Background

Life at Bucknell’s campus is vibrant and full of opportunities for students to be active. Additionally, visitors to campus often need to know about parking and events that are happening. There is an obvious need for an all around campus assistant that visitors, students, and faculty can use to stay up to date with what is happening on campus.

Executive Summary

A tool like this could take the form of an app and a web page. Both would have the same functionality, and having both would allow for visitors to campus to find resources they need without having to find an app they might not know about. The app should be able to provide the user with relevant campus events, available parking for visitors and students, and help facilitate community involvement in events by advertising them.

Viability Analysis

A key piece of this project will be keeping the app up to date with relevant events. Ways to keep the app up to date would be to set up a script to scrape bucknell websites and automatically create new events based on what is posted on bucknell websites (like the main page, different athletic pages, weis center main page, etc). A different option would include creating a simple way to create a new event on the app and let, either through a whitelist or just by anybody, people post events. Other problems could be letting users use the app without service. Cell service at Bucknell and surrounding areas is not always the best, and this could prove problematic.

Risks and Rewards

The main risk in this app is that is doesn’t have much room to grow. A Bucknell campus assistant is an app that can only be used at Bucknell. On the other hand, the app could be developed in a way that leaves it more general. This could lead to a whole suite of apps that can become campus assistants for many schools. In addition, the app could clear up annual commotion that happens with annual events (like the high school swimming tournament that is hosted).

Closing

Bucknell is a campus that is always buzzing. Whether it is busy with an athletic event or the campus is hosting some national event, there is always something going on. Students and visitors alike are often interested in these events and other things that go on. At times the influxes of people can cause unexpected commotion on campus that leads to parking and other problems. An app that solves these issues would not only help Bucknell students, but could even lead to a whole new design for campus assistant apps.

Background

Medical education is very similar in learning a language in that it takes repetition of concepts over years. Many medical professionals use books, question banks, and journals to keep from losing their knowledge. This situation begs for an app that can help medical students and professionals learn and keep the skills they need.

Executive Summary

An obvious solution to the described problem is a mobile app. Something like this should be tailored to each user in a way that allows a specific medical professional to choose what they should and shouldn’t be quizzed on. The system should be able to notify a user when they might be getting rusty on a subject. A key feature of the app would be to allow users to compare themselves to others in the same field. Leaderboards on subjects that can be filtered by medical field, age, and level of expertise are some features that would be desireable. To build on the competitive aspect, a game where two medical professionals could be matched up and directly compete in a quiz would be interesting.

Viability Analysis

The difficulty in this system will be building a database of questions that can be used by all kinds of medical professionals. Manually building this could in itself take months. Other options for building a database of questions could be setting up a script that scrapes online journals and question banks for questions or even partnering with medical professionals from different disciplines to help generate questions that can be put in the database. Questions could even be crowdsourced and the app could be user driven to take the necessity of medical knowledge out of the realm of the programmers.

Risks and Rewards

There are not too many risks involved in this project’s development that I can foresee. Building a database of questions from so many different medical disciplines that doesn’t grow incredibly large might be an issue. Because medical professionals deal with people’s lives, this app would also have to have correct answers to relevant questions. If the app was delivered well and had accurate questions though, the reward could be high. This app could be used by all medical professionals, and thus could have a big user base.

Closing

The large field of medicine is one that all doctors have to learn. This learning is repetitive and has be permanent. This project is to build an app that can help students learn and help professionals keep their knowledge fresh. The risks for this project are not much. The software would be nothing revolutionary and there are already questions that can be found online to use. The rewards on the other hand are apparent. A built in user base comes with the territory of building an app for medical professionals. Additionally, this project has good potential to be monetized.

Capturing Emotional Reactions to Data Visualization Preproposal

Background

As technology advances and more and more data is taken of nearly everything, there is an interesting gap in data about what people feel. This would be emotional data. Whether somebody is watching a movie, playing a videogame, or looking at a data visualization, people react emotionally. This sort of data can always be asked for afterwords by using a survey, but does that really give a good indication of what somebody was feeling at the exact moment they saw a scene in a horror film or a chart light up? A system that could accurately take emotional data would revolutionize the field of data science and could open up the doors to entirely new fields of research.

Executive Summary

This project should be able to take emotional data and make it available to a user. This can be done using body sensors or simply using facial recognition software. Currently, there is existing software that can recognize frowns, anger, happiness, etc through a webcam in real-time. Additionally, there are open-source tools for eye tracking. A tool that can combine these two data sources could be very powerful. The tool should be able to take data at specific time increments, or at predefined times, or could even hook up to programs to take data based on specific program events. Emotional data could change the landscape of data science, and a tool that makes taking data easy could be the first commercial tool to do so.

Viability

The main constraint to the success of this project is image quality. The tool mentioned above can recognize facial expressions in real time, so speed of this algorithm is not a problem. Additionally, open source eye tracking tools already exist. This project not only seems viable but it looks like it could be the next big step in data science. Image quality could be a huge problem though. Do we want this app to work on all sorts of cameras, or only certain ones? Should this work for mobile? These are questions that will have to be thought about more as the project develops and we become more comfortable with the tools that can be used.

Risks and Rewards

The primary risk of this project is privacy. Users will of course have to opt in to use the tool, but how do we protect user data from there? Massive companies that collect data consistently deal with these issues, how will we deal with it as well. Another risk is hoping that the APIs we plan on using work as desired. No software is perfect, and diving into a project that relies on third party software can be a great risk. One the other hand, this project has the potential to revolutionize the way companies collect and use data. The reward of this project is creating a tool that can and should be universally used.

Closing

Data is collected on everything possible. From what you hover your mouse over, to everything you type into a search bar. In many ways, this has made our lives significantly more convenient. Google knows what I want to search before I type it in. Amazon tells me what to buy. However, none of the data that is taken is based on human emotion, the thing that drives people. Imagine a non-evil company that was able to take emotional. This company would be able to find out what drives people. Emotional data is the future of data science, and this project can be one of the first steps in making it a reality.

Lukas Munoz

lukasmunoz255@gmail.com

 

EDUCATION

Bucknell University
Bachelor of Science in Computer Science and Engineering
Bachelor of Arts in Mathematics
 

EXPERIENCE

Google Inc. – New York, New York
Software Engineering Intern

• Implemented reliable logging system for corporate database transactions
• Utilized newly released API’s and database frameworks
• Added to existing corporate database transaction API
• Worked with Producers framework: Google’s asynchronous Java library

Google Inc. – Chicago, Illinois
Engineering Practicum Intern

• Worked on large scale infrastructure refactoring project on GWS (Google Web Server) team
• Created development guide for future GWS infrastructure refactoring
• Communicated closely with other internal teams to enable seamless restructuring of non-GWS code
• Acted as a TA for the Chicago Computer Science Summer Institute program

Google Inc. – Kirkland, Washington
Engineering Practicum Intern

• Utilized in-house systems by learning internal API’s and communicating with other teams
• Implemented auto-fill feature on Google Compare mobile site
• Fixed numerous team user experience bugs in Javascript and CSS

Google Inc. – Seattle and Kirkland, Washington
Computer Science Summer Institute Participant

• Selected to participate in a three-week intensive computer science curriculum
• Worked with two other participants to create whattoweartest.appspot.com in three days
• Implemented clothing selection and closet display details for “What to Wear” web application
• Worked with Google App Engine to build backend storage system for “What to Wear” web application

AlphaWorks Capital – Chicago, Illinois
Software Engineering  Intern

• Wrote trade data collection tools using C++
• Created graphical GUI for analysis of trading algorithms in C#
• Used Microsoft CLI language to create data retrieval API

 

SKILLS & INDIVIDUAL PROJECTS

Java – 5 years

• Created a zombie shooter game over the course of six months using Java graphics library
• Implemented Huffman Compression Algorithm

Python – 2 years

• Wrote space adventure game using Pygame library

JavaScript – 1 year

• Created retro frogger game from scratch using canvas: froggercssi.appspot.com

C++ – less than 1 year

• Created a simple autocorrect algorithm implementing a graph data structure
• Utilized recursive techniques for functions of autocorrect algorithm

 

ACADEMIC AWARDS & DISTINCTIONS    

• Elected member of Pi Mu Epsilon national honorary mathematics society
• National Hispanic Recognition Program Scholar
• Eagle Scout, Boy Scouts of America

 

EXTRACURRICULAR ACTIVITIES

• Bucknell Division 1 Lacrosse Team
• Tutor at North Chicago’s Section 8 Federal Subsidized Forrestal Schools
• Volunteer at Great Lakes Adaptive Sports Association