Jeremy M. Gernand, PhD, CSP, CRE Associate Professor of Environmental Health and Safety Engineering
Associate Department Head for Graduate Education
John and Willie Leone Department of Energy and Mineral Engineering
College of Earth and Mineral Sciences
The Pennsylvania State University, University Park, PA, USA
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The overall goal of my educational contributions at Penn State is to increase the capacity of future engineers to use quantitative risk analysis methods including probabilistic models and data informatics to improve engineers' abilities to "hold paramount the health and safety of the public." These courses are based on my 8-year professional career as a Safety and Reliability Engineer, as well as graduate training in Engineering and Public Policy.

I currently teach (or have taught) the following courses at the Penn State University Park campus. Dates for future planned course offerings are tentative until the official course schedule is released by the university.

Penn State Courses

ENVSE 400: Safety Engineering

This course includes an investigation of the regulatory and ethical basis for considering safety in the engineering design of systems and operations, as well as the analytical methods for identifying, controlling, and reducing safety risks. Students learn how to identify hazards in a system, develop controls for those hazards, and assess the overall level of risk in a system or operation.

ENVSE 470: Engineering Risk Analysis

This course trains engineering students in qualitative and quantitative techniques for risk analysis including reliability statistics, fault tree analysis (FTA), and failure modes and effects analysis (FMEA). This course investigates how can we use the concepts of probability to understand uncertain future events and the interaction between an engineered system and its environment.

EME 524: Machine Learning for Engineering Problems

This course explores the theory and application of machine learning algorithms relevant to the problems and data sets typical in engineering research and problem solving. Specifically, the creation and validation of machine learning models such as classification and regression trees, artificial neural networks, hierarchical clustering, and genetic algorithms among \ others. Students have the opportunity apply these techniques to further their own research or explore new directions of interest.

EME 551: Safety and Environmental Risk Analysis

This course explores methods applicable to quantitative risk assessment for engineering systems including a probabilistic understanding of failure and disasters, the validity of test results and the likelihood and effects of human error and cognitive biases around risk, as well as methodical qualitative analysis techniques for designing more robust, fault tolerant systems.

EBF 304W: Global Management for the Energy and Mineral Industries

How should decision makers in a business decide what to do in the face of uncertain project outcomes or the potential for risks from spills, worker injuries, or public opposition? Students in this class learn analytical methods for decision making under conditions of uncertainty and apply these in the context of real world scenarios facing energy and mineral extraction businesses. This course satisfies university requirements for "writing across the curriculum".

Online Courses

I have several online short courses in development and will post updates here once that content becomes available.


There are multiple short course training options available in the areas of safety engineering, regulatory policy for engineers, risk analysis, reliability engineering, and related topics. Potential clients interested in scheduling a short course in-person at your facility or online, should contact me via the following address: