- Ph.D., Physics, University of California, Irvine, 2018
- M.S., Physics, University of California, Irvine, 2016
- B.S., Applied Physics, University of California, Davis, 2012
- Data Science Foundations Professional Certificate
- IBM Data Science Professional Certificate
- IBM Python Data Science Professional Certificate
- Postdoctoral Researcher, Physics of Quantum Materials, Max Planck Institute for the Chemical Physics of Solids, Dresden, Germany, 2018-2021
- Graduate Student Researcher, Department of Physics and Astronomy, University of California, Irvine, 2014-2018
- Research Engineer, Western Digital, San Jose, CA, 2017
- Teaching Assistant, Department of Physics and Astronomy, University of California, Irvine, 2013-2014
- Data Scientist, Defense MicroElectronic Activity, Department of Defense, McClellan, CA 2011-2013
- Undergraduate Grader, Department of Physics and Astronomy, University of California, Davis, 2009
- Undergraduate Researcher, Department of Physics and Astronomy, University of California, Davis, 2009
Dr. Alex Stern implements technology driven solutions to rapidly changing problems for a variety of clients in both the commercial and government sectors. Leveraging his background in computational simulations and high-precision measurements, he can add value to any part of the data science lifecycle, including data collection, data analysis, quality assurance, machine learning modeling, and the communication of results.
While performing all these tasks, Alex seeks to always put the customer's needs first and to establish a clear line of communication on the value generated.
Prior to joining Exponent, Alex worked as a postdoctoral researcher at the Max Planck Institute for the Chemical Physics of Solids in Dresden, Germany, where he continued pioneering new measurement techniques to probe unconventional quantum crystal materials. His projects included developing uniaxial strain techniques, which involved suspending a narrow crystal bar between two clamps to change the long axis of the bar in situ by about 1% and drastically change the material's properties. Alex was only the second person to publish a scientific paper using this measurement technique, which has now become a popular tool for cutting-edge physics research.
The experiments were performed with high-precision electronics and custom-made scientific equipment to provide highly accurate quantitative results. To complete such projects, Alex designed custom experimental equipment, programmed experiment specific simulations, developed high-precision data collection environments, analyzed data, wrote peer-reviewed papers, and presented results at international conferences.
Dr. Stern received a Ph.D. in Physics from the University of California, Irvine in the field of condensed matter physics, where he performed electrical, optical, and strain experiments on exotic crystal materials, through which he acquired extensive experience in experimental design, simulations, and high-precision measurements.
Before attending graduate school, Alex worked at the Department of Defense co-leading an engineering group that programmed data science techniques for the identification of electronic functionality with a high degree of confidence, which never produced a false-positive result. Additionally, Alex has experience in electronic design, electronic fabrication, and image processing.
Furthermore, Alex has developed a diverse skillset including: a variety of programming languages, data science, data engineering, distributed systems, image processing, image recognition, conference presentation, scientific writing, electronic design, machine learning, cryogenics, magneto-optical measurements, and high precision electrical measurements.
Currently, Alex works on a multidisciplinary team to quickly respond to customer's challenges and develop machine learning algorithms to generate value. By utilizing a variety and technology tools, the team pursues creative solutions to existing and future problems. The group can assist any client through any part of the data lifecycle.