Jeremy M. Gernand, PhD, CRE, CSP
Associate Professor | Environmental Health and Safety
Engineering
John and Willie Leone Family Department of Energy and Mineral Engineering
The
Pennsylvania State University
121 Hosler Building | University Park, PA 16802 | jmgernand
[at] psu [dot] edu | 814.865.5861
© 2013-
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-
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.
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.
Course offered annually in the Fall semester.
[Fa 2014, Fa 2015, Fa 2016, Fa 2017,
Fa 2018, Fa 2019, Fa 2020]
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.
Course offered annually in the Spring semester.
[Sp 2014, Sp 2015, Sp 2016, Sp 2017,
Sp 2018, Sp 2019, Sp 2020, Sp 2021]
EME 524
Machine Learning for EME 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.
Course offered every other year in the Fall semester.
As EGEE 597: [Fa 2014, Fa 2016];
As EME 524: [TBA]
EME 551
Safety and Environmental Risk Analysis for EME Systems
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.
Course offered annually in the Spring semester.
[Sp 2019, Sp 2020, Sp 2021]
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”.
Course offered annually. I taught it in the Spring semester between 2014 and 2017.
[Sp 2014, Sp 2015, Sp 2016, Sp 2017]
EME 460
Geo-
The course covers engineering evaluation of geo-
Course offered annually in both semesters. I participated as co-
[Sp 2016]