About Me
I am Jad, I will be guiding you through your AI journey, from A to Z!
Scroll down this page to know more about me and my work.
Education
PhD in Artificial Intelligence at Art et Metiers (ENSAM) in Paris (ongoing).
Some of my PhD's work:
I work primarily on AI model development for various engineering applications, specifically, generative design and dynamical systems.
I have developed many novel models currently used in numerous fields such as cancer cell modelling, fiber dynamics, and control of magnetic bearings.
Previous Degrees
Master’s in Mathematical Modelling and Scientific Computing (MMSC) from the University of Oxford.
Some of my Master's work:
I worked on various research projects that lead to new models (e.g. battery modelling), and new libraries (e.g. general finite difference solvers in python FDpy).
On my thesis, I worked on downstream classification of cancer patients using Neural Controlled Differential equations and the path signature. The report can be found here.
Bachelor’s in Mechanical Engineering from the Lebanese American University (LAU).
Some of my Bachelor's work:
I worked on multiple engineering projects such as the design of a hybrid quadricycle, an autonomous farming tractor, or an HVAC system.
I also did research work where I include thermal effects in a MOR technique for elastohydrodynamic lubrication problems.
Prizes and Publications
Prize of Excellence – University of Oxford
I was awarded a prize of excellence for scoring first on the Mathematical Modelling and Scientific Computing (MMSC) master’s degree at the University of Oxford with an average above 78/100.
Publication in AI model development (Autoencoders)
In this work, we developed a new Autoencoder architecture, Rank Reduction Autoencoders (RRAEs) that solves limitations in traditional autoencoders. The paper can be found here.
Publication in MOR techniques for Elastohyrdodynamic Lubrication Problems
In this work, we enhanced a MOR technique, to include thermal effects when solving Elastohydrodynamic Lubrication problems. The paper can be found here.
Publication in time Multiscale Modelling
In this work, we apply the partition of unity to solve a viscoelastic fatigue problem using a multiscale approach. The paper can be found here.
A few presentations
Advanced AI course – Abha, Saoudi Arabia
Short Summary:
I was the main instructor of an advanced AI course with KAUST academy. The course covered various concepts of computer vision.
CNRS@CREATE – Singapore.
Short Summary:
Presented various generative AI techniques and their applications across multiple engineering domains.
ECCOMAS – Portugal.
Short Summary:
Presented methods for learning dynamical systems using machine learning and approaches to enhance techniques such as Neural ODEs.
Universitat Politècnica de València – Spain.
Short Summary:
Presented an introduction to artificial intelligence to help students determine whether to pursue a PhD in the field.
Unversity of Oxford – United Kingdom.
Short Summary:
Presented multiple AI models (e.g. Neural CDEs, Random Forests with signatures), as well as physical models for batteries’ reactions.
