Haitham Seada is a data scientist at AltairPD/Ford Motor Company. He is a Computer Science major with a master degree in Bioinformatics and a PhD in Evolutionary Multiobjective Optimization. After his PhD, Haitham joined Kim Boekelheide's lab at Brown University as a postdoc, where he developed computational pipelines to process and analyze high throughput cell culture imaging data. His current role at Ford involves creating optimization models and algorithms for vehicle routing problems and architecting software wrappers to the developed techniques. His research interests involve vehicle routing, non-linear optimization, computational intelligence, linear modeling and machine learning, as exhibited in his list of publications. For more than 8 years, Haitham used to teach a diverse selection of computer science topics to both undergraduate and graduate students at several private and public sector universities and institutions. He is also the author of several software libraries, both closed and open source, spanning a wide range of technologies.
Check his CV

@ Ford

On the 9th of July, I joined Ford Motor Company through AltairPD as a Data Scientist. I admit that my experience at Brown University went far beyond my expectations. The Boekelheide lab is the best work environment you can think of. I will miss them but I am glad to be back with my family in Michigan, doing what I do best, optimization☺️

@ Brown

On the 1st of February, I joined Kim Boekelheide's lab at the department of Pathology and Laboratory Medicine at Brown University. Well it's a big step, to a completely different type of labs! The team is really amazing and the projects have an open-ended potential.

Was a Nice Day !

At 11:00 AM, On the 28th of Spetember 2017, I defended my PhD disseration. It was a nice day. A PhD journey is overwhelming but it is defintely worth every single bit of effort.  Looking forward to the next step.

Finally,
KKTPM Calculator !

Sneak a Peek !
Just released my first version of my new library KKTPM Calculator. The library provides a simple interface for using Karush Kuhn Tucker Proximity Measure (KKTPM) proposed by Deb and Abouhawwash in 2015. KKTPM calculator supports XML-based inputs and symbolic mathematical function evaluations among other interesting features to both researchers and practitioners in the field of optimization.