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2018 Schlumberger Innovation Fellows Announced


Five ICME graduate students have been named 2017-2018  Schlumberger Innovation Fellows. The Schlumberger Innovation Fellows program recognizes aspiring scholars in the fields of machine learning, deep learning, high performance computing, and 3D modeling and data visualization. The award was established to encourage scholarship and research in these emerging technology areas, which hold great promise across many industries to improve performance, lower costs, increase accuracy and provide new research and business insights. 
 
This is the second year of the Schlumberger Innovation Fellows program, which, in addition to fostering collaboration between Fellows, Stanford faculty, and members of the Schlumberger Software Technology Innovation Center (STIC), includes a $10,000 Fellowship award.
 
  • Kailai Xu is a second year PhD student in ICME, advised by Professor Eric Darve. He holds a B.S. degree from Peking University studying computational mathematics. His research target is high performance computing and aims to to apply state-of-art computing techniques to the emerging problems.
  • Ines Chami is a second year ICME masters student in the Data Science track. Her research interests include computer vision, natural language processing and, more specifically, multimodal analysis.  Prior to joining Stanford, she studied mathematics and computer science at École Centrale Paris. She is currently working on information extraction from semi-structured data (pdf tables) within the Hazy Research group led by Prof. Ré at Stanford.
  • Daniel Byrnes is a second year ICME masters student. His interests include 3D modeling, motion planning, optimal control, and high-performance computing. He received his B.A. in Mathematics from Bowdoin College.
  • Miguel Ferrer Avila is a first year ICME masters student in the Computational Geosciences track conducting research in the Stanford Exploration Project. His interests include high performance and scientific computing, and numerical methods and simulations. He has a B.Sc. in Computer Science from Barcelona School of Informatics and a B.Sc. in Physics from the University of Barcelona.
  • Shervine Amidi is a first year ICME masters student in the Data Science track. His research project is in self-supervised learning at the Stanford Vision Lab (SVL) with Dr. Amir R. Zamir and Professor Silvio Savarese.  He has a B.A. and an M.S. in Engineering from École Centrale Paris.
This program is made possible with the generous support of Schlumberger, the world's leading provider of technology for reservoir characterization, drilling, production, and processing to the oil and gas industry.