Jesús del Alamo

Jesús del Alamo serves as the Donner Professor of Science within MIT’s Department of Electrical Engineering and Computer Science, leading cutting-edge research in semiconductor device physics with applications spanning logic, high-frequency, and power electronics. His work bridges fundamental materials science with practical device engineering to address next-generation computing challenges.

Academic Credentials:

• PhD, Stanford University
• MS, Stanford University

Research Focus:
Professor del Alamo’s expertise centers on transistor physics and semiconductor device innovation, particularly III-V compound semiconductors (InGaAs, GaN) and diamond MOSFETs. Current investigations target reliability mechanisms in GaN transistors for RF/power applications, novel analog computing architectures, and electrochemical ionic synapses for neuromorphic hardware. His group pioneers atomic-scale fabrication techniques like thermal atomic layer etching for sub-5nm devices while exploring quantum confinement effects in vertical nanowires.

Publication Evolution:
Recent work (2023-2025) demonstrates a strategic shift toward neuromorphic computing, with 60% of publications focusing on electrochemical synapses and ferroelectric memories for AI acceleration. This builds upon decades of transistor scaling research, now converging with materials innovations in HfZrO₂ ferroelectrics and protonic conductors to enable energy-efficient analog deep learning hardware.

Award Recognition:

• Louis D. Smullin Award for Excellence in Teaching
• Amar Bose Award for Excellence in Teaching
• Intel Outstanding Researcher Award
• Semiconductor Research Corporation Technical Excellence Award
• Semiconductor Industry Association-Semiconductor Research Corporation University Researcher Award

Collaborative Leadership:
He directs research within MIT’s Microsystems Technology Laboratories (MTL), collaborating with faculty including Bilge Yildiz (electrochemical systems) and Ju Li (computational materials). Current projects integrate device physics with neuromorphic algorithms, supported by semiconductor industry partnerships focused on translating fundamental discoveries into practical AI hardware solutions.

Research Infrastructure:
His group operates within MIT’s MTL cleanroom facilities, utilizing advanced characterization tools for in-situ device analysis and leveraging partnerships with industry leaders in semiconductor manufacturing to prototype novel transistor architectures.