The Mathematics + Computer Science Seminar is a biweekly seminar highlighting research activities within the MCS Department at LTU.
Attendance is a requirement of "MCS 2111: MCS Seminar"
Machine Learning for Security and Security for Machine Learning
Speaker: Tao Liu
Abstract: In this talk, I will first introduce research topics on the intersection between Machine Learning and Cybersecurity, including Machine Learning for Security, and Security for Machine Learning. Research projects include Machine Learning based Malware Analysis, Adversarial Machine Learning, and Machine Learning powered Malware will be discussed to provide students with an in-depth understanding of these topics. I will then briefly introduce my other research works, supervised student projects, and cybersecurity teaching projects.
Data Science in Healthcare (Bioinformatics)
Speaker: Destiny Anyaiwe
Abstract: An important parameter in getting scholars to engage in research is basically their genuine interest in the subject. For undergraduate students, such interest could stem from affinity for a profession, area of interest for further studies, or type of job the student is aiming to get. Student advisors & supervisors also play a huge role in influencing students' interests. In this talk, I will take a moment to talk about myself as an advisor, my teaching ideology, my research and classroom environments. I will also take a look at areas of my research interest and some topics of recent students CRE and capstone projects. The talk will be concluded with a description of who 'an ideal research/senior project student' is to me, what I expect from them and what the future demands from our working together.
Introduction on AI applications in cyber physical systems (CPSs)
Speaker: Abdollah Kavousifard
Abstract: The threat of cyberattacks have motivated researchers to use Big Data and Artificial Intelligence (AI) to detect malicious activity and ensure the preservation of privacy and security. Within the smart grid and smart city concepts, AI techniques can be used to identify transactions that are likely to be fraudulent or compromised, as well as automate manually intensive data management tasks. My recent research activities involve applications of AI in electric grids to transportation systems, smart city, microgrids, electric vehicles, electric arc furnaces, industrial control systems (IDSs), renewable energy sources, and energy hubs. My talk will familiarize students with my research interests in the areas of advanced AI, cyber security, IDSs, and big data mining to facilitate possible future research collaborations.
Speaker: Yelena Vaynberg
Abstract: In this talk, I will introduce students to actuarial mathematics. I will explain what actuary science is and show the different mathematical computations involved. I will also talk about my Geometry in Art class and an interesting application. We will gain an understanding of the kind of research that is done in this area and how it is used to help Archeologists and Historians determine the age of excavated objects.
Speaker: Sharon M. Carter
Abstract: In this presentation I will discuss: who I am outside of the classroom, the evolution of my teaching career, my philosophy of Math Education, and projects with my students.
Research & Development Opportunities in ESE, Robotics, IoT, EC, AI, DL and STEM Education
Speaker: CJ Chung
Abstract: In this talk, I will introduce research & development project experiences in areas such as Embedded Systems/Software Engineering (ESE), Autonomous Robotics, Internet of Things (IoT), Evolutionary Computation (EC) including Cultural Algorithms, Evolutionary Neuro Fuzzy Systems, Deep Learning (DL), and STEM education since 1980 for over 40 years. Then future opportunities as well as in-class project ideas in those fields will be introduced.
Communication Between Math, History, Art in Architectural Buildings
Speaker: Wisam Bukaita
Abstract: The scope of the presentation incorporates a brief review of the research path and future research in addition to the in-class projects and modeling. A second-order non-homogenous differential equation is employed in my research papers to add the aesthetical and architectural views to the structural system and deliver the art of math in a real-life structural building. The modified differential equation provides a strong alternative to the most recent American Institute Steel Construction, AISC codes for structural engineers through a new derived alignment chart to facilitate the design process. Coding skills and 3D printing are functionalized to enhance learning in the classroom. Other alternative teaching methods are presented to combine playing games and practicing some of the theoretical concepts using virtual reality.
Extract Meaning from Text using Word Embeddings
Speaker: Paula Lauren
Abstract: In this talk, I will explain the use of word embeddings and how they are used to derive meaning from text. Word embeddings are a numerical representation of words (also known as distributional word vectors) based on word pair co-occurrences from a corpus. In addition, I will present an overview of some of my past, recent, and current research projects leveraging word embeddings in various computing tasks. Since this seminar series is geared towards MCS2111 students, I will also incorporate a teaching part at the end of my talk to discuss my text mining and analytics course along with methodology towards senior projects and directed study.
A Mathematical Journey of Disease Spread Models
Speaker: Bruce Pell
Abstract: In this talk, I’ll present an overview of my past, present and future research projects that relate to modeling the spread of infectious diseases. Along the way we’ll discuss reasons for why such a task is important and what types of mathematical tools can be used to understand the dynamic spread of diseases. Specific case studies will be presented from previous research projects (Ebola, Zika and Plague) along with current and future projects (COVID-19, pathogen fitness and thermal mismatch curves).
A Mathematical Model of COVID-19 Spread by Vaccination Status
Speaker: Matthew D. Johnston
Abstract: In this talk, I will present some recent joint work with Drs. Pell and Nelson on the mathematics of COVID-19 spread. We introduce an n-stage vaccination model and corresponding system of differential equations which can simulate a disease outbreak by breaking the population down according to their vaccination status. This allows the mitigation effects of vaccination and accelerating effects of variants such as delta to be uncoupled from one another, and offers valuable insight for the future course of the COVID-19 pandemic. We fit the model to 2021 data from the Virginia Department of Health.