Faculty Advisor: Adjunct Faculty, Carnegie Mellon School of Computer Science

What is Accelerated Research Practicum

Accelerated Research Practicum combines both recorded and live sessions with the Faculty Advisor and allows students to achieve tangible outcomes and potentially earn a letter of recommendation in a shorter period of time.

Practicum Introduction

Humans and machines have different capabilities. Steve Jobs, decades ago, waxed eloquent on the amplification of human ability by referring to the efficiency of man with a bicycle. With the increasing prevalence of Artificial Intelligence (AI), the debate is shifting to how machines can complement people, scaling human performance and expertise as well as reducing risk. Frameworks for and best practices in teaming are just starting to evolve in different milieus. Data, mores, task goals, and component capabilities may dictate the overall team architecture. This is a fertile ground for learning and experimenting in a contemporary sandbox. Bias-free implementations with attention to ethical considerations are a focus area. 

In this project, the Faculty Advisor will provide motivating scenarios along with pathways for exploration. Participants will get a taste for data analysis and concepts in AI. This innovative practicum will lay a foundation for critical, data-oriented thinking and problem solving in a technologically advancing world.

The faculty advisor will guide students on which topic they should choose for their final project. Students will have access to a combination of videos, notes, and project topics that they can pursue for their final projects. 

At the end of the program, each student will complete a concise 3-5 page research paper or proposal, and submit it to the faculty advisor for a final review.

Possible Topics For Final Project:

• Human-Machine teaming for Health: How can wellness and clinical care be improved by combining expert clinicians and tools?

• Human-Machine teaming in the Wealth milieu: Predicting stock prices, analyzing economic data

• Human-Machine teaming in the Wisdom milieu: How to disseminate reliable information in a world with over-flooded information? 

• Human-Machine teaming for prediction: How to design surveys and polling to inform results of future events (in sports, politics, etc.) 

• Human-Machine teaming for social responsibility: How to reduce bias via teaming? How to achieve social justice?

• Or other topics in this subject area that you are interested in, and that your professor approves after discussing it with you

Program Detail

• Cohort Size: 2-5 students

• Duration: 4 weeks

• Target Students: 7-12th grade students who are interested in Computer Science, Artificial Intelligence, Data Analytics, FinTech, Healthcare Technology, or Machine Learning and wish to complete a research project with a prestigious professor rapidly to boost their research experience and obtain deliverables that can be used for college applications and other programs.

Program Structure

• Week 1: Students and the faculty advisor will discuss in a live session the available project topics and agree on a set of goals for the project. 

• Week 1-3: Students will complete an extensive recorded video research program, including core videos that must be completed and optional advanced videos for students with higher aims.

• Week 4: Students will complete their research project and submit for review. They will also have a second live session with their faculty advisor to ask questions, discuss their findings, and conclude their research experience very positively.