Carnegie Mellon University

Practicum Project

Work with the smartest minds at CMU to develop and improve ideas as an INI Practicum Project sponsor!

Through the practicum experience, teams of INI students in information networking, security, and mobile and IoT engineering collaborate with industry sponsors to tackle problems, pilot new ideas and establish proof-of-concept for top companies, agencies and organizations. These projects span a variety of topics in computing, mobile systems and security, and range from fundamental research to software development.

Why Sponsor a Practicum Project? 

lightbulb-clear.pngMeaningful Impact

Practicum projects are an outstanding way for companies to work with the smartest minds at CMU in order to develop and improve ideas. Students leverage their background and experience to provide novel approaches to a project that will have meaningful impact on the company.

grad-icon.pngRecruitment Opportunity

Sponsoring a practicum grants companies early access to exceptionally qualified INI students. From pitching project proposals to the entire pool of talented INI students to working closely with a small project team, the practicum environment is ideal for evaluation and recruiting.

Have an idea for a project? Connect with our Practicum Team and we can help move it forward.

 Explore Projects

202320222021|

2020 | 2019

How It Works

3-6 Students Per Team

Matched according to skill sets and interests

14 Weeks

During CMU's fall or spring semester, which is typically 14 weeks.

1400+ Hours of Work

Teams of 5 log throughout the semester

Submit a Proposal!  

We welcome proposals from corporate, government and research sponsors. Please review each step below for instructions on preparing and submitting your proposal.

The INI Practicum Proposal form collects information about potential practicum project sponsors, including details about the sponsoring organization, the project and the student background skills required for project success on the project.

Sponsorship Information:

  • Contact information for a technical and a business contact
  • Sponsoring company or organization name
  • Name of faculty/staff contact at CMU, if applicable
  • Whether INI and CMU may publicize sponsor's involvement in the INI Practicum
  • Confirmation that sponsor will agree to the terms and conditions of our Educational Project Agreement 
  • Please note that sponsorship includes a financial contribution:
    $40k for-profit entities
    $36k CyLab Partner
    $25k small businesses (as defined by SBA)
    $0 government organizations and non-profits 

2. Proposal Submission: You will have the option of submitting your proposal by either entering responses into a series of text boxes or providing a link to a proposal document. In either case, the proposal must include the following:

  • Brief-yet-descriptive project title that captures the essence of the project
  • Few-sentence summary of the project and goals
  • Detailed, several-paragraph description of the project, including background, motivation, technical challenges, relevant technologies, etc.
  • Short list of expected project goals or outcomes that the project team could aim for. For example, explain a prototype or demo that would be of interest to the sponsor. Please note that educational projects are not allowed to have specific technical deliverables that are required by the sponsor.

3. Project Skills Requirement: You will be asked to rank skills that are required or beneficial to the project, such as cloud computing, machine learning, secure coding, etc. 

Sponsorship of INI Practicum projects is done under a CMU Educational Project Agreement (EPA) and requires a financial contribution to the INI, the amount depending on the sponsoring organization as:

$40k for-profit entities
$36k CyLab Partner
$25k for small businesses (as defined by SBA)
$0 for government organizations and non-profits

Negotiation of the agreement's terms and conditions are subject to an increase in sponsorship fees and must be initiated as soon as possible. Please note that certain terms are non-negotiable.

Practicum at CMU Silicon Valley

CMU students retain ownership of their intellectual property. At the above levels of sponsorship, sponsoring companies receive a non-exclusive, royalty-free, commercial-use license to use the student work product from the project course. Additionally, the teams share an archive of their work with the sponsor at the end of the semester. Sponsors interested in additional IP rights can negotiate directly with the students after the end of the academic semester.

Submit your proposal

Want to chat about this opportunity? Contact the INI practicum team by email with questions.

Recent Sponsors 

99P Labs • Aptiv • Carnegie Mellon University  Bosch • City of El Paso • City of Portland • DemocracyLab • SCION • CMU Robotics Institute • SLAC ...and more! 

Students demonstrating the fling-to-display gesture at Google's headquarters.

Google

"Practicum gives us an opportunity to explore projects from a perspective that we normally wouldn't be able to take. This is essentially the number one goal, along with creating better future tech employees!"

TREVOR PERING

Cisco Cyberwarfare Practicum Team

99P Labs

"An INI practicum partnership allows your company to engage young, agile minds who bring new perspectives for tackling relevant problems with support from top faculty and industry leaders."

Ryan Lingo

SLAC Practicum Team

SLAC National Accelerator Laboratory

"The value for us is to meet and benefit from the contributions of top students, who bring an amazing energy and enthusiasm, and an amazing set of skills and new tools."

SILA KILICCOTE

Quin Practicum Team

Quin

"The students completed the proof-of-concept to validate the idea, added features and resolved issues along the way. That's tremendous help for me to take the next step for my work."

YEN-MING CHEN

Recent Project Examples

Activity Detection Using RF & Sensor Data Fusion

Sponsor: Bosch | Fall 2023

This project aims to leverage RF sensor and BLE technologies to enhance the detection and monitoring of a wide range of human activities, from basic movements to complex actions including yoga poses, utilizing ML and DL techniques.

The focus includes data acquisition from sensor nodes, and development of tailored ML models for activity detection, while embedded programming on provided hardware is not in scope. 

Current ML Models for activity detection do not cater to a wide range of activities and do not emphasize on physical wellness for elderly people that this project targets.

 

Control of a Passively Steered Rover

Sponsor: CMU Robotics Institute | Fall 2023

The project focuses on developing the Zoe 2 rover, a compact and technologically advanced successor to Zoe 1, equipped with a 3D kinematic model-based controller. The primary use case is for the rover to navigate precisely on challenging terrains such as deserts and other rough landscapes on Earth. The aim is to enhance the rover's effectiveness in terrestrial exploration, showcasing its capabilities in real-world scenarios.

Monitor Creative Cloud Express with AIOps

Sponsor: Adobe | Fall 2022

The team built a Machine Learning system, based on incoming metrics, to help site reliability engineers (SREs) analyze the large amounts of data and provide monitoring and anomaly detection. Given the incoming metrics from Prometheus, the team decided the right statistics for the metrics in the system and created corresponding alerts for these statistics.

Smartphone-based Peer-to-peer Blockchain-enabled Compute & Workload Sharing

Sponsor: Honda Development & Manufacturing of America | Fall 2022

Today, smart cars rely on cloud based services for computational needs such as predicting efficient routes and preventing accidents. Can we offload computation tasks to idle cars? In the team's project, they designed a system where idle cars may perform computation tasks requested  by other cars and earn cryptocurrency in return. 

Security Analysis of Consumer IoT System 

Sponsor: Carnegie Mellon University | Fall 2021

With the rapid increase of IoT devices, the attack surface of in-home networks has grown significantly, imposing a security risk since these devices have become a primary target for cybercriminals. Many different types of attacks could be avoided with an anomaly detection system that aims to reduce the risk of IoT device attacks. The team developed the foundation for an anomaly detection system that specifically performs data collection and device type identification in the network. To achieve this, different tools and methods were used to complete each task including Scapy (powerful packet manipulation program), nProbe (extensible NetFlow probe/collector), and Machine Learning (ML) algorithms. Training of the ML models using a decision tree classifier and random forest classifier resulted in an accuracy of 97% and 98% respectively. These results contribute to the foundation of a more complex IoT anomaly detection system that will apply an ML detection model for each identified IoT device.

BLOSEM: Blockchain for Optimized Security and Energy Management 

Sponsor: SLAC | Fall 2021

Establishing end-to-end security of critical grid infrastructure such as grid assets is one of the most challenging areas in energy infrastructure management. Compromised assets installed in the energy grid can expose the entire energy delivery system to cyber threats and risk the collapse of critical national infrastructure. This project involves working with SLAC National Accelerator Labs to enhance grid resilience against cyber attacks by developing a blockchain-based distributed, decentralized, and privacy-preserving supply-chain management system. The system is used to verify grid asset integrity through the supply chain and identify if the assets were tampered with during transit. Particularly, the system is designed to protect against clone attacks and false data injection attacks on grid assets.

Internet-of-Things Data Fusion

Sponsor: National Security Agency | Fall 2020

As their proliferation increases, Internet-of-Things (IoT) devices continue to generate more data and new types of information. Such devices are increasingly used by personnel in military installations, creating digital dust that presents a growing operational security concern for National Security Agency and Department of Defense organizations. This project team seeks to better understand how different IoT datasets could interact with each other and provide intelligence to adversaries. 

Serverless SIEM/Log Management Solution 

Sponsor: Procter & Gamble | Fall 2020

As a multinational company, P&G has Security Operations Center (SOC) teams that rely on SIEM (Security information and event management) systems to collect and aggregate event logs from across the enterprise to analyze and respond to security incidents. However, SIEM solutions have been expensive and difficult to scale. Therefore, this project team seeks to design and implement a scalable SIEM based on the existing cloud service infrastructure.