Past Projects

Projects and Outcomes for Info Challenge 2023


Photo of Grand Prize winners Dharini Chandrashekar, UMD and Amanpreet Kaur, UMD with members of the event team

Congratulations to our 2023 Grand Prize winners! Dharini Chandrashekar, UMD and Amanpreet Kaur, UMD. Challenge: CoPAR Website Concept Design – UMD iSchool (Design). See below for more challenge winners.

UMD Global Classroom Analysis (category: data analytics, level 1)

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The University of Maryland Global Classrooms program allows UMD students to gain international experience in a virtual learning environment. After the COVID-19 pandemic, Global Classrooms courses and participants have increased significantly, and the Office of International Affairs seeks to understand student diversity trends for past semesters. Students will use their creative insights on how variables such as gender, race, ethnicity, age, and residency from past student data can be used to compare diversity trends by semester, academic year, and student status.

Project Participants:

Alanna Hart, Anita Conteh
Mentor: Margaret Kahl
Link to project

Brita Laveck, Ellen Kim, Tartela Tabassum
Mentor: Adam Lee
Link to project

Jaehyun Lee, Daniel Yu, Eojin Kim
Link to project

Majdoleen Mohammedaman, Reem Saleh
Mentor: Prasad Senesi
Link to project

Grant Glasgow, Ben Keenan
Mentor: Mark Magsino
Link to project

Harshitha Ramachandra, Shashank Ramprasad
Mentor: Tatyana Yevgrafova
Link to project

Osinakachi Amaefule, Cecilia Chavez, Jaclyn Tran
Mentor: Jeffrey Zuback
Link to project

Christine Wang, Anthony Avelar
Mentor: Jeffrey Zuback
Link to project

Ramith Wijesinghe, Matthew Chin, Kidus Solomon, Courtney Brandon
Mentor: Maria Bardossy
Link to project

Sehba Wani, Josue Tlapechco, Vienna Nguyen
Link to project

CrisisFACTS Summarization (category: data analytics, level 2)

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When crisis responders react to ongoing emergencies, they need to know what new critical developments have occurred in the past several hours. Oftentimes, responders are able to find this information through social media, however, finding the most important information first is crucial. By analyzing different social media platforms and news sources, construct daily summaries of Hurricane Florence and Hurricane Dorian using a digital version of FEMA’s Incident Status Summary form and utilize this data to assess which platforms provide the most useful information for emergency response personnel.

Project Participants:

Ivan Thomas
Mentor: Dan Roche
Link to project

Bennett Huffman, Maurice Salayon
Mentor: Dan Roche
Link to project

Hanna Zakharenko, G Goodwin
Link to project

Sadaf Davre, Tiara Eltrevoog, Sarah Zachariah
Link to project

Washington Fatal Crash Survey (category: data analytics, level 3)

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In 2018, Washington State enacted stronger distracted driving laws, and in response, a survey was developed to evaluate residents’ understanding of the new Driving Under the Influence of Electronics Act, which was conducted in one-month time periods over the past four years. We are curious to know how public perceptions of this new act have changed over time, particularly among demographic subgroups. This analysis will be used by the Public Health Seattle-King County (PHSKC) to target specific subgroups for media outreach, materials, and infographics, which students can also contribute to in addition to their analysis.

Project Participants:

Aditya Kiran Aswin Kumar, Rajeevan Madabushi, Sravya Lenka, Srikanth Parvathala
Mentor: Brian Wilkinson
Link to project

Manas M Bhat, Shantanu Parab, Vineet Singh
Mentor: Jeffrey Zuback
Link to project

Gunakshi Sharma, Dhiraj Lahoti, Shweta Salelkar, Sakshi BR Patil
Link to project

Thomas Cho, Jenna Han, Joshua Kang, Daniel Shin
Mentor: Duy Duong-Tran
Link to project

Malcolm Rivers, Ryan Grafman, Christopher Hom
Mentor: Nate Chambers
Link to project

Angelina Cheng, Caroline Irwin, Harrison Morrow
Mentor: Duy Duong-Tran
Link to project

Aedan Ounsamone, Lindsey Beiche
Mentor: Nate Chambers
Link to project

Justin Werner, Alexander Grande
Mentor: Duy Duong-Tran
Link to project

Aiden Patel, Chris Kim, Myles Evans, Ola Kwasniewski
Mentor: Justin Blanco
Link to project

Ashley Yi, Nicholas Munoz
Mentor: Nate Chambers
Link to project

Washington Fatal Crash Files (category: data analytics, level 4) 🏆

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Since the beginning of the COVID-19 pandemic, Washington State has experienced an unprecedented year-over-year increase in traffic fatalities. The Washington Traffic Safety Commission (WTSC) manages traffic safety behavior programs and media outreach for various communities. However, we are curious to know if the people living in these communities are the same people involved in the crashes where occur there. By analyzing datasets of crash data, students can answer questions such as: what proportion of drivers are involved in crashes in communities where they live? Are there specific zip codes where higher-risk drivers tend to be more common than others?

Best Team Presentation
Micah Tracy, US Naval Academy
Rhys Winter, US Naval Academy
Kaosi Unini, US Naval Academy
Ryan Zhang, US Naval Academy
Team IC23044
Challenge: Washington Fatal Crash Files – WTSC (Data Analysis, Level 4)
Mentor: Fiona Knoll
Micah Tracy, US Naval Academy; Rhys Winter, US Naval Academy; Kaosi Unini, US Naval Academy; Ryan Zhang, US Naval Academy

Outstanding Data Analytics Project (Tie)
Gabriel Duran, UMD
Keshav Gupta, UMD
Soham Pawaskar, UMD
Team: IC23048
Challenge: Washington Fatal Crash Files – WTSC (Data Analysis, Level 4)
Mentor: Vikrant Aute
Gabriel Duran, UMD; Keshav Gupta, UMD; Soham Pawaskar, UMD

Outstanding Data Analytics Project (Tie)
Anna Lavrentieva, UMD
Iris Yu, UMD
Ethan Taggart, Montgomery College
Christopher Way, UMBC
Team: IC23058
Challenge: Washington Fatal Crash Files – WTSC (Data Analysis, Level 4)
Mentor: Chauncey Robbs
Anna Lavrentieva, UMD; Iris Yu, UMD; Ethan Taggart, Montgomery College; Christopher Way, UMBC

Project Participants:

Jarrar Haider, Akhil Reddy, Eshan Agarwal, Chaitanya Pohnerkar
Mentor: James Li
Link to project

Xirui Han, Johannah Ryan, Tam Thu Doan, Kevin Weiner
Mentor: Kunpeng Zhang
Link to project

Jimmy Nguyen, Anthony Capasso, John Dutan
Mentor: James Li
Link to project

Zizheng Zhang, Xiaoze Liu, Wangxi Pan
Mentor: Vikrant Aute
Link to project

Matthew Purvis, Aidan Aguilar, Olivia Love, Danny Taylor
Mentor: Justin Blanco
Link to project

Caden Chau, Christopher Jones
Mentor: Dan Roche
Link to project

Rhys Winter, Micah Tracy, Ryan Zhang, Kaosi Unini
Mentor: Fiona Knoll
Link to project

Keshav Gupta, Soham Pawaskar, Gabriel Duran
Mentor: Vikrant Aute
Link to project

Kent O’Sullivan, Nicole Schneider
Link to project

Iris Yu, Anna Lavrentieva, Ethan Taggart, Christopher Way
Mentor: Chauncey Robbs
Link to project

Minnesota’s Fast Healthcare Interoperability Resources (category: design)

Under HIPAA (the Healthcare Insurance Portability and Accountability Act), every person has a right to access healthcare data about themselves. The State of Minnesota’s Department of Human Services (DHS), along with every other state, is developing tools to allow individuals’ to exercise their right to easily access their health data. MN DHS is seeking students’ help to create a simple, yet comprehensive series of screens for future healthcare uses. Students will use their creative abilities and UX/UI design skills to create user-friendly wireframes that make healthcare data accessible and provide easy to understand screens for current and future patients. 

Project Participants:

Makda Demleash, Fatma Fadlelmola
Mentor: Miles Calabresi
Link to project

CoPAR Website Concept Design (category: design) 🏆

The Council on the Preservation of Anthropological Records (CoPAR) was an organization founded in the 1990s to promote archiving and discovery of archival materials for cultural materials around the world. Since then, its website has remained the main resource for information about where to find anthropology archives, and how to encourage archiving practices among anthropologists. The current format of the CoPAR website is outdated, counterintuitive, and difficult to search and navigate, and resources are not presented in a visually compelling format. Students are tasked with brainstorming ideas and redesigning the website, improving user-friendliness, and developing visualizations that will facilitate greater access.

Grand Prize
Dharini Chandrashekar, UMD
Amanpreet Kaur, UMD
Team IC23063
Challenge: CoPAR Website Concept Design – UMD iSchool (Design)
Photo of Grand Prize winners Dharini Chandrashekar, UMD and Amanpreet Kaur, UMD

Project Participants:

Dharini Chandrashekar, Amanpreet Kaur Sareen
Link to project

Candace Sun
Mentor: Brittany Johnson
Link to project

Hannah Milillo
Mentor: Jacob Davidson
Link to project

Pygmalion Tool Maps Design (category: design) 🏆

The Pygmalion tool can be used to create interactive visualizations of the meanings associated with a word, or vice versa of different words associated with similar concepts, to provide researchers, teachers, and learners with an instrument to visually represent the heterogeneous and complex information presented by dictionaries in a more intuitive way. The tool offers both interactive linear visualizations and network visualizations of a word, however, the interactivity and readability of these maps could be improved. Students will brainstorm ideas and design concepts to increase the interactivity of these visualizations and make them more user-friendly, as well as brainstorm ideas for the use of this tool in educational environments.

Outstanding Design Project
Fatema Motiwala, UMD
Pooja Gajera, UMD
Pratya Nellore, UMD
Shaunak Bhanarkar, UMD
Team: IC23025
Challenge: Pygmalion Tool Maps Design – University of Neuchâtel (Design)
Mentor: Dan Forest
Fatema Motiwala, UMD; Pooja Gajera, UMD; Pratya Nellore, UMD; Shaunak Bhanarkar, UMD

Project Participants:

Fatema Motiwala, Pooja Gajera, Pratya Nellore, Shaunak Bhanarkar
Mentor: Dan Forest
Link to project

Vimbainashe Mabvaru, Runyararo Mucheche
Mentor: Dan Forest
Link to project

Cybersecurity Controls: Audit, Automate, and Advise (category: cybersecurity) 🏆

Controls to mitigate against cybersecurity attacks are an important component of an entity’s overall IT control environment. As such, it is increasingly important for external auditors to be aware of the risks that clients face because of poor or inadequate cybersecurity processes and controls. For this challenge, students will play the role of an external auditor for a public company, tasked with evaluating and testing internal controls. More specifically, students will evaluate and test passwords–a crucial component of access controls. Students will evaluate, perform, and document a series of steps as part of reviewing password management as a key Information Technology General Control (ITGC) and have the option to develop a system to automate the process.

Outstanding Cybersecurity Project
Ivan Bajceta, US Naval Academy
Michael Huizenga, US Naval Academy
Strahinja Janjusevic, US Naval Academy
Eric Liu, US Naval Academy
Team: IC23038
Challenge: Cybersecurity Controls: Audit, Automate, and Advise – EY (Cybersecurity)
Mentor: Fiona Knoll
Ivan Bajceta, US Naval Academy; Michael Huizenga, US Naval Academy; Strahinja Janjusevic, US Naval Academy; Eric Liu, US Naval Academy

Removing Personal Data (category: cybersecurity)

This dataset, compiled by Yael Grauer, is a list of data brokers with steps for people to get their data removed. Each data broker is labeled if it is high priority, requires a driver’s license for removal, if the user must make their request via snail mail, or if the site charges for removal. There is also a free-text description of the removal process, usually including links. We are looking for ways to allow users to make informed decisions about how to proceed with getting their personal data out of these systems. Prioritizing a list by ease of the process (something challenge participants will have to rank based on multiple factors), urgency, number of steps, etc. would be useful, along with clear steps explaining what to do.

Project Participants:

Sai Divvela, Pranav Bonagiri, Danish Nadar, Itunuoluwa Ayo-Durojaiye
Mentor: Jimmy Alexis
Link to project

Jimmy Garcia, Quinn Carmack
Mentor: Kevin Barbian
Link to project

Min Cheong Kim, Luis Mayorga, Seshasai L
Mentor: Maddie Metcalfe
Link to project

Projects and Outcomes for Info Challenge 2022

ERS USDA: FoodAPS (category: data analytics, level 1)

Organization: Economic Research Service (ERS), US Department of Agriculture (USDA)
Project Name: FoodAPS
Category: Data Analytics

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Description: The National Household Food Acquisition and Purchase Survey (FoodAPS) collects nationally-representative, comprehensive data on household food purchases and acquisitions, in what quantity, at what price, and from where, as well as nutrition, economics, environment, and health. USDA ERS has developed interactive charts related to food spending and food access using FoodAPS data. USDA ERS is interested in expanding these visual analyses to address issues related to equity. Specifically, USDA ERS is interested in carrying out an assessment on the extent to which programs and policies perpetuate systemic barriers for people of color and other underserved communities. To evaluate this, USDA ERS is looking for students to analyze the FoodAPS data and identify trends among vulnerable populations with regard to food access, food choice, and food prices.

Team IC22025 | Project Title: Food Access
Joshua Kaplowitz | US Naval Academy
Tongbun Pengkaew | US Naval Academy
Ryan Samotis | US Naval Academy

Team IC22028 | Project Title: Team22028-Food Accessibility
Aboli Dahiwadkar | University of Maryland
Anuja Bendre | University of Maryland
Tasnim Obaied | University of Maryland

Team IC22050 | Project Title: Top Deterrents to Food Access in Highly Underserved U.S. Populations from National Household Food Acquisition and Purchase Survey (FoodAPS) in 2012
Amani Mbonimpa | Montgomery College
Michelle Nguyen | Montgomery College
Mai Tran | Montgomery College
Matthew Chin | Montgomery College

Team IC22059 | Project Title: Food Spending and Food Access in different Target Groups
Tanna Nguyen | Montgomery College
Thanh Trinh | Montgomery College
Luis Valderrama | Montgomery College

Bea Hardy: Naval Officer Shipping Lists (category: data analytics, level 1)

Organization: Bea Hardy
Project Name: Naval Officer Shipping Lists (NOSLs)
Category: Data Analytics

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Description: The Chesapeake colonies were a vibrant part of the world economy during the 18th century, trading extensively with the British empire and other foreign ports. Tax officials documented these trades in Naval Officer Shipping Lists (NOSLs) which recorded all ships entering and clearing the Chesapeake ports, along with detailed lists of their cargoes. These records have been transcribed into a relational database, including summaries of imports and exports, types of goods, quantities, destinations, and prices. Students can use this data in a variety of ways and answer several questions regarding the logistics of the economy and trading hundreds of years ago.

Team IC22022 | Project Title: Exploring Shipping in the Eighteenth Century Chesapeake
Jenny Luo | US Naval Academy
Krystal Kim | US Naval Academy
Everett Stenberg | US Naval Academy
Young Kim | US Naval Academy

INFO College and the Library of Congress: Rosa Parks in Her Own Words (category data analytics, level 2)

Organization: INFO College and the Library of Congress
Project Name: Rosa Parks in Her Own Words
Category: Data Analytics

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Description: Rosa Parks and Dr. Martin Luther King are both known and praised for their roles in the Montgomery Bus Boycott in 1955, which campaigned for equal rights of use of public services and spaces. Over 40,000 African Americans participated in this movement, yet the majority of their contributions are not publicized. The Library of Congress currently houses over 7,000 documents from Parks’ legacy, 1,769 of which include the names and details of many carpool participants from the Montgomery Bus Boycott. The College of Information Studies is interested in using this collection to create a visualization of those involved in the Montgomery Bus Boycott, their contributions, and their experiences.

Team IC22045 | Project Title: Analyzation of Rosa Parks Data
Janushaa Bala Krishnan Muthiah | US Naval Academy
Mingyu Han | US Naval Academy
Courtney Weir | US Naval Academy

Joe Bonsignore: The Armed Conflict Location and Event (category: data analytics, level 2) 🏆

Organization: Joe Bonsignore
Project Name: The Armed Conflict Location and Event
Category: Data Analytics

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Description: The Armed Conflict Location and Event (ACLED) project collects real-time data on the locations, dates, actors, fatalities, and types of all reported political violence and protests across multiple countries. ACLED aims to capture how various attacks and demonstrations of violence occur in different states. Focusing on a subset of this data for the United States, use data analytics skills to understand how the number of events have changed over time, whether there are any significant locations of events, and how the types of events have changed over time.

Award Winner: Outstanding Data Analytics Project
Team IC22043 | Project Title: Trends with Conflicts in the U.S.
Liam Bailey | US Naval Academy
Isaac Cho | US Naval Academy
Paul Hendron | US Naval Academy
Antawn Weg | US Naval Academy

Team IC22011 | Project Title: Unrest in America
Matthew Lewis | US Naval Academy
Jeff Peters | US Naval Academy
Julian Muniz | US Naval Academy
James Fiscus | US Naval Academy

Team IC22035 | Project Title: Police incidents and protests
Prathamesh Malage | University of Maryland
Eduardo Gonzalez | Montgomery College
Tai Ngo | Montgomery College

Team IC22037 | Project Title: ACLED – BLM Focus
Elizabeth Farmer | US Naval Academy
Samuel Chanow | US Naval Academy
Ashley Chung | US Naval Academy

Team IC22058 | Project Title: Protests in the US
Mark Roh | US Naval Academy
Nathan Utesch | US Naval Academy
Brigitta Szepesi | US Naval Academy

Small Business Administration: Paycheck Protection Program (category: data analytics, level 3)

Organization: US Small Business Administration (SBA)
Project Name: Paycheck Protection Program
Category: Data Analytics

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Description: Enacted by Congress in 2020 to respond to the economic impact of the COVID-19 pandemic, the Paycheck Protection Program provided nearly $800 billion in loans to small businesses in order to retain payrolls. While the Small Business Administration has released data on more than 11.5 million approved applications from the program, they have also removed applications from the dataset that have been previously present. Using data analysis on two datasets, one which includes loans that remain in the PPP database, and one that includes loans that were removed from the PPP database, develop an understanding of why these loans may have been removed by analyzing defining characteristics in the datasets.

Team IC22001 | Project Title: Analysis of PPP Loans in Georgia
Yu-Cheng Lai | University of Maryland
Farid Freyha | University of Maryland
Nan Wang | University of Maryland

Team IC22004 | Project Title: Predicting Removed Loan –  Paycheck Protection Program Application
Chung-Hao Lee | University of Maryland
Chia-Lin Tsai | University of Maryland
Wang-Han Li | University of Maryland

Team IC22007 | Project Title: PPP data analysis
Jieqian Xiao | University of Maryland
Tianli Ding | University of Maryland
Zihan Zhang | University of Maryland
Rui Jin | University of Maryland

Team IC22009 | Project Title: The Story of Georgia
Dishant Vakte | University of Maryland
Radiah Tahsin Tanisha | University of Maryland
I-Ju Lin | University of Maryland
Naila Sharmin | University of Maryland

Team IC22015 | Project Title: Paycheck Protection Program
Chido Shamuyarira | University of Maryland
Emma Darkwa | University of Maryland
Shu-Ping Chen | University of Maryland
Wei-Yu Jen | University of Maryland

Team IC22021 | Project Title: An Exploration of Why Loan Records Are Removed from SBA Database
Amy Chan | University of Maryland
Amola Patel | University of Maryland
Yufei Deng | University of Maryland
Ziyu Liu | University of Maryland

Team IC22023 | Project Title: How To Give A Best Shoot of your Paycheck Protection Program
Kexin Xu | University of Maryland
Zhaoying Ren | University of Maryland

Team IC22029 | Project Title: Paycheck Protection Program Data Analysis
Hsin Chen | University of Maryland
Jinping Guo | University of Maryland
Jing Lin | University of Maryland
Po-Han Yen | University of Maryland

Team IC22030 | Project Title: Prediction & Analysis of Removed Loan Applications
Haoning Ke | University of Maryland
Ling Fang | University of Maryland
Upasana Mohapatra | University of Maryland
Yu-Tung Chang | University of Maryland

Team IC22031 | Project Title: Analysis of the paycheck protection program
Abhijit Haridas | University of Maryland
Drishti Jain | University of Maryland
Girish Saraf | University of Maryland
Pratyush Gupta Uddagiri | University of Maryland

Team IC22032 | Project Title: Serving the Underserved: PPP Loans in Georgia, USA
Danny Rivas | University of Maryland
Javan Reuto | University of Maryland

Team IC22046 | Project Title: Paycheck Protection Program
Ramith Wijesinghe | University of Maryland
Priyanka Chib | University of Maryland
Yi-Hua Huang | University of Maryland—ic22046.git

Team IC22047 | Project Title: PPP removed applications, Why?
Rijul Newalkar | University of Maryland
Theophile Sadio Nanzo | University of Maryland
Govinda Sri Charan Duggirala | University of Maryland, Baltimore County
Maryam Alomair | University of Maryland, Baltimore County

Team IC22052 | Project Title: Paycheck protection program: Analysis
Manikanta Koneru | University of Maryland
Jayasree Karthik Nandula | University of Maryland

UMD Dept of Transportation Services: E-Scooter Sidewalk Usage (category: design/data analytics, level 3) 🏆

Organization: UMD Department of Transportation Services
Project Name: 
Veo E-Scooter Sidewalk Usage
Design/Data Analytics

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Description: Veo is a mobility service company that provides e-scooters throughout the University of Maryland’s campus. Asking anyone about the shared e-scooter service on campus would probably elicit a wide range of opinions, but one prevailing opinion — and regulation — is an important one: deterring e-scooter operation on campus sidewalks. DOTS and Veo have provided a dataset of e-scooter route data on campus, as well as GIS map data denoting the location of all sidewalks on UMD College Park campus. The Department of Transportation Services would like to know the most traveled sidewalks that are used by e-scooter users, the hours of the day when the most infractions occur, and any other significant patterns of e-scooter routes that occur on campus sidewalks, including infractions on football or basketball game days.

Award Winner: Outstanding Data Analytics Project
Team IC22062 | Project Title: Creating a safe campus for e-scooter riders and Pedestrian
Richmond Yeboah | Montgomery College
Sumeet Ram | University of Maryland
Uzair Masih Israrahmed | University of Maryland

Team IC22010 | Project Title: E-Scooter Sidewalk Usage at UMD
Fabienne Yang | University of Maryland
Chu-Hsuan Tsao | University of Maryland
Kevin Chou | University of Maryland

Team IC22013 | Project Title: An Analysis to Optimize Strategies for Reducing Veo Scooter Traffic Infractions
Kelly Bye | US Naval Academy
West Gapasangra | US Naval Academy

Team IC22014 | Project Title: The battle for sidewalk space: Understanding pedestrian safety through VeoRide e-scooter trip data
Ruthwik Kuppachi | University of Maryland
Govind Nageswaran | University of Maryland
Iskander Lou | University of Maryland
Alibi Shokputov | University of Maryland

Team IC22016 | Project Title: VEO Ride Safety Measures
Gauri Goel | University of Maryland
Rohin Bhagavatula | University of Maryland
Parth Kodnani | University of Maryland

Team IC22019 | Project Title: Veo E-Scooter Sidewalk Usage
Anshika Patel | University of Maryland, Baltimore County
Sanaa Mironov | University of Maryland, Baltimore County
Jaganathan Velraj | University of Maryland, Baltimore County
Nick Corbin | University of Maryland, Baltimore County

UMD Department of Astronomy: All Sky Imagery (category: data analytics, level 4) 🏆

Organization: UMD Department of Astronomy
Project Name: All Sky Imagery
Category: Data Analytics

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Description: The UMD Department of Astronomy Observatory captures thousands of high-quality, 180 degree images of the sky every night. These images are stored in the Flexible Image Transport System (FITS) file format which can be read in Python as a numpy array as well as transformed into other graphic formats. These images can capture stars, planets, meteors, planes, satellites, bugs sitting on the protective dome, and even rocket launches. The Department of Astronomy is interested in using this dataset to identify and analyze the different types of objects that are captured in this imagery, as well as photometry of particular stars and any possible correlation between exposure lengths and clear or dark skies.

Award Winner: Grand Prize
Team IC22017 | Project Title: AllSky Tool
Aryan Anwar | Montgomery College
Rohit Sharma | Montgomery College
Matthew Nanas | Montgomery College

UMD Dept of Transportation Services: Traffic Flow at UMD (category: design) 🏆

Organization: UMD Department of Transportation Services
Project Name: Traffic Flow at UMD
Category: Design
Description: With the continuing and widespread increase of construction projects on campus, the flow of traffic at the University of Maryland oftentimes experiences significant disruptions. Not only do these construction projects cause impacts to vehicle traffic, but pedestrian, bike, scooter, and skateboard traffic are also disrupted across campus. The College of Information Studies is seeking creative solutions for how all types of traffic flow on campus can have minimal disruptions. This design challenge includes addressing questions such as how traffic flow can be better on campus, how pedestrian safety can be improved, and actions the university can take to mitigate traffic disruptions during future construction projects.

Award Winner: Outstanding Design Project
Team IC22054 | Project Title: Traffic Pattern Design Challenge
Siao-Ting Lin | University of Maryland
Jing Wang | University of Maryland
Jialun Yang | University of Maryland

Team IC22036
Kieran Hatton | University of Maryland
Shardul Aggarwal | University of Maryland
Tusharkanth Karlapudi | University of Maryland

UMD INFO College Career Center: WireFrames for Careers Newsletter (category: design) 🏆

Organization: UMD INFO College Career Center
Project Name: WireFrames for Careers Newsletter
Category: Design
Description: INFO College Careers is a service point within the College of Information Studies that provides support for students and alumni from all of our degree programs (InfoSci, InfoDesign, HCIM, MIM, MLIS, and PhD). iSchool Careers offers a weekly newsletter that lists career-related events happening on campus as well as internship and job opportunities that match our students’ skills. The current newsletter is very simple in its content and formatting, and the iSchool Careers team would like to improve the newsletter in both areas. They would like have creative ideas about the content and wireframes of potential formatting changes.

Award Winner: Best Team Presentation
Team IC22020 | Project Title: iSchool Career Newsletter Redesign Project
Kinny Chen | University of Maryland
Zi Lin | University of Maryland

Team IC22038 | Project Title: UMD iSchool Career Center Project
Scott Mobarry | University of Maryland
Salahdin Waji | University of Maryland
Alexandra Beleho | Montgomery College ISCXIDS2012 Cybersecurity Dataset (category: cybersecurity) 🏆

Project Name: ISCXIDS2012 Cybersecurity Dataset
Category: Cybersecurity
Description: Malicious hackers and automated malware attacks are one of the biggest threats facing cybersecurity experts today. To help encourage novel solutions to these problems, researchers at the Canadian Institute for Cybersecurity have assembled a number of datasets cybersecurity researchers and practitioners can use to evaluate their malware detection methodologies. The dataset for this challenge represents a subset of their 2012 Intrusion Detection Evaluation Dataset. Here, the UNB researchers employed real cyber attack and malware scenarios, along with background network traffic simulations to create an evaluation dataset. This dataset contains multiple possible challenges, ranging from dataset exploration, to machine learning, to novel visualizations.

Award Winner: Outstanding Cybersecurity Project
Team IC22034 | Project Title: ISCXIDS2012 Cybersecurity
Elvin Vanathayan | University of Maryland, Baltimore County
Khang Nguyen | University of Maryland, Baltimore County

Team IC22005 | Project Title: iscxIDS
Jay Siliphet | University of Maryland
Ben Nordmann | University of Maryland, Baltimore County

Team IC22024 | Project Title: Following the Attack Chain
Kade Heckel | US Naval Academy
Jennifer Jung | US Naval Academy
Christian Rose | US Naval Academy
Brenton Pieper | US Naval Academy

Team IC22033 | Project Title: – Malware Attack Classification
Nishant Jadhav | University of Maryland
Rakshit Sinha | University of Maryland
Sanjit Mahajan | University of Maryland

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