Complex software systems and cloud-native architectures require mathematical and algorithmic skills beyond those taught in regular computer science classes. With a Ph.D. in theoretical physics and 25 years of experience in the software industry, I provide in-depth, specialized advice and expertise for difficult, unusual, and challenging problems at the intersection of computation, applied math, and software development.
Typical areas of engagement include:
Determining the health of a complex and inteconnected system requires more than time-series analysis of logfile data. Instead, we need mathematical models for the expected behavior in order to define criteria to identify outliers and anomalies. Methods from statistical process control then detect anomalous conditions early and reliably, and trigger corrective actions.
Adapting to variable loads and working conditions through auto-scaling and active queue managment is a requirement for reliable operations. Control theory and feedback designs have long been used in the engineering professions to build reliable systems, but are almost unknown to software professionals. I have written “the book” on control theory for computer systems. If you have a control problem, I can help.
Optimization problems, in particular combinatorial optimizations (traveling salesman-type problems, such as routing, scheduling, bin fitting problems) in general cannot be solved using textbook methods, but require problem-specific approximation methods and heuristics. (I once solved a client’s scheduling problem using methods from Quantum Field Theory.)
Green energy, robotics, materials or bio-science start-ups must find solutions that are constrained by the laws of nature. As a Ph.D. in physics, I can help you understand this particular problem space and distinguish ideas that are merely difficult from those that are physically impossible, and perform the necessary calculations to develop practical, actionable solutions.
Numerical analysis and computationally intensive programming projects? Discrete event simulations? Defect reduction and preventive maintance? Data model, dashboard, control tower design? Stuff too weird to describe? Maybe we should talk…
Philipp K. Janert obtained a Ph.D. in Theoretical Physics from the University of Washington (Seattle) in 1997, and has worked in the tech industry ever since, both in the United States and overseas. He spent four years at Amazon, optimizing Amazon’s order fulfillment systems and processes.
His particular interest is the intersection of mathematical modeling and software design. He specializes in combinatorial optimization and in the the application of control theoretic ideas (like feedback and process control) to enterprise systems.
He is the author of several books on data analysis, visualization, and applied math, including the best-selling Data Analysis with Open Source Tools (O’Reilly, 2010), which was one of the very first books on data science, before the term was even invented.
Visit his personal website and blog at janert.me.
Questions? Let’s talk.
Email me at contact AT principal-value DOT com
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