Electronic and Photonic Devices

Pursuing theoretical and experimental research for next generation devices.

We explore various device technologies, material science and device architectures to dramatically improve power and RF device performance to achieve higher efficiency, high linearity and much wider frequency band. We develop novel photonic integrated circuits to improve performance and reduce cost in optical communications applications.

  • Researchers

  • Awards


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  • News & Events

    •  NEWS   MERL and Mitsubishi Electric U.S. participating in International Microwave Symposium Week 2021
      Date: June 18, 2021
      MERL Contacts: Mouhacine Benosman; Rui Ma
      Research Areas: Electronic and Photonic Devices, Machine Learning, Signal Processing
      Brief
      • During the 2021 International Microwave Symposium Week (June 20-25), Rui Ma will give an invited talk on MERL's recent power amplifiers research at an IMS Technical Workshop to be held on June 21st, titled "From Digital to Intelligent: Advancement of MISO Power Amplifiers by Machine Learning".

        IMS is the annual flagship conference of IEEE MTT-S (Microwave Theory and Techniques Society) and the centerpiece of Microwave Week. It is the largest gathering of RF/Microwave professionals in the world and combines multiple technical conferences with the biggest commercial exhibitions for the microwave industry.

        Mitsubishi Electric U.S. (MEUS) will also host an online interactive booth to showcase our latest high-frequency Semiconductor & Device products at IMS week.

        More detailed information can be found at the Mitsubishi Electric booth.
    •  
    •  NEWS   Research on Intelligent Power Amplifier is Cover Story of Microwave Journal
      Date: April 15, 2021
      MERL Contacts: Mouhacine Benosman; Rui Ma; Koon Hoo Teo
      Research Areas: Communications, Electronic and Photonic Devices, Machine Learning
      Brief
      • The cover article in the April issue of Microwave Journal features MERL and MELCO's invited paper entitled "A New Frontier for Power Amplifiers Enabled by Machine Learning". Our recent research applying ML for optimizing operating conditions of advanced power amplifier designs is highlighted.

        Since 1958, Microwave Journal has been the leading source for information about RF and Microwave technology, design techniques, news, events and educational information. Microwave Journal reaches 50,000 qualified readers monthly with a print magazine that has a global reach.
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  • Internships

    • MD1561: Desgn and fabrication of power devices in power electronics or RF

      MERL is seeking a highly motivated, qualified individual to join our 3-month internship program to carry out research in the area of power electronics and RF semiconductors devices. The ideal candidate should have a significant background in the simulation and design of a 2D and 3D GaN devices using Matlab and TCAD. Proficiency in device semiconductor modeling or hands-on experience in GaN device fabrication processes and a deep knowledge of negative capacitance would be a great asset. Candidates who hold a PhD or in their senior years of a Ph.D. program are encouraged to apply. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • MD1648: THz Electronic Sensing

      MERL is looking for a senior Ph.D. student to join our team to conduct application-motivated research and experiments. The candidate must have hands-on practical lab experiment experience on millimeter-wave, sub-THz, or THz for sensing, radar, and other applications. Skills of using RF/Microwave Lab equipment are necessary. Knowledge of solid-state device physics, high frequency, and high speed integrated circuit (IC) chip design, and signal processing is desired. The internship is expected to be 3-6 months, starting date is flexible after September. This internship requires work that can only be done at MERL.

    • SP1504: Coherent Imaging Systems

      MERL is seeking an intern to work on coherent optical imaging. The ideal candidate would be an experienced PhD student or post-graduate researcher working in coherent imaging. The candidate should have a detailed knowledge of optical interferometry and imaging with a focus on either optical coherence tomography, optical coherence microscopy or FMCW LIDAR. Strong programming skills in MATLAB are essential. Experience of working in an optical lab environment is a required. Duration is 3 to 6 months. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.


    See All Internships for Electronic and Photonic Devices
  • Recent Publications

    •  Tang, Y., Kojima, K., Koike-Akino, T., Wang, Y., Jha, D., Parsons, K., Qi, M., "Nano-Optic Broadband Power Splitter Design via Cycle-Consistent Adversarial Deep Learning", Conference on Lasers and Electro-Optics (CLEO), May 2021.
      BibTeX TR2021-045 PDF Presentation
      • @inproceedings{Tang2021may3,
      • author = {Tang, Yingheng and Kojima, Keisuke and Koike-Akino, Toshiaki and Wang, Ye and Jha, Devesh and Parsons, Kieran and Qi, Minghao},
      • title = {Nano-Optic Broadband Power Splitter Design via Cycle-Consistent Adversarial Deep Learning},
      • booktitle = {Conference on Lasers and Electro-Optics (CLEO)},
      • year = 2021,
      • month = may,
      • url = {https://www.merl.com/publications/TR2021-045}
      • }
    •  Fujihashi, T., Koike-Akino, T., Watanabe, T., Orlik, P.V., "HoloCast+: Hybrid Digital-Analog Transmission for Graceful Point Cloud Delivery with Graph Fourier Transform", IEEE Transactions on Multimedia, DOI: 10.1109/​TMM.2021.3077772, May 2021.
      BibTeX TR2021-043 PDF
      • @article{Fujihashi2021may,
      • author = {Fujihashi, Takuya and Koike-Akino, Toshiaki and Watanabe, Takashi and Orlik, Philip V.},
      • title = {HoloCast+: Hybrid Digital-Analog Transmission for Graceful Point Cloud Delivery with Graph Fourier Transform},
      • journal = {IEEE Transactions on Multimedia},
      • year = 2021,
      • month = may,
      • doi = {10.1109/TMM.2021.3077772},
      • url = {https://www.merl.com/publications/TR2021-043}
      • }
    •  Tang, Y., Kojima, K., Gotoda, M., Nishikawa, S., Hayashi, S., Koike-Akino, T., Parsons, K., Meissner, T., Song, B., Sang, F., Yi, X., Klamkin, J., "InP Grating Coupler Design for Vertical Coupling of InP and Silicon Chips," Tech. Rep. TR2021-034, MERL Technical Report, May 2021.
      BibTeX TR2021-034 PDF
      • @techreport{Tang2021may2,
      • author = {Tang, Yingheng and Kojima, Keisuke and Gotoda, Mitsunobu and Nishikawa, Satoshi and Hayashi, Shusaku and Koike-Akino, Toshiaki and Parsons, Kieran and Meissner, Thomas and Song, Bowen and Sang, Fengqiao and Yi, Xiongsheng and Klamkin, Jonathan},
      • title = {InP Grating Coupler Design for Vertical Coupling of InP and Silicon Chips},
      • institution = {MERL Technical Report},
      • year = 2021,
      • month = may,
      • url = {https://www.merl.com/publications/TR2021-034}
      • }
    •  Tang, Y., Kojima, K., Gotoda, M., Nishikawa, S., Hayashi, S., Koike-Akino, T., Parsons, K., Meissner, T., Song, B., Sang, F., Yi, X., Klamkin, J., "InP Grating Coupler Design for Vertical Coupling of InP and Silicon Chips," Tech. Rep. TR2021-034, MERL Technical Report, May 2021.
      BibTeX TR2021-034 PDF
      • @techreport{Tang2021may,
      • author = {Tang, Yingheng and Kojima, Keisuke and Gotoda, Mitsunobu and Nishikawa, Satoshi and Hayashi, Shusaku and Koike-Akino, Toshiaki and Parsons, Kieran and Meissner, Thomas and Song, Bowen and Sang, Fengqiao and Yi, Xiongsheng and Klamkin, Jonathan},
      • title = {InP Grating Coupler Design for Vertical Coupling of InP and Silicon Chips},
      • institution = {MERL Technical Report},
      • year = 2021,
      • month = may,
      • url = {https://www.merl.com/publications/TR2021-034}
      • }
    •  Ma, R., Komatsuszaki, Y., Benosman, M., Yamanaka, K., Shinjo, S., "A New Frontier for Power Amplifier enabled by Machine Learning", Microwave Journal, No. 4, pp. 22-32, April 2021.
      BibTeX TR2021-030 PDF
      • @article{Ma2021apr,
      • author = {Ma, Rui and Komatsuszaki, Yuji and Benosman, Mouhacine and Yamanaka, Koji and Shinjo, Shintaro},
      • title = {A New Frontier for Power Amplifier enabled by Machine Learning},
      • journal = {Microwave Journal},
      • year = 2021,
      • number = 4,
      • pages = {22--32},
      • month = apr,
      • issn = {0192-6225},
      • url = {https://www.merl.com/publications/TR2021-030}
      • }
    •  Teo, K.H., "International Conference on Electron Device Meeting Report," Tech. Rep. TR2021-017, Mitsubishi Electric Research Laboratories, March 2021.
      BibTeX TR2021-017 PDF
      • @techreport{Teo2021mar,
      • author = {Teo, Koon Hoo},
      • title = {International Conference on Electron Device Meeting Report},
      • institution = {for MERL Tech Report},
      • year = 2021,
      • month = mar,
      • url = {https://www.merl.com/publications/TR2021-017}
      • }
    •  Kojima, K., Tang, Y., Koike-Akino, T., Wang, Y., Jha, D., TaherSima, M., Parsons, K., "Application of Deep Learning for Nanophotonic Device Design", SPIE Photonics West, Bahram Jalali and Ken-ichi Kitayama, Eds., DOI: 10.1117/​12.2579104, March 2021.
      BibTeX TR2020-182 PDF Video
      • @inproceedings{Kojima2021mar,
      • author = {Kojima, Keisuke and Tang, Yingheng and Koike-Akino, Toshiaki and Wang, Ye and Jha, Devesh and TaherSima, Mohammad and Parsons, Kieran},
      • title = {Application of Deep Learning for Nanophotonic Device Design},
      • booktitle = {SPIE Photonics West},
      • year = 2021,
      • editor = {Bahram Jalali and Ken-ichi Kitayama},
      • month = mar,
      • publisher = {SPIE},
      • doi = {10.1117/12.2579104},
      • url = {https://www.merl.com/publications/TR2020-182}
      • }
    •  Kojima, K., TaherSima, M., Koike-Akino, T., Jha, D., Tang, Y., Wang, Y., Parsons, K., "Deep Neural Networks for Inverse Design of Nanophotonic Devices", IEEE Journal of Lightwave Technology, DOI: 10.1109/​JLT.2021.3050083, January 2021.
      BibTeX TR2021-001 PDF
      • @article{Kojima2021jan,
      • author = {Kojima, Keisuke and TaherSima, Mohammad and Koike-Akino, Toshiaki and Jha, Devesh and Tang, Yingheng and Wang, Ye and Parsons, Kieran},
      • title = {Deep Neural Networks for Inverse Design of Nanophotonic Devices},
      • journal = {IEEE Journal of Lightwave Technology},
      • year = 2021,
      • month = jan,
      • doi = {10.1109/JLT.2021.3050083},
      • issn = {1558-2213},
      • url = {https://www.merl.com/publications/TR2021-001}
      • }
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  • Videos