Ming C. Wu (Advisor)

Research Advised by Professor Ming C. Wu

Sangyoon Han

Alumni
Electrical Engineering and Computer Sciences
Professor Ming C. Wu (Advisor)
Ph.D. 2016, PostDoc 2016

Sangyoon Han is an alumnus of BSAC and currently an assistant professor at DGIST, Korea. He received the B.S. degree in Electrical Engineering from the Seoul National University in 2010, and the Ph.D. degree in Electrical Engineering and Computer Sciences from the University of California, Berkeley in 2016. From 2016 to 2020, he was a postdoctoral researcher at the physics department, KAIST, Korea. His research interests include silicon photonics, non-linear optics, MEMS, heterogeneous integration, and LIDAR. He has authored and co-authored over 30 papers in leading technical journals and...

Packaging of Si Photonic MEMS Switches

Johannes Henriksson
2022
Spring 2022 BSAC Research Review Presentation View Slides View Presentation

Fast optical switches have been proposed as a promising alternative to enable continual scaling of data centers with increasing size and data rates We have previously demonstrated the largest integrated optical switch reported to date, a 240x240...

Amirmahdi Honardoost

Postdoctoral Researcher
Electrical Engineering and Computer Sciences
Professor Ming C. Wu (Advisor)
PostDoc 2022

I received a Ph.D. degree in Electrical Engineering from the University of Central Florida UCF, Orlando, FL, in May 2020. During my Ph.D. studies at UCF, I was with the CREOL, the College of Optics and Photonics, as a graduate research assistant in Prof. Sasan Fathpour's IPES group, working on design, fabrication, and characterization of photonic integrated circuits focusing on thin-film lithium niobate devices such as electro-optic modulators, and second-order nonlinear optical frequency converters. From May to August 2019, I was with the imec USA, as a photonics research intern. In May...

Johannes Henriksson

Graduate Student Researcher
Electrical Engineering and Computer Sciences
Professor Ming C. Wu (Advisor)
Ph.D. 2022 (Anticipated)

Johannes graduated from Lund University, Sweden, with a Masters degree in Engineering Physics which also included one year at UCLA as an exchange student. He has work experience from BorgWarner, ON Semiconductor and Lawrence Livermore National Laboratory and Apple. Johannes is currently pursuing his PhD degree in Electrical Engineering and Computer Science at UC Berkeley where he is working with Prof. Ming Wu on MEMS and silicon photonics.

BPN960: Low-Loss Silicon Photonic MEMS Switches

Amirmahdi Honardoost
Johannes Henriksson
Kyungmok Kwon
Jianheng Luo
Jean-Etienne Tremblay
Mizuki Shirao
2021

Our group has previously developed a new architecture suitable for building large-scale MEMS-based silicon photonics optical switches with fast response time. Switches with the scale of 240x240 were demonstrated using our new architecture consisting of an in-plane optical crossbar network with MEMS-actuated couplers implemented on a silicon photonics platform. Increasing the integration level up to 1000x1000 switches and beyond can result in a significant overall optical loss. In a new project we are aiming to develop low-loss switch units in order to address the aforementioned issue by...

BPN961: Scalable Photonic Integrated Circuits for Trapped Ion Quantum Computers

Daniel Klawson
Sara Mouradian
Rohan Kumar
2022

Quantum computing is a new paradigm of computing that promises exponential performance increases for certain tasks as compared to classical computers. Trapped ions have been identified as a favorable medium – trapped ion quantum computers perform operations on singular atoms with precisely aimed laser pulses calibrated to state transitions within the ions’ energy levels. Bulk free space optics are currently used for qubit manipulation, but the large amount of optical equipment required hinders scalability. Recent pushes to build higher bit systems have identified photonic integrated...

BPN957: MEMS Switch Based Integrated FTIR

Jianheng Luo
Johannes Henriksson
2022

This project aims to develop integrated FTIR technology for material detection using MEMS-based photonic switch as building block. This implementation of integrated FTIR promises high resolution (1cm^-1) on small chip size ( 5mm x 5mm).

BPN949: Optoelectronic Reservoir Computing

Philip L. Jacobson
2022

As the demand for faster, more efficient training of neural networks continues to grow, specialized photonic hardware has emerged as a potential alternative to classical computers for AI applications. Reservoir Computing (RC), a lightweight alternative to computationally-intensive Recurrent Neural Networks, has been demonstrated to be possible using simple delay dynamical systems. We propose an optoelectronic implementation of this architecture through a Mach-Zehnder modulator driven by delayed feedback from a laser. We introduce a new optoelectronic scheme in which input data is first pre...

BPN751: Large-Scale Silicon Photonic MEMS Switch with Sub-Microsecond Response Time

Johannes Henriksson
Jianheng Luo
Amirmahdi Honardoost
2022

We developed a new architecture suitable for building a large-scale optical switch with fast response time. We have demonstrated switches with a scale of 240x240 and speed of sub microsecond using our new architecture. The switch architecture consists of an optical crossbar network with MEMS-actuated couplers and is implemented on a silicon photonics platform. To our knowledge this is the largest monolithic switch, and the largest silicon photonic integrated circuit, reported to date. The passive matrix architecture of our switch is fundamentally more scalable than that of multistage...