AiPEX Lab

Artificial Intelligence in Products Engineered for X (AiPEX) Lab

Our research explores the use of machine learning methods that predictively improve the outcome of product design solutions through the acquisition, fusion and mining of large-scale, publicly-available data. It has been reported that 70-80% of the costs of a product are determined during the design phase. Here, the term product is used in a general sense to refer to physical/digital systems that are guided by user needs, and that require domain knowledge to create. Towards enhancing the efficiency of the design process and creating personalized solutions, our research focuses on three thrust areas, outlined below.

Our lifelong research and education goals are tightly integrated and focus on advancing personalization, both from a design and learning perspective.

Faculty

Conrad Tucker

Conrad Tucker

Director of CMU-Africa and Associate Dean for International Affairs-Africa

Professor of Mechanical Engineering

Courtesy Appointments, Biomedical Engineering, Machine Learning, Robotics Institute

Dr. Conrad Tucker is a professor of mechanical engineering and holds courtesy faculty appointments in Machine Learning, Robotics, and Biomedical Engineering at Carnegie Mellon University. His research focuses on the design and optimization of systems through the acquisition, integration and mining of large scale, disparate data.

Dr. Tucker has served as PI/Co-PI on federally/non-federally funded grants from the National Science Foundation (NSF), the Air Force Office of Scientific Research (AFOSR), the Defense Advanced Research Projects Agency (DARPA), the Army Research Laboratory (ARL), the Office of Naval Research (ONR) via the NSF Center for eDesign, and the Bill and Melinda Gates Foundation (BMGF). In February 2016, he was invited by National Academy of Engineering (NAE) President Dr. Dan Mote, to serve as a member of the Advisory Committee for the NAE Frontiers of Engineering Education (FOEE) Symposium. He received his Ph.D., M.S. (Industrial Engineering), and MBA degrees from the University of Illinois at Urbana-Champaign, and his B.S. in Mechanical Engineering from Rose-Hulman Institute of Technology.

Email
conradt@andrew.cmu.edu
Google Scholar
Conrad Tucker
▲ Back to the top

Research thrusts

  • Research Thrust 1: Product Feature Discovery and Quantification: research imageIt is often stated that product customization is limited by the difficulty of addressing individual needs and converting them into product specifications. This research thrust seeks to advance machine understanding of user needs through the mining of large scale, publicly-available data (e.g., social media networks such as Twitter) for scalable and efficient product customization.
  • Research Thrust 2: Conceptual Design Generation and Evaluation: This research thrust seeks to create scalable ways to generate personalized design concepts, based on individuals’ unique needs. The evaluation of generated designs is grounded in a fundamental understanding of our physical universe and the laws that govern it. We explore ways to teach machines how to learn the relationships between design concepts and the environments/constraints that they must operate in.research image
  • Research Thrust 3: Information Veracity and Security: Ascertaining the veracity and security of data in the information age is a challenge both for humans (e.g., communicating within social media networks) and machines (e.g., training data for artificial neural networks). A lack of data veracity has the potential to “fool” both machines, as well as humans into achieving unintended outcomes/output. We explore ways to ensure the veracity of data used to train machine learning models in order to avoid garbage-in, garbage-out outcomes during the design process.research image

 

Project videos

Below, you'll find videos related to research and projects from the AiPEX Lab. ▲ Back to the top

Research team

Junghun Lee

Junghun Lee

Doctorate

Research interests
design, AI
Email
junghunl@andrew.cmu.edu
Jennifer Evans

Jennifer Evans

Doctorate

Co-Advisor
Jon Cagan
Research interests
AI, Machine Learning applied to problem solving, intuitive decision making, innovative design
Email
jennifee@andrew.cmu.edu
Conan Guo

Conan Guo

Doctorate

Research interests
Robotics, Deep Learning
Email
ccguo@andrew.cmu.edu
Daniel Nguyen

Daniel Nguyen

Doctorate

Research interests
Deep Learning, controls, dextrous manipulation
Email
dtn2@andrew.cmu.edu
James Cunnningham

James Cunningham

Doctorate

Research interests
Deep Learning/Reinforcement Learning
Email
jamescun@andrew.cmu.edu
Ananyananda Dasari

Ananyananda Dasari

Doctorate

Research interests
Deep Learning, Machine Vision, Healthcare
Email
adasari@andrew.cmu.edu
Jessica Ezemba

Jessica Ezemba

Doctorate

Research interests
Product design, function/physics based design, graphic neural networks, generative design
Email
jezemba@andrew.cmu.edu
Madeleine Weaver

Madeleine Weaver

Masters

Research interests
human-robot interaction, biomimicry, machine learning
▲ Back to the top

Publications

Engineering and STEM

Peer Reviewed Journal Publications

Peer-Reviewed Conference Publications

Healthcare

Peer Reviewed Journal Publications

Peer Reviewed Conference Publications

▲ Back to the top

Visit to CMU-Africa

View the photo slide show from the Upanzi Network Digital Public Goods Workshop.

The Upanzi Network Digital Public Goods Workshop - March 24-25, 2022 ▲ Back to the top