Akis sakellariou biography of alberta

Atmospheric composition in the European Arctic and 30 years of the Zeppelin Observatory, Ny-Ålesund

Evaluation and optimization of ICOS atmosphere station data as part of the labeling process

Camille Yver-Kwok, Carole Philippon, Peter Bergamaschi, Tobias Biermann, Francescopiero Calzolari, Huilin Chen, Sebastien Conil, Paolo Cristofanelli, Marc Delmotte, Juha Hatakka, Michal Heliasz, Ove Hermansen, Kateřina Komínková, Dagmar Kubistin, Nicolas Kumps, Olivier Laurent, Tuomas Laurila, Irene Lehner, Janne Levula, Matthias Lindauer, Morgan Lopez, Ivan Mammarella, Giovanni Manca, Per Marklund, Jean-Marc Metzger, Meelis Mölder, Stephen M. Platt, Michel Ramonet, Leonard Rivier, Bert Scheeren, Mahesh Kumar Sha, Paul Smith, Martin Steinbacher, Gabriela Vítková, and Simon Wyss

Atmos. Meas. Tech., 14, 89–116, https://doi.org/10.5194/amt-14-89-2021,https://doi.org/10.5194/amt-14-89-2021, 2021

Short summary
  • Sakellariou (forthcoming) provides cross-country analysis
  • From November 2020 to June

    • Institute of Computer Science-FORTH

    Comparative species delimitation: examples with lizards
    Human Face, Expression, and Emotion 3D Modeling using Deep Learning
    Speaker: Panagiotis Filntisis, Postdoctoral Researcher, Athena Research Center
    Deep Neural Network Compression with Emphasis on Sparsification Techniques
    Speaker: George Retsinas, Postdoctoral Researcher, Athena Research Center
    3D Gaussian Splatting: Past, Present and Future
    Speaker: George Drettakis, Senior Researcher, Inria, Team Leader GRAPHDECO , Inria Centre d'Université Côte d'Azur, Sophia-Antipolis, France

    Past Lectures

    • 3D Gaussian Splatting: Past, Present and Future
      Speaker : George Drettakis, Senior Researcher, Inria, Team Leader GRAPHDECO , Inria Centre d'Université Côte d'Azur, Sophia-Antipolis, France
      Date : 26.09.2024
      Location : “Stelios Orphanoudakis” Meeting Room (Foundation for Research and Technology-Hellas)
      Host : Prof. Yannis Tzitzikas
    • Robot motion planning in crowded environments
      Speaker : Prof. Luigi Palopoli, Department of Information Engineering and Computer Science, University of Trento
      Date : 02.07.2024
      Location : Vassilis Dougalis Room – FORTH, Science and Technology Park of Crete, ground floor
      Host : Prof. Antonis Argyros
    • Diffusion Generative AI Images for Science
      Speaker : David Donoho, Professor of Statistics, Stanford University
      Date : 17.05.2024
      Location : Fotakis Seminar Room - FORTH, Main Building, 1st floor
      Host : Jean-Luc Starck and Panagiotis Tsakalides
    • Systems research in the era of AI
      Speaker : Prof. Christos Kozyrakis, Stanford University, http://www.stanford.edu/~kozyraki
      Date : 09.02.2024
      Location : East Campus Amphitheater (CARV building), FORTH
      Host : Angelos Bilas, Manolis Katevenis
    • From deep network mysteries to physics
      Speaker : Stéphane Mallat Professor, Collège de France https://www.di.ens.fr/~mall
    • EECERA is an independent, self-governing, international
    • Akis, S., Peristianis, N. and

      • Asilomar AI Principles

      These principles were developed in conjunction with the 2017 Asilomar conference (videos here), through the process described here.

      Click here to see this page in other languages:  ChineseGermanJapaneseKoreanRussian

      Artificial intelligence has already provided beneficial tools that are used every day by people around the world. Its continued development, guided by the following principles, will offer amazing opportunities to help and empower people in the decades and centuries ahead.

      Research Issues

      1) Research Goal: The goal of AI research should be to create not undirected intelligence, but beneficial intelligence.

      2) Research Funding: Investments in AI should be accompanied by funding for research on ensuring its beneficial use, including thorny questions in computer science, economics, law, ethics, and social studies, such as:

      • How can we make future AI systems highly robust, so that they do what we want without malfunctioning or getting hacked?
      • How can we grow our prosperity through automation while maintaining people’s resources and purpose?
      • How can we update our legal systems to be more fair and efficient, to keep pace with AI, and to manage the risks associated with AI?
      • What set of values should AI be aligned with, and what legal and ethical status should it have?

      3) Science-Policy Link: There should be constructive and healthy exchange between AI researchers and policy-makers.

      4) Research Culture: A culture of cooperation, trust, and transparency should be fostered among researchers and developers of AI.

      5) Race Avoidance: Teams developing AI systems should actively cooperate to avoid corner-cutting on safety standards.

      Ethics and Values

      6) Safety: AI systems should be safe and secure throughout their operational lifetime, and verifiably so where applicable and feasible.

      7) Failure Transparency: If an AI system causes harm, it should be possible to ascertain why.

      8) Judicial Transparency: An

      .