Levent Burak Kara
Professor, Mechanical Engineering
Professor, Mechanical Engineering
L. Burak Kara is a professor in the Department of Mechanical Engineering, with a courtesy appointment in the Robotics Institute. His research develops new computational analysis, design, and manufacturing technologies with wide-ranging applications in the space of mechanical CAD, topology optimization, additive manufacturing, electronics design, and bio-engineering. To this end, his research combines principles of machine learning, optimization, and geometric modeling to develop new knowledge and computational software for use in next-generation design systems.
Some of his recent projects show how machine learning can aid in many of the conventionally tedious and expensive design steps. Examples include deep learned physics to replace expensive structural simulations, learning from past designs to automatically generate novel products, robust sampling to reduce the cost in combinatorial design optimization scenarios, the use of deep reinforcement learning for electronic chip design, and crowdsourcing to learn semantic maps between human preferred language and 3D computer models.
Kara is the recipient of National Science Foundation Career award and American Society of Mechanical Engineers Design Automation Society Young Investigator Award. At CMU, he teaches courses in AI and Machine learning, Engineering Design, and Linear Algebra and Vector Calculus. He earned his B.S. in Mechanical Engineering from the Middle East Technical University (1998), and his Ph.D. in Mechanical Engineering from Carnegie Mellon University (2005).
2004 Ph.D., Mechanical Engineering, Carnegie Mellon University
2000 MS, Mechanical Engineering, Carnegie Mellon University
1998 BS, Mechanical Engineering, Middle East Technical University
MechE’s Burak Kara and Conrad Tucker have been recognized as Impact Scholars and awarded $10,000 as part of Google’s AI for Social Good program. Their proposal aims to use machine learning and artificial intelligence to improve screening for oral cancers.
Carnegie Mellon University (CMU) and the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory (ARL) have entered into a $3.5 million cooperative agreement that supports machine learning-enabled additive manufacturing.
When life throws lemons to mechanical engineers, they make lemonade... and dynamic systems, geometric models, and thermal fluids experiments. There's no stopping mechanical engineers. See what we're planning for the fall semester.
CMU and Air Force Research Laboratory establish 5-year, $7.5M Center of Excellence in data-driven materials research.
A novel approach to 3D printing using a support bath can greatly expand the types of polymers that can be printed, enable chemical reactions of the printed materials to gain novel material properties, and increase the mechanical strength and reduce the print time of mechanical parts through design optimization.
Burak Kara is collaborating with Cadence Design Systems, Inc. and NVIDIA on applying advanced machine learning techniques to develop integrated and intelligent design system flows.
Design Automation Conference
MechE’s Burak Kara was a panelist at the Design Automation Conference earlier this month, discussing how innovations in machine learning, deep learning, and artificial intelligence impact electronic design automation (EDA). The panel was sponsored by Cadence Design Systems, a company Kara is collaborating with on a new project to automate the design process of electronic circuits and chips.
Kate Whitefoot and Burak Kara are developing methods allowing manufacturers to redesign multiple parts into one continuous part using 3-D printing.
In Levent Burak Kara’s project-based graduate course, students applied their skills in artificial intelligence and machine learning to solve real-world problems outside the classroom.
Levent Burak Kara develops ways to best bolster lightweight, 3-D printed materials and reduce production costs.
Carnegie Mellon engineers are leading a collaborative initiative to develop computational technologies for optimal design and fabrication of complex core structures for the aerospace industry.