ASME

Journal of Computing and Information Science in Engineering

Nabil 
Anwer, Ph.D.
NABIL_ANWER

Areas of Interest

COMPUTATIONAL METROLOGY
GEOMETRIC TOLERANCING
REVERSE ENGINEERING
Ecole Normale Superieure Paris-Sarclay, France
Dr. Nabil Anwer is full professor in the department of mechanical and manufacturing engineering, Paris Sud University, France. He is a member of the International Academy of Production Research CIRP and serves as the technical secretary of the Scientific and Technical Committee Design (STC Dn). He is also a member of The Design Society, The European Society for Precision Engineering and Nanotechnology (EUSPEN), the American Society of Mechanical Engineers (ASME), and Committee member of ISO TC 213 (Geometrical Product Specifications and Verification). Dr. Nabil Anwer has special research interests in Tolerancing and Assembly, form metrology, Geometric Modelling, Additive Manufacturing, Cyber-Physical Production Systems and Digital Twin. He leaded and participated in a number of research projects funded by major French companies, French Inter-ministerial Fund, and the French National Research Agency. He published and co-authored more than 200 publications.

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Announcements

July 17 Spotlight: “Information Embedding in Additively Manufactured Parts Through Printing Speed Control” 

A recording is now available for the July 17, 2024 JCISE Spotlight talk by Professor Jitesh Panchal on paper co-authored with Karim A. ElSayed entitled “Information Embedding in Additively Manufactured Parts Through Printing Speed Control” J. Comput. Inf. Sci. Eng. J. Comput. Inf. Sci. Eng. Jul 2024, 24(7): 071005 (10 pages) Paper No: JCISE-23-1496 https://doi.org/10.1115/1.4065089.

Announcements

June 18, 2024 Spotlight: “Updating Nonlinear Stochastic Dynamics of an Uncertain Nozzle Model Using Probabilistic Learning With Partial Observability and Incomplete Dataset”

A recording is now available on Youtube for the June 18, 2024 Spotlight talk by Professor Christian Soize (Université Gustave Eiffel) on his paper “Updating Nonlinear Stochastic Dynamics of an Uncertain Nozzle Model Using Probabilistic Learning With Partial Observability and Incomplete Dataset,”

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