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    Workshop: Scaling AI for Business Impact

    Thu, November 20, 2025 Workshop
    Cambridge, MA

    Designed for senior leaders, innovation officers, and executives, the workshop combines expert guidance with peer learning in an intimate setting. Through hands-on exercises and facilitated discussions, attendees will gain practical frameworks and clear direction for driving AI adoption across their organizations.

  • 2025 MIT AI Conference

    Tue, April 1, 2025 Conference
    Boston Marriott Cambridge

    For over 80 years, the digital revolution has redefined how we work, learn, and collaborate, reshaping societies and economies worldwide. Today, the rapid advancements in Artificial Intelligence and Machine Learning are accelerating this transformation, pushing the boundaries of what humans and machines can achieve together. 

    The 2025 MIT AI Conference will analyze the latest AI trends, groundbreaking developments, and their profound implications for the future of knowledge, work, skills, and intelligence.

  • October 1, 2008

    Business Created from the Innovation Jam

  • SMR-Logo
    April 13, 2020

    Education, disrupted

  • Carlo
    Ratti

    Professor of the Practice / Director, SENSEable City Laboratory
    Primary DLC
    Department of Urban Studies and Planning

    Contact

    MIT Room
    9-216
    Phone
    (617) 253-7926
    ratti@mit.edu
  • 2023 Korea Conference

    2023 MIT Korea Conference

    Fri, April 28, 2023 Conference

    The 2023 MIT Korea Conference, co-organized with the Korea Pharmaceutical and Bio-Pharma Manufacturers Association (KPBMA), will bring you closer to the MIT ecosystem and allow you to explore global trends in MIT’s innovative Drug Discovery and Manufacturing research and experiments from leading MIT faculty and MIT-connected startups. 

  • August 1, 2009

    Creating a Better Environment for Finance

  • Aragao

    Jeehwan Kim - 2017 ICT Conference

    April 12, 2017Conference Video Duration: 41:34

    Extremely cost-effective semiconductor layer-transfer process via graphene & Highly uniform advanced RRAM

    As a strategy to save the cost of expensive substrates in semiconductor processing, the technique called “layer-transfer” has been developed. In order to achieve real cost-reduction via the “layer-transfer”, the following needs to be insured: (1) Reusability of the expensive substrate, (2) Minimal substrate refurbishment step after the layer release, (3) Fast release rate, and (4) Precise control of a released interface. Although a number of layer transfer methods have been developed including chemical lift-off, optical lift-off, and mechanical lift-off, none of those three methods fully satisfies conditions listed above. In this talk, we will discuss our recent development in a “graphene-based layer-transfer” process that could fully satisfy the above requirements, where epitaxial graphene can serve as a universal seed layer to grow single-crystalline GaN, III-V, II-VI and IV semiconductor films and a release layer that allows precise and repeatable release at the graphene surface. We will further discuss about cost-effective, defect-free heterointergration of semiconductors using graphene-based layer transfers.

    Lastly, I will introduce our new research activities in developing advanced RRAM devices. Resistive switching devices have attracted tremendous attention due to their high endurance, sub-nanosecond switching, long retention, scalability, low power consumption, and CMOS compatibility. RRAMs have also emerged as a promising candidate for non-Von Neumann computing architectures based on neuromorphic and machine learning systems to deal with “big data” problems such as pattern recognition from large amounts of data sets. However, currently reported RRAM devices have not shown uniform switching behaviors across the devices with high on-off ratio which holds up commercialization of RRAM-based data storages as well as demonstration of large-scale neuromorphic functions. Recently, we redesigned RRAM devices and this new device structure exhibits most of functions required for large-array memories and neuromorphic computing, which are (1) excellent retention with high endurance, (2) excellent device uniformity, (3) high on/off current ratio, and (4) current suppression in low voltage regime. I will discuss about the characterization results of this new RRAM device.

    2017 MIT Information and Communication Technologies Conference
  • John Hansman

    Jeehwan Kim - 2017 Japan

    January 27, 2017Conference Video Duration: 35:41

    Extremely cost-effective semiconductor layer-transfer process via graphene & Highly uniform advanced RRAM

    As a strategy to save the cost of expensive substrates in semiconductor processing, the technique called “layer-transfer” has been developed. In order to achieve real cost-reduction via the “layer-transfer”, the following needs to be insured: (1) Reusability of the expensive substrate, (2) Minimal substrate refurbishment step after the layer release, (3) Fast release rate, and (4) Precise control of a released interface. Although a number of layer transfer methods have been developed including chemical lift-off, optical lift-off, and mechanical lift-off, none of those three methods fully satisfies conditions listed above. In this talk, we will discuss our recent development in a “graphene-based layer-transfer” process that could fully satisfy the above requirements, where epitaxial graphene can serve as a universal seed layer to grow single-crystalline GaN, III-V, II-VI and IV semiconductor films and a release layer that allows precise and repeatable release at the graphene surface. We will further discuss about cost-effective, defect-free heterointergration of semiconductors using graphene-based layer transfers.

    Lastly, I will introduce our new research activities in developing advanced RRAM devices. Resistive switching devices have attracted tremendous attention due to their high endurance, sub-nanosecond switching, long retention, scalability, low power consumption, and CMOS compatibility. RRAMs have also emerged as a promising candidate for non-Von Neumann computing architectures based on neuromorphic and machine learning systems to deal with “big data” problems such as pattern recognition from large amounts of data sets. However, currently reported RRAM devices have not shown uniform switching behaviors across the devices with high on-off ratio which holds up commercialization of RRAM-based data storages as well as demonstration of large-scale neuromorphic functions. Recently, we redesigned RRAM devices and this new device structure exhibits most of functions required for large-array memories and neuromorphic computing, which are (1) excellent retention with high endurance, (2) excellent device uniformity, (3) high on/off current ratio, and (4) current suppression in low voltage regime. I will discuss about the characterization results of this new RRAM device.

  • 2019 Management

    2021 MIT Innovations in Management Conference

    September 22 - 23, 2021 Conference
    MIT Samberg Conference Center

    Once the disruption of the pandemic settles, successful leaders need to address pressing issues in challenging, different fronts amidst an exponentially changing world. CEOs must face unprecedented demands from the their company’s workforce, customers, Board, investors, suppliers, and regulators, and must answer the questions at hand. How will we measure and improve corporate culture? How can we can shape the technologies transforming work? What is the future of eCommerce and omnichannel strategies? How do we assign decision rights for organizational acceleration? How will organizations systematically innovate and build technology organizations? How will organizations successfully implement hybrid work environments? Join us to hear from MIT faculty and MIT Startup Exchange entrepreneurs to learn how to navigate this new era with management best practices.

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