The Department of Computer Science at the University of Iowa would like to share our research and our passion for this work with you and your students. To this end, we would like to introduce our speakers bureau, a list of faculty in our department who would love to present their work to your students! Our goal is to provide a single point of contact to set up faculty talks from our department. We also provide a list of possible talk topics, so you have an idea what we can offer. Ideally, by making it easier to organize colloquia and other presentations at your school, we will see you more often!
Below is a list of our faculty who have volunteered, as well as sample talks they already have prepared. If you would like to set up a talk, please send an e-mail to Sriram Pemmaraju with ideal dates and times and any preferred speakers or talks, and he will work to find a speaker available to fit your schedule. If you aim for a particular speaker, feel free to coordinate directly with them (though please copy email@example.com, too).
Speakers and Example Talk Topics
Bijaya Adhikari, Ph.D.
Data Driven Epidemic Forecasting
The ongoing COVID-19 pandemic has highlighted the necessity of epidemic forecasting. An accurate forecasting framework acts as a powerful tool to combat infectious outbreaks by giving valuable lead-time for preparation. In this talk, we present our data driven frameworks for epidemic forecasting for various targets associated with influenza and COVID outbreaks. Our data driven approaches are carefully designed with the true nature of the disease in mind. Hence, they help in addressing several challenges of real time forecasting such as interpretability, handling noisy signals, and principled propagation of uncertainty. Results from real time forecasting challenges show that our approaches are among the state-of-the-art.
Octav Chipara, Ph.D.
Developing and Deploying Mobile Sensing Applications
Mobile sensing applications are an emerging class of mobile applications that take advantage of the increasing sensing, computational, storage, and networking capabilities of mobile devices. Chipara’s research focuses on the systems, networking, and software engineering aspects of developing mobile health (mHealth) systems that continuously monitor and infer the health status of patients. His work combines the design of communication protocols, middleware, and programming tools with large-scale real-world deployments of working systems.
Recent visit: Grinnell College (Fall 2015)
Omar Chowdhury, Ph.D.
Leveraging Formal Techniques For Ensuring Security, Privacy, and Safety
Automated formal verification techniques have the potential to provide rigorous assurances about the satisfaction of desired properties of a system. The properties in question here often capture security, privacy, safety, or even functional requirements of a system. Automated formal verification techniques, however, are often presumed not to scale when applied to complex, real systems. In this talk, I will offer three examples as evidence to demonstrate that the above conventional wisdom does not hold invariably. In these examples, we leverage formal verification techniques to achieve a higher level of privacy, security, and safety in complex systems.
First, I will show how we used techniques from logic programming and runtime monitoring to efficiently detect whether an organization's business practice is compliant with a real privacy regulation (i.e., the US Health Insurance Portability and Accountability Act). Second, I will demonstrate how we took advantage of techniques from program analysis and model checking to check whether a given protocol implementation satisfies some expected properties. I will conclude my talk by demonstrating how we benefited from efficient runtime monitoring techniques to ensure that an autonomous research vehicle from a reputed car company does not violate safety properties.
Recent visits: Cornell College (Fall 2016), Central College (Fall 2016)
Juan Pablo Hourcade, Ph.D.
Increasing use of computers to satisfy needs and rights (e.g., voting, purchases, payments) means designers must ensure accessibility for increasingly diverse populations and computing devices. This talk outlines challenges and opportunities in design to achieve that goal for children, older adults, and people with lower socio-economic status.
Recent visits: Knox College (Fall 2012), Cornell College (Fall 2013)
Doug Jones, Ph.D.
Election Forensics in the Digital Era
An investigation of problems in a 2006 election in Sarasota County, FL. Finding out went wrong at the polls took 4 years, with investigations into classical forensics, hacking, and human-factors research. The results indicate some of the difficulties in designing computer systems that maintain forensic evidence while preserving security and privacy.
Recent visit: Wartburg College (Fall 2012)
J. Garrett Morris, Ph.D.
Extensibility in programming language design
Extensibility is an evergreen problem in programming and programming language design. The goal is simple: specifications of data should support the addition of both new kinds of data and new operations on data. Despite this problem having been identified as early as 1975, modern languages lack effective solutions. Object-oriented languages require programmers to adopt unintuitive patterns like visitors, while functional languages rely on encodings of data types. Lower-level languages, where similar problems arise, rely on textual substitution. I will present recent work which proposes a unified approach to extensible data specifications. I will show how this work both encompasses existing approaches to extensible data specifications, and captures examples inexpressible in all existing systems. Our approach naturally generalizes, providing a single account of extensible objects, effects, and bit-level specifications.
Brandon Myers, Ph.D.
High-performance Parallel Systems for Data-intensive Computing
Applications in data science rely on two computing paradigms: tuned high performance parallel programs and data analytics. While historically the differences between these paradigms were good reason to separate them into different systems, recent changes in hardware and, as a result, fast data processing techniques, call this separation into question. First I’ll discuss hardware trends and the requirements of data-intensive scientific applications. Then, I’ll talk about two systems that bring high performance parallel computing and data analytics closer together: 1) Grappa, an extension of C++ that allows the user to write data-intensive parallel code without worrying about all the complexities of programming a cluster of computers and 2) Radish, a system that compiles database-style queries (e.g., SQL) into parallel code.
Rishab Nithyanand, Ph.D.
Tussling with Anonymity and Privacy on the Internet
In recent years the Internet has integrated itself into the critical infrastructure and its users have become increasingly dependent on it for commerce, communication, and social and political organization. This has resulted in the emergence of Internet stakeholders that have competing and contradictory interests. For example, given that the Internet economy is fueled by user data and targeted advertising, content providers aim to maximize their ability to gather user data and personally identifiable information (PII). This goal contradicts the interests of parties lobbying for consumer and privacy protection on the Internet. Effective regulation and resolution of such tussles by Internet governing authorities are hampered by the opacity of the Internet and the inability to uncover the behaviors of competing parties. In this talk I will focus on my most recent work that uncovers the state of two such tussles: (1) anonymity vs. accountability and (2) privacy vs. profitability.
Suely Oliveira, Ph.D.
Fast Computing for Data Sciences
In this talk I will present algorithms from continuous optimization used for Machine Learning and Data Analysis. Particularly, I will concentrate on models for clustering and classification of large data that give accurate algorithms for various applications. Another important aspect for Data Sciences is speed. The fastest computers consist of thousands of nodes and thousands of GPUs making hybrid computing a must if you want to achieve high performance for scientific computing and data science algorithms. In this talk I will also address these computational issues.
In Computer Science at University of Iowa we teach GPU as well as Message Passing programming classes, we also offer a certificate in Large Data Analysis to prepare Computer Students for future challenges in Data Sciences. Jointly with statistics we are also offering a new major in Data Sciences.
Sriram Pemmaraju, Ph.D.
The Power of Randomization in Algorithms
Over the last two decades, randomization has been recognized as a powerful tool in the design of algorithms. There are now many instances where randomization improves either the simplicity or the speed (or both) of algorithms. Also, randomization has become indispensable in new computational settings, for example in the context of online or streaming algorithms or in the context of wireless networks. This talk will provide accessible examples of the power of randomization in the design of algorithms starting with classical examples such as primality testing algorithms to recent examples of data streaming algorithms.
Recent visits: Cornell College (Fall 2012), Knox College (Spring 2014), Grinnell College (Fall 2014), University of Wisconsin La Crosse (Fall 2015), Luther College (Fall 2016), Drake University (2017), Cornell College (2018), Grinnell College (2019), Carleton College (2019)
Kyle Rector, Ph.D.
Accessible Computing for All
One in six people have a disability, whether hidden or apparent. It is important for designers to create technologies that are accessible to people of different backgrounds. First, this talk will outline the research that I and others have conducted in computer science to improve access and wellness for people with disabilities. Then, I will focus on two of my research projects: 1) Eyes-Free Yoga, an accessible yoga exercise game that provides auditory instructions and feedback for people who are blind or low vision, and 2) Eyes-Free Art, a system that allows people who are blind or low vision to explore 2D paintings using audio techniques. Finally, I will discuss future research opportunities in accessibility and computer science.
Recent visits: Knox College (Fall 2016), Grinnell College (Fall 2016)
Alberto Maria Segre, Ph.D.
Computational epidemiology lies at the intersection of computer science, engineering, statistics, and health care. Our goal is to inform public and hospital policy decisions on topics such as: disease surveillance, disease prevention measures, and outbreak containment. Covers our work, including computational models, simulations, and visualization for the spread of disease.
Recent visits: Grinnell College (Fall 2012), St. Ambrose University (Fall 2013), University of Illinois Chicago (Spring 2014), Cornell College (Fall 2015), Central College (Fall 2015), Iowa State University (Spring 2016)
Supreeth Shastri, Ph.D.
Legalizing Personal-data Systems
In recent years, many societies have recognized the privacy and protection of personal data as a fundamental right of the people. While regulations such as GDPR (in Europe) and CCPA (in California) are already in effect, modern computing systems are struggling to comply with them. In this talk, I will show how these laws invalidate computing principles and practices that have years of precedence, and why it is challenging to legalize personal-data systems. The overarching goal of my research has been to bridge this gap between (legal) intention and (computing) implementation. I will share the work that my collaborators and I have been doing in this space, and identify some of the interesting open problems.
Padmini Srinivasan, Ph.D.
What is Text Mining?
Text mining is an exciting area of study that underlies a wide variety of entrepreneurial initiatives especially with Web data. For example, when applied to social media such as Twitter and YouTube we can find out interesting details such as the hottest topics, the most influential posters, which subjects attract the most attention from the public, how long does it take for an idea to spread etc. This talk highlights the many opportunities that arise with text mining.
Recent visit: Coe College (Fall 2013), Drake University (Fall 2015)
Aaron Stump, Ph.D.
A Type-Based Approach to Verified Software
Discusses recent work to provide lighter-weight verification using strongly typed languages. Instead of relying on proving correctness, this approach expresses properties in the code using a rich type system. One goal is to support a continuum, where developers can select how much of their code to verify. Recent research examples are discussed.
Recent visits: Truman State University (Fall 2012), St. Ambrose College (Fall 2012), St. Ambrose-Knox College IEEE meeting (Fall 2013), Grinnell College (Fall 2013)
Denise Szecsei, Ph.D.
Programming Humanoid Robots
Learn about the capabilities of Nao humanoid robots and see them in action. Get a brief introduction to what is involved in programming them, and watch the robots dance, act, and perform magic tricks. For more information, visit the CS Performing Robots page.
Recent visits: K-12 and university outreach
Cesare Tinelli, Ph.D.
Verifying the Correctness of Programs
An introductory talk on formal verification of software, including: motivation for program verification; comparison of formal verification versus testing; and an overview of modern techniques for automating verification. Focuses on Iowa's research in the area.
Tianbao Yang, Ph.D.
Machine Learning and Big Data
Machine learning has become one of the core data-driven technologies. It has created tremendous value in various domains. In this talk, I will introduce machine learning and its relationship with big data. In particular, I will talk about what machine learning is, how to conduct machine learning, what the applications of machine learning are, etc. I will also give some suggestions on how to learn machine learning for students.
Recent visits: Drake University (Fall 2016)