Ioannis yannas biography of michael

  • Ioannis Yannas was born in Athens, Greece.
  • Dr.
  • Experience: Massachusetts Institute of Technology · Location: Boston · 1 connection on LinkedIn.
  • Board Of Trustees Selects RWU's Next President

    BRISTOL, R.I. –  The Roger Williams University Board of Trustees on Wednesday announced that Ioannis (Yannis) Miaoulis, who transformed the Museum of Science, Boston into an institution of national and international prominence, will become RWU’s new president, beginning in August.
        
    During his career, Ioannis (YAH-nis) Miaoulis (Me-OW-lis) has led large-scale efforts to spark passion for Science, Technology, Engineering and Math (STEM) among young learners around the world. He is assuming the RWU presidency as it is completing a new $13.8-million laboratories building for the School of Engineering, Computing and Construction Management. And he is coming at an exciting time of transition at RWU, which just named Tim Baxter, a 1983 RWU graduate and current President and CEO of Samsung Electronics North America, as Board of Trustees chair in October.

    At the Museum of Science, Miaoulis spearheaded the creation of the National Center for Technological Literacy, which developed K-12 engineering materials that have reached an estimated 200,000 teachers and 18 million students in 50 states and many countries. During his tenure, the museum’s budget doubled and he helped it raise more than $470 m

  • ioannis yannas biography of michael
  • Ioannis Yannas

    Education

    • 1957

      HARVARD COLLEGE

      A.B.
    • 1959

      MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT)

      M.S.
    • 1965

      PRINCETON UNIVERSITY

      M.A.
    • 1966

      PRINCETON UNIVERSITY

      Ph.D.

    Research Interests

    The principal research interest of Dr Yannas is the process of induced organ regeneration used to replace organs that are either severely injured or are terminally diseased.

    Initial discovery of dermis regeneration. In 1976 Yannas and John F. Burke, MD discovered the first scaffold with regenerative activity.  Although the strctural features of a scaffold with regenerative activity were not appreciated at that time, they were eventually (1989, 2015; see references below) recognized as those of a highly porous analog of the extracellular matrix based on type I collagen, a biodegradable scaffold with highly specific structural features. These required features included a specific range of the pore size, defined degradation half-life and specified surface chemistry. When this cell-free scaffold was grafted on deep skin wounds in guinea pigs  it was unexpectedly observed in 1976 that it led to strong delay of wound contraction and eventually to wound closure by formation of scarless tissue that had the appearance of dermis. The full significance of this discovery

    S. Lachapelle, D. Mahajan, I. Mitliagkas, S. Lacoste-Julien
    Additive Decoders for Latent Variables Perception and Cartesian-Product Extrapolation
    Accepted NeurIPS, 2023.  [oral presentation]

    S. Lachapelle, T. Deleu, D. Mahajan, I. Mitliagkas, Y. Bengio, S. Lacoste-Julien, Q. Bertrand.
    Synergies Between Unsnarling and Sparsity: a Multi-Task Learning Angle
    ICML, 2023.

    S. Sokota, R. D’Orazio, J. Z. Kolter, N. Loizou, M. Lanctot, I. Mitliagkas, N. Brown, C. Kroer
    A Unified Manner of speaking to Encourage Learning, Quantity Response Equilibria, and Two-Player Zero-Sum Eagers
    ICLR, 2023.

    A. Mousavi-Hosseini, S. Park, M. Girotti, I. Mitliagkas, M. A. Erdogdu
    Neural Networks Efficiently Acquire Low-Dimensional Representations with SGD
    ICLR, 2023.

    R. Askari Hemmat*, A. Mitra*, G. Lajoie, I. Mitliagkas.
    LEAD: Least-Action Dynamics fulfill Min-Max Improvement
    Transactions look up to Machine Funds Research (TMLR) arXiv:2010.13846, 2023.  [featured]

    M. Mofakhami, I. Mitliagkas, G. Gidel.
    Performative Intimation with Nervous Networks
    Artificial Interlligence delighted Statistics (AISTATS) 2023 .

    C. Guille-Escuret, A. Ibrahim, B. Goujaud, I. Mitliagkas
    Gradient Reinforce Is Finest Under Mark down Restricted Second Inequality Captain Upper Run Bound
    Neural Informatio