2019 Prospective Student Visit Day and Graduate Research Symposium

Picture from Daniel Yahyazadeh's presentation at 2019 Grad Research Symposium

The Computer Science (CS) department welcomed individuals from around the country interested in graduate programs during our annual Prospective Student Visit Day. We are looking for strong students with diverse backgrounds to join our MCS and PhD programs. A wide variety of research areas are represented by our world-class faculty including algorithms; computer security and privacy, cybersecurity; computational epidemiology; computational logic; distributed computing; human-computer interaction; mobile systems; numeric, parallel, and optimization algorithms; retro-computing and historic computer reconstruction; text/web mining; machine learning; informatics; and virtual environments.

Coinciding with the Prospective Student Visit Day, we also hosted the 5th Iowa Computer Science Graduate Research Symposium (2019). Senior CS PhD students presented talks on their latest research, showcasing a variety of CS research areas including algorithms, big data, machine learning, human computer interaction, and data mining. A keynote by a CS faculty member followed. Talks are intended for a wide audience with interest in CS, including CS juniors and seniors. The talks presented by current CS graduate students at the Symposium are excellent examples of the exciting research taking place here in Iowa City!


Friday, Nov 8, 2019

Morning Sessions (in MacLean Hall) for Visiting/Prospective Students


Overview of Graduate Programs, Sriram Pemmaraju, Director of Graduate Studies


CS Faculty Meetings and Research Demonstrations


Visiting students will meet and have lunch with Computer Science Graduate Students


Graduate Student Research Symposium (W401 Pappajohn Business Building (PBB))


Session One


Umar Iqbal

Machine Learning for Ad & Tracker BlockingMachine Learning for Ad & Tracker Blocking - Umar Iqbal


Jeff Hajewski

Designing Neural NetworksDesigning Neural Networks_Jeff Hajewski




Session Two


Daniel Yahyazadeh

The status quo of IoT [in]security


Adnan Ahmed

Optimizing Web Performance with HTTP/2


Poster Session and Reception

Poster Presentation Title

Kyle Diederich

Title: Play-Based Design:​ Face-to-Face Interaction for Young Children Voices in the Design ProcessPlay-based design

Authors: Kyle Diederich and Juan Pablo Hourcade

Hasib Hasan [Best Poster Award]

Title: Mining Kinect traces to estimate interaction times between healthcare workers and patientsMining Kinect Traces to Estimate Interactions between Healthcare Workers and Patients

Authors: Hasibul Hasan, Philip M. Polgreen, Alberto M. Segre, Jacob Simmering, and Sriram V. Pemmaraju

Andrew Marmaduke

Title: Quotient Types by Idempotent Functions in CedilleQuotient Types by Idempotent Functions in Cedille

Authors: Andrew Marmaduke, Christopher Jenkins, and Aaron Stump

Mudathir Mohamed

Title: A new relational solver for the Alloy Analyzer

Authors:  Mudathir Mohamed, Baoluo Meng, Andrew Reynolds, and Cesare Tinelli

Qi Qi

Title: A Simple and Effective Framework for Pairwise Deep Metric Learning

Authors: Qi Qi, Yan Yan, Zixuan Wu, Xiaoyu Wang, and Tianbao Yang

Lakshmi Subramanian

Title: Impact of Adaptive Headlamp Systems on Nightime Bicyclist Safety

Authors: Lakshmi D. Subramanian, Elizabeth E. O’Neal, Rini Sherony, Jodie M. Plumert, and Joseph K. Kearney

Arjun Viswanathan

Title: Verifying Bit-vector Invertibility Conditions in CoqVerifying Bit-vector Invertibility Conditions in Coq

Authors: Burak Ekici, Arjun Viswanathan, Yoni Zohar, Clark Barrett, and Cesare Tinelli


Keynote Speaker: Kasturi Varadarajan

The K-Center Problem: Some Algorithmic Aspects


Umar Iqbal

Title: Machine Learning for Ad & Tracker Blocking

Umar Iqbal - UI CS PhD candidate


User demand for blocking online advertisements and trackers is large and growing. Existing methods, both deployed and described in research, have proven useful, but they lack either the completeness or robustness needed for a general solution. Existing detection approaches generally focus on only one aspect of advertising or tracking (e.g. URL patterns, code structure), making them susceptible to evasion.

In this talk, we first give a brief overview of ads and trackers and then discuss existing approaches that propose machine learning to identify ads and trackers.Then we propose our approach (AdGraph),  which builds a novel graph-based representation of the HTML structure, network requests, and JavaScript behavior of a webpage, and uses this unique representation to identify advertising and tracking resources. Overall, we conclude that fine-grained interaction details of HTML, network, and JavaScript are essential for an effective ad and trackerblocking solution.

4th year PhD student | Advisor: Zubair Shafiq | Area of research: privacy and security

Jeff Hajewski

Title: Designing Neural Networks

Jeff Hajewski - UI CS PhD candidateAbstract:

Despite the recent success of deep learning, neural networks remain difficult to design. The challenge in designing a neural network is two-fold: the interactions between network hyper-parameters is unclear and evaluating a given network architecture is computationally intensive because it requires training the network. This talk will discuss our current work in using evolutionary algorithms to design neural networks and building distributed systems to efficiently evaluate the networks. The goal is to balance the effectiveness of the search process with the cost of running the distributed system, which is run on AWS.

3rd Year PhD student | Advisor: Suely Oliveira | Area of research: distributed systems and machine learning

Daniel Yahyazadeh

Title: The status quo of IoT [in]security

Daniel Yahyazadeh - UI CS PhD candidateAbstract:

IoT, as a new emerging technology, is expanding quickly. It has gained a foothold in many different domains such as smart home, health care, and industrial manufacturing, while there is a huge gap in its security. This lack of security has made them vulnerable to a rapidly increasing attack surface and being proxy to potentially threaten the other Internet infrastructures. In this talk, we will focus on a variety of threats targeting different components in an IoT system and present a survey of the literature on the potential countermeasures. This presentation concludes by raising awareness of security in the IoT systems and the need for conducting research to bridge their security gap.

4th year PhD student | Advisor: Omar Chowdhury | Area of research: computer security, privacy, and formal verification

Adnan Ahmed

Title: Optimizing Web Performance with HTTP/2

Adnan AhmedAbstract: 

Over the past decades, the web has evolved from simple single-page text oriented websites to a complex ecosystem with rich-content being fetched from multiple web servers that fall in different administrative domains. Prior studies have highlighted how degradation in web performance can cause user frustration and potentially cause webpage owners millions and billions of dollars of loss in revenue. Therefore, there has been a never-ending effort in both academia and industry to propose new ways to optimize web browsing and improve user experience in the face of ever-increasing user expectations.

In this talk, I will highlight some of the existing state-of-the-art research on web optimizations. These techniques typically rely on identifying dependencies among resources present on a webpage, and analyzing critical rendering paths to prioritize resource fetches. Furthermore, I will discuss HTTP/2 which has changed the way webpages and content is delivered over the Internet. For instance, one of the new features in HTTP/2 is server push, which enables servers to preemptively send resources to clients. While a lot of prior work focuses on proposing techniques to deploy server push and improve webpage performance, we discuss how the benefits of such solutions are undermined by the fragmented nature of modern web, requiring first-party content publishers to consistently coordinate with third-parties to configure server push. To solve this, I will talk about ATOMIX---a data-driven approach that allows third-parties to discover pushable resources without requiring any coordination with the first-party content publisher. At a high level, ATOMIX discovers pushable resources by analyzing patterns in HTTP request logs at the server-side using a Markovian transition matrix. Furthermore, ATOMIX is able to evaluate server push effectiveness in an online fashion and adjust the transition matrix accordingly to achieve high precision.

5th year PhD student | Advisor: Zubair Shafiq | Area of research:  video delivery, video/web QoE, and interconnection strategies

Keynote Speaker Kasturi Varadarajan

Title: The K-Center Problem: Some Algorithmic Aspects 

Kasturi Varadarajan - UIowaCS Professor


K-Center is a well known optimization problem that is inspired by facility location and clustering. For more than three decades, researchers have studied algorithms for computing approximately optimal solutions for variations of this problem. We will discuss some of these variants, focusing on the algorithmic approaches that have been employed.

Research Interests: In principle, all of theoretical computer science. In practice, a subset that includes primarily parts of computational geometry, but also optimization problems on graphs and the like and polynomial time computability of equilibria in games and some economic models.


Getting to the ConferenceMap of area and symposium location

Iowa City lies just off of Interstate 80 in Eastern Iowa. Regardless of whether you are coming from the West or the East, you will want to take exit 244 off of I-80 following Dubuque Street until you intersect with Church Street. Follow Church Street as it turns into Clinton Street and continue straight until you reach the downtown area and the Pentacrest (you will see the Old Capitol to the right/West), which is the heart of the University of Iowa's campus. All of the symposium will take place in that general vicinity in MacLean Hall and W401 Pappajohn Business Building (PBB) Check out the adjacent map!