Below you will find a list of faculty that will be conducting research during the Summer of 2022 and are looking for research students.

  • Algorithmic Methods for Analyzing Tumor Evolutionary Trees (Layla Oesper)
  • Symbiosis in Digital Evolution (Anya Vostinar)
  • Evaluating the Perceptual Limitations of Text Visualizations (Eric Alexander)

Descriptions of the projects are below:


Algorithmic Methods for Analyzing Tumor Evolutionary Trees (Layla Oesper)

2-3 students, June 13–August 12 (9 weeks)

Cancer is a disease resulting from the accumulation of genomic alterations that occur during an individual’s lifetime and cause the uncontrolled growth of a collection of cells into a tumor. These mutations occur as part of an evolutionary process that may have begun decades before a patient’s diagnosis. Better understanding about the history of a tumor’s evolution over time may yield important insight into how and why tumors develop as well as which mutations drive their growth.  While recent algorithmic progress has led to improved inference of tumor evolutionary histories, there is still a very challenging task.

This summer students in my group will be part of an ongoing initiative to develop algorithmic methods for analyzing these tumor evolutionary histories (represented as trees) and better understanding what the space of these histories looks like.  The exact details of what students will be working on will depend on their interests, background and how the project progresses prior to the start of summer.  Aspects of the project that students may likely work on include:

  1. Extend and modify existing distance measures designed for tumor evolutionary trees.
  2. Develop new distance measures for tumor evolutionary trees that relax certain mathematical assumptions about the trees.
  3. Perform mathematical and computational analysis of the space of tumor evolutionary trees.

Students working on these tasks may gain experience working with large datasets, using large multi-core machines, designing computational experiments and will become familiar with some aspects of DNA sequencing data and analysis.  COVID permitting, one week of the summer will be spent at University of Illinois at Urbana-Champaign working with collaborators (student expenses for this trip will be covered).

Ideally, students should be available to participate in an independent study during the spring of 2022 to read papers, familiarize themselves with related tools/concepts, and have discussions to begin planning the project.  Applicants should have completed at a minimum CS 201 by the end of Spring term 2022.  Students who have taken Computational Biology, Bioinformatics or Algorithms are also strongly encouraged to apply.  No specific biology background is required, just an interest in applying computational techniques to important biological problems.

*Graduating seniors who are interested in working for longer periods of time (3-12 months ideally) should contact Layla directly as she has funds to support such a position as well. 


Symbiosis in Digital Evolution (Anya Vostinar)

1-2 students, June 27–September 2 (10 weeks)

Symbiosis in biology is a close and long-term relationship between at least two organisms of different species. It can be a relationship that benefits both organisms, termed a mutualistic symbiosis, or it can be harmful for one of the organisms, termed a parasitic symbiosis. Symbiotic relationships are a fundamental dynamic in all of life on Earth, impacting everything
from human health to agriculture to how organisms will deal with climate change. Understanding how these symbiotic relationships did and continue to evolve is a challenging problem, but aided by computational modeling using techniques called agent-based modeling and digital evolution.

This summer, students in my group will be part of an ongoing initiative to develop open-source agent-based modeling software that is validated by real-world and/or mathematical modeling data. Students will then use that software to investigate specific microbial symbiotic systems and general trends in eco-evolutionary dynamics. The exact details of what students will be working on will depend on their interests, background, and how the project progresses prior to the start of summer. Aspects on the project that students may likely work on include:

  1. Implement and analyze the effect of symbionts and hosts capable of more complex (Turing complete) behavior
  2. Implement and analyze the effect of multi-infection where multiple symbionts interact within a host while co-evolving with the host species
  3. Expand the GUI that accompanies Symbulation (the software project) to show these or other behaviors

Students working on these tasks may gain experience working with large open-source software, computer clusters, designing computational experiments, and understanding biological data.

I expect to hire 1-2 students for this project. Students who are accepted will work from June 27-Sept 2 during the summer of 2022. Ideally, students should be available to participate in an independent study during the spring of 2022 to read papers, familiarize themselves with related tools/concepts, and have discussions to begin planning the project.

Applicants should have completed, at a minimum, CS 201 by the end of Spring term 2022. Students who have taken Evolutionary Computing and Artificial Life are strongly encouraged to apply. No specific biology background is required, just an interest in applying computational techniques to important biological problems.


Evaluating the Perceptual Limitations of Text Visualizations (Eric Alexander)

1-2 students, June 13 – August 19 (flexible) (10 weeks)

It may seem silly to say “A picture is worth a thousand words” at the beginning of a research description containing exclusively text, but in many ways, it’s true. The human perceptual system allows us to make complex judgments about enormous amounts of data in mere fractions of a second, which is why so many in-depth prose arguments and sophisticated statistical analyses are skimmed over in favor of looking at the accompanying figure. As tools for communicating information to a wide audience, data visualizations are exceptionally efficient. 

However, powerful though it may be, our perceptual system is also fraught with bias and inaccuracy. We evolved to be able to spot berries amongst dense leaves, not to precisely compare the positions and sizes of red and green glyphs in a scatter plot. Aspects of our vision that help us find the berries might distort our impressions of data in a visualization, making it important to understand and quantify these sorts of perceptual quirks if we want to convey accurate information to our readers.

This summer, students in my group will be working to evaluate our ability to accurately perceive data encoded in visualizations containing text (e.g., word clouds). Text visualizations share some of the same perceptual oddities as other visualizations, with additional cognitive challenges associated with how a word’s meaning might skew the way we see or remember it. The precise trajectory of this summer’s work is open-ended, and will depend on the skills and interests of those involved. Some of the things that students may work on include:

  1. Designing experimental conditions that allow us to isolate and measure specific aspects of text visualization perception of online participants.
  2. Developing tools to dynamically generate visualizations that meet these constraints.
  3. Performing the statistical analysis of participant performance.

Students working on this project are likely to gain experience in web development, designing and analyzing perceptual experiments, and visualizing complex data.

I will be looking for 1-2 students to join me in this project. Accepted students will work for 10 weeks during the summer of 2022, though the precise dates may be flexible. Ideally, students should be available to participate in an independent study during the spring of 2022 to read papers, familiarize themselves with related tools/concepts, and have discussions to begin planning the project.  Applicants should have completed at a minimum CS 201 by the end of Spring term 2022.  Students who have taken Data Visualization, Software Design, or classes in perceptual psychology are strongly encouraged to apply. No specific background in visualization or text analysis is required, just an interest in how the choices we make as designers can affect the information our readers take away.