Turki Haj Mohamad

I'm a data scientist working in system analytics at PARC, where I support the development and launch of new IoT ventures such as Eloque. In the past year, I have been developing algorithms for structural health monitoring using fiber optic technology.

I'm passionate about developing and implementing innovative machine learning algorithms integrated with my engineering knowledge to solve complex problems.

My background is in predictive maintenance, data analytics and machine learning.

<Recent News>

(September 2021) I was selected to chair the "Diagnostics and Anomaly Detection" session at the PHM 2021 conference [Learn more]

(May 2021) Our paper on "Application of Deep CNN-LSTM Network to Gear Fault Diagnostics" is accepted for publication at IEEE PHM 2021

(May 2021) Received the 2021 ME department in Dynamics and Control PhD Award

(April 2021) Book chapter on "Delamination Fault Compensation in Composite Structures" is published as a proceeding to VETOMAC XV [here].

(April 2021) Serving as TPC member in PHM 2021 conference

(February 2021) Our paper on "Early Detection of Cracks in a Gear Train System Using Proper and Smooth Orthogonal Decompositions" is accepted for publication at NODYCON 2021

(February 2021) Passed my PhD dissertation defense

(January 2021) Joined PARC as a data scientist in system analytics

(October 2020) Joined Strados Labs as a part-time data scientist

(October 2020) Selected to be chair of "Deep Learning Methods and Applications" session at the PHM 2020 conference (Learn more)

(July 2020) A provisional patent that covers novel fault diagnostic algorithms was filled - a co-invention with Dr. Nat

(May 2020) VCADS low cost ventilator is featured in Forbes (read full article)

(May 2020) Book chapter published on proper and smooth orthogonal decompositions for detection of inner race defects in bearings (learn more)

(April 2020) Journal paper accepted on fault identification and severity analysis of rolling element bearings (learn more)

(April 2020) Work with Siemens was accepted at the AIChE conference 2020, San Francisco