I am a multidisciplinary engineering analyst and manager with over a decade of professional experience in engineering acoustics, analyzing sensor data, and systems engineering. I also chair an annual session for the American Society of Mechanical Engineers (ASME) for Analytical, Computational, Artificial Intelligence, and Machine Learning in Dynamics, Vibrations, and Acoustics and serve as a member of the Technical Committee on Vibration and Sound. I also provide peer review for publications for IEEE Sensors and a variety of other professional societies. At the moment, I am a part of collaborative research projects that involve predictive analytics, complex systems, and operations research. My intent is to creatively apply my engineering insights to tackle a wide variety of non-traditional multidisciplinary problems (such as those in the public health, medical, and economic domains) as well as learn about best practices from fields outside of engineering.
Research Interests: Creativity in Engineering Design, Operations Research, Predictive Analytics, Probability & Stochastic Processes, Signal Processing, Systems Engineering, Systems Science
Joseph Blochberger
Department of Civil & Systems Engineering
The Johns Hopkins University
3400 N. Charles St.
Baltimore, MD 21218
jblochb2@jhu.edu
Post-Masters Certificate, Electrical & Computer Engineering
Enrolled as a graduate student while working as a full-time engineering project manager. Concentrated in signal processing, machine learning, applied probability & stochastic processes, and detection & estimation theory.
Licensed Professional Engineer
Master of Science, Mechanical Engineering
Enrolled as a graduate student while working as a full-time engineer. Concentrated in computational mechanics (linear and nonlinear finite element analysis), mechanical vibrations, and engineering acoustics.
Bachelor of Science, Mechanical Engineering
Enrolled as a full-time student while managing part-time student jobs (Virginia Tech Bookstore & Virginia Tech Math Emporium). Completed two engineering internships (with Kollmorgen Motors Division and General Dynamics Electric Boat, respectively). Performed undergraduate research under the guidance of Prof. Lei Zuo on energy-harvesting shock absorbers, built an autonomous acoustic monitoring system for the NASA Langley Research Center under the guidance of Prof. Chris Fuller, and completed a minor in Engineering Science and Mechanics.
Assistant Program Manager • Engineering Analyst
Graduate Student
Signatures Engineer
Languages: MATLAB, MySQL, Mathematica, Octave, R, Python, CSS, HTML, Javascript
Skills: Acoustics, Analyzing Sensor Data, Applied Probability / Statistics, Test & Evaluation, Mechanical Engineering, Noise Control, Project Management, Sonar, Signal Processing, Systems Engineering, Vibrations
This project simulates an iterative adaptation of Schelling's Segregation Model in MATLAB. MATLAB code is available for use in private study or as a teaching tool.
Engineering
This project uses the Olivetti dataset to explore the use of singular value decomposition to identify common features of the human face.
Engineering
In my experience as an engineering project manager, I have led teams of PhD-level staff who are experts in acoustic modeling. In an effort to get smarter on the subject, I am currently exploring MATLAB implementations of a variety of acoustic modeling techniques. Shown on this website are realizations of a modal summation approach to modeling acoustic propagation in the ocean. Specifically, the method I am demonstrating here is known as the method of Normal Modes. Analogous to how notes on a guitar string are the sum of multiple modes of vibration, this approach assumes top and bottom boundary conditions of an ocean environment and sums over a finite amount of modes to obtain the pressure field visualized as a contour plot. Original code modified from: https://oalib-acoustics.org/Other/demo/MatMod.pdf
Engineering
In my anecdotal experience, I have identified at least seven electrical engineering textbooks which introduce and discuss the concept of convolution solely from an applied mathematics or algorithm perspective (Flip, Shift, Multiply, Sum). As a mechanical engineer taking graduate-level courses in signal processing, I felt the need to connect the convolution operation to a practical application found in digital audio workstation software. This project involves the application of the convolution operation to simulate a reverberation effect on a recorded signal in MATLAB. I also wrote a MATLAB demo with code available for use in private study or as a teaching tool.
Engineering
Periodic structures are commonplace in multiple industries. My research, using the finite element method and wavenumber transform analysis, quantified the structural acoustic performance of a clamped plate when considering stiffener thickness and plate thickness as design variables. This research was performed while I was a part-time MSME student at Penn State (advised by Prof. Alok Sinha) and subsequently published in ASME IMECE 2019 conference proceedings (available here).
Engineering
As an undergraduate, I took a graduate-level engineering acoustics course on engineering noise control. Throughout the course, I had a tough time developing my intuition with how the cross-sectional areas of expansion chamber designs and quarter-wave resonators affect acoustic performance. Therefore, I created this demonstration in Mathematica. This demonstration was created towards the end of my undergraduate studies and accepted for publication on the Wolfram Demonstrations Project website in 2016 (available here).
Engineering
Advised by Prof. Chris Fuller at Virginia Tech, the team behind the Smart Acoustic Monitoring System senior capstone project sought to design and implement a novel method for easier deployment of an acoustic phased array for the NASA Langley Research Center in Hampton, VA. NASA deploys these arrays in outdoor settings in order to characterize the acoustic signatures of small aircraft and unmanned aerial systems, with their current focus mainly on the latter. Current methods for deploying these arrays are lengthy, cumbersome, and labor intensive. It was the team's intent to make this process easier in the Fall 2014 and Spring 2015 semesters as part of their undergraduate senior design capstone project at Virginia Tech. This project received the "Best in Innovation & Creativity" award at the 2015 Capstone Realization of Engineering and Technology (CREATE) Exposition at Virginia Tech. A video describing the project in detail is available here.
Engineering
Advised by Prof. Lei Zuo at Virginia Tech, along with guidance from Dr. Lirong Wang and Dr. Lin Xu, the team behind the Energy Harvesting Shock Absorber project sought to design and implement a novel method for recovering dissipated energy in a conventional automobile shock absorber. Designing an energy harvesting shock absorber is a technical challenge, especially if it is planned to be retrofitted onto a vehicle such as a Hummer H2 automobile. This project captured preliminary designs for an automotive energy harvesting shock absorber and findings were translated into a future senior design project for mechanical engineering students at Virginia Tech. Ultimately, one year after I graduated from Virginia Tech, a team of 6 undergraduates completed their own undergraduate capstone project titled, "2015-2016 Senior Design: Energy Harvesting from Suspension."
EngineeringThe views, opinions, and content on this website belong to Joseph Blochberger and do not necessarily reflect the positions of either the Johns Hopkins University Applied Physics Laboratory, the General Dynamics Corporation (and its subsidiaries), or any other educational institution or company.