Mingoo Seok

He has created novel analog, mixed-signal, and digital circuits and system architecture that improve performance, energy-efficiency, robustness, and area-efficiency and enable new features such as artificial intelligence and machine learning. His group has prototyped more than 40 test chips for demonstrations. In 2017 he won a National Science Foundation Faculty Early Career Development (CAREER) award for his project focused on next-generation computing chip design.

Of particular interest to Seok are circuits, architecture adaptive to manufacturing process, temperature, voltage variations, and long-term wearout. He is also interested in integrated compact power converter circuits, to optimally design them with load circuits via non-conventional (e.g., event-driven) control systems. Another interest of his is machine-learning models and implementation for hardware systems having limited resources.

Seok received the BS (summa cum laude) in electrical engineering from Seoul National University, South Korea, in 2005, and the MS and PhD degree from University of Michigan in 2007 and 2011, respectively, both in electrical engineering. He was a member of technical staff in Texas Instruments, Dallas in 2011. He joined Columbia University in 2012.

Research Areas

• Natural Language Processing and Speech
• Security and Privacy
• Computer Architecture and Engineering
• Artificial Intelligence (AI) and Machine Learning (ML)
• Design Automation
• Edge Computing
• Internet of Things (IoT) and Industry 4.0
• Analog Devices
• Computer Systems and Computer Engineering
• Control Systems
• Digital Devices
• Embedded Systems
• Hardware Accelerators
• Integrated Circuits and Systems
• Very Large-Scale Integration (VLSI)
• Computer Vision and Speech Processing
• Energy Efficiency and Conservation Technology
• Neuromorphic Computing
• Sensor Systems
• Silicon Photonics
• Sustainable Computing (Green Computing)