebra. We aim to keep the talk accessible to undergraduate and graduate students alike. Speaker Ryan Bianconi UI Mathematics PhD...

Abstract From a summer REU at the University of Minnesota, we constructed a solvable lattice model for the dual weak symmetric Grothendieck polynomials in hopes of using such a model to prove related properties of these polynomials, including Cauchy identities and branching rules. We also considered a similar lattice model construction for the weak symmetric Grothendieck polynomials in hopes of proving a Cauchy identity, concluding with a negative result. Moreover, we expand on previous work by...

Abstract Digital signatures are an important feature in any encryption/decryption scheme, as it provides a message with integrity, authenticity, and nonrepudiation. The problem occurs when long messages are being exchanged and signatures that are just as long need to be verified. By using hash functions, a ”fingerprint” of the message can be used instead of the message itself for verification, making the process computationally inexpensive. If we consider a single iteration of a general hashing...

Speaker John Reppy Abstract The analysis of structure in three-dimensional images is increasingly valuable for biomedical research and computational science.  At the same time, the computational burden of processing images is increasing as devices produce images of higher resolution (e.g., typical CT scans have gone from 128^3 to roughly 512^3 resolutions).  With the latest scanning technologies, it is also more common for the values measured at each sample to be multi-dimensional rather than...

What we know, what we don't, and where we're going Every ten years, the Census Bureau conducts the Census, a nation-wide tallying of every single individual living in the United States. In addition to helping governments and researchers manage land, understand population trends, and distribute resources, the Census is essential to a key democratic function: drawing electoral districts. The process of drawing electoral districts, called “redistricting,” divides every state in the United States...

Speaker: Ariel Aloe, Dept. of Psychological and Quantitative Foundations Topic: Evidence synthesis and meta-analysis

Speaker: Yannick Meurice, Dept. of Physics & Astronomy Topic: Finding the boundary of quantum advantage for quantum field theory

Speaker: Jia Lu, Department of Mechanical and Industrial Engineering Topic: What machine learning can tell us about tissue rapture

Speaker: Vincent Rodgers Topic: Gauged Projective Geometry in Gravitation

Speaker: Shaoping Xiao, Department of Mechanical Engineering Topic: Motion Planning in Robotics by Using Reinforcement Learning with LTL Constraints Abstract: High-level robotics motion planning requires the robot to accomplish complex tasks instead of simple go-to-goal navigations. This seminar presents a research topic of motion planning in robotics via the integration of reinforcement learning (RL) and linear temporal logics (LTL). The framework consists of a Markov decision process (MDP)...

Speaker: David Stewart Topic: TBA

Speaker: Weimin Han Topic: Boundary Value Problems of Partial Differential Equations: Weak Formulation and Numerical Solution

Speaker: Tong Wang, Dept. of Business Analytics Topic: Hybrid Predictive Model: When an Interpretable Model Collaborates with a Black-box Model

Speaker: Nicholas Yannelis, Dept. of Economics Topic: Contracts under Asymmetric Information

Speaker: Mathews Jacob, Dept. of Electrical and Computer Engineering Topic: Learning algorithms for next-generation computational MRI