May 16, 2021

Awards Honor May 2021 Graduates

The School of Information’s May 2021 Virtual Commencement presented an opportunity to honor both faculty and student achievements.

The faculty Head Graduate Advisors presented awards for outstanding capstone projects from the Master of Information Management and Systems program, the Master of Information and Data Science program, and the Master of Information and Cybersecurity program.

Students in both the MIMS, MIDS, and MICS programs voted for their most outstanding instructors and gave awards to their classmates.

Also see the Summer 2020 MIDS and MICS capstone winners, and the Winter 2020 MIDS and MICS award winners.

James R. Chen Award for Outstanding MIMS Final Project, 2021

Track 1

Ontology Mapping for Cardiovascular Ailments
Brinda Gurusamy, Ramya R, Vibhor Sehgal
Advisor: Hany Farid

Next to chest x-ray, ultrasound is the single highest-volume cardiac imaging test practiced in millions of hospitals worldwide. And yet, reporting is highly variable despite the clinical guidelines on what to report. Variability in reporting hurts doctors’ and patients’ ability to communicate the test results and hampers the ability to harmonize data and data labels in pursuit of effective and robust machine learning models for cardiac ultrasound imaging. This project aims at building robust methods for clinical report harmonization.

Track 2

PrivacyBot
James Carney, Joanne Jia, Archana Kulkarni, Cameron Lopez
Advisor: Chris Jay Hoofnagle

Have you ever wished you could do something about the creepy ads you see or the eerily accurate people search results about you? PrivacyBot is a free and open-source way to delete your data from an exhaustive list of data brokers and people search sites.

MIMS Video Award

Loop is the winner of the MIMS Video Award. Check out the video here.

Hal R. Varian MIDS Capstone Award, Spring 2021

TowerScout
Jia Lu, Gunnar Mein, Thaddeus Segura, Karen Wong

Legionnaires’ disease is a severe pneumonia with a 1 in 10 fatality rate, and cooling towers containing Legionella bacteria are a common source of community outbreaks. TowerScout is a tool that uses machine learning to automatically detects cooling towers visible from aerial imagery across the United States.

Lily L. Chang MICS Capstone Award, Spring 2021

hunnypOT
Bryan Everly, Greg Herweg, Jennifer Mvongo, Chukwunenye Nnebe, Sam Sabetan

hunnypOT is a network appliance that simulates an Industrial Control System network. It provides an early warning system so that attacks on critical infrastructure (such as power plants, water treatment facilities and telecommunications networks) can be detected before the attacker can cause damage.