Saleeby was formerly a research staff member from Oak Ridge National Laboratory where he was in the Manufacturing Science Division. His work focuses on connecting machines and manufacturing processes with Industry 4.0 and Industrial IoT technologies. Current interests center on applications of data analytics and closed-loop control for Hybrid Manufacturing processes, where additive and subtractive (machining) processes are combined within a single machine tool.

Billyde Brown is a Senior Research Faculty and Education and Workforce Development (EWD) Director at the Georgia Tech Manufacturing Institute (GTMI), one of eleven interdisciplinary research institutes at the Georgia Institute of Technology. Dr. Brown also serves as a Manufacturing Advisor at the Georgia MBDA (Minority Business Development Agency) Business Center where he connects minority-owned business clients with resources and expertise at Georgia Tech and provides assistance with prototyping and engineering services.

Brown’s overall role at GTMI is to create strong partnerships among industry, government, and academia in the area of manufacturing research, development, and deployment, while acquiring and managing sponsored research programs. Brown is currently the Principal Investigator of an Advanced Regenerative Manufacturing Institute (ARMI BioFabUSA) funded project to develop a wireless sensor system for real-time in-situ monitoring of critical quality attributes including pH, glucose, lactate, and protein biomarkers in human mesenchymal stem cell expansion bioreactors.

In regard to EWD, Brown manages a Manufacturing Certificate program and proctors a Manufacturing Seminar Course for the Georgia Tech College of Engineering while hosting a 10-week GTMI Lunch and Learn Lecture Series each semester with high profile industry, government, and academic speakers to share advanced manufacturing knowledge within a global community. Brown also coordinates an annual 10-week Research Experience for Undergraduates (REU) summer program called REVAMP (Research Experiences for student Veterans in Advanced Manufacturing and entrePreneurship) sponsored by the National Science Foundation that maintains target demographics of 50% student veterans and 40% underrepresented minorities with STEM majors.

Brown has strong expertise in several technical areas including electrochemical biosensors for bioprocess monitoring, thin-film manufacturing (CVD, PVD, ALD, AJP), nanomaterial synthesis and characterization, and electrochemical energy storage. Brown has over 20 peer-reviewed publications and is a regular reviewer of high impact factor peer reviewed journals. He earned his B.S. and Ph.D. degrees in Electrical Engineering from NC State University and Duke University, respectively.

Dr. Kan Wang is a research faculty in the Georgia Tech Manufacturing Institute at Georgia Institute of Technology. Dr. Wang's current research focus inerests include tissue engineering, bioprintinng, biosensors, and supply chain of regenerative medicine. He has conducted over 15 research projects sponsored by major federal agencies including National Science Foundation, Food and Drug Administration, Department of Defense and Department of Veterans Affairs. Dr. Wang has published 4 book chapters, over 50 peer-reviewed journal articles and 5 patents.

Andrew Dugenske is the Director of the Factory Information Systems (FIS) Center and a Principal Research Engineer at the Georgia Tech Manufacturing Institute (GTMI). He is also founder and C.E.O. of Factory Right LLC, a software company that provides information technology solutions to manufacturing enterprises and was co-founder and president of Great Technological Collaborations Inc. In addition, Mr. Dugenske is a State of Georgia registered professional engineer.

For the past 20 years, Mr. Dugenske has led dozens of industry-funded projects relating to software systems and supply chain issues across a variety of industries. He currently acts as an industry liaison for Georgia Tech, conducts short courses, publishes, and consults in the area of Factory Information Systems (FIS). He is a member of the National Electronics Manufacturing Initiative (NEMI) FIS working and implementation groups, the NEMI road mapping team, several IPC technical committees, the JISSO International Council and the joint NEMI-IPC CAMX standardization committees.  Prior to his arrival at GTMI, Mr. Dugenske was a Research Engineer at the Georgia Tech Research Institute (GTRI), where he developed computer-controlled radar positioning systems, conducted structural analysis using finite element analysis, and provided design expertise.  He received a B.S. from the University of Illinois, an M.S. from the Georgia Institute of Technology both in Mechanical Engineering.

Zach Brunson is a Research Engineer in the G. W. Woodruff School of Mechanical Engineering at the Georgia Institute of Technology, working primarily at the Advanced Manufacturing Pilot Facility (AMPF). Prior to Georgia Tech, Zach was a graduate teaching fellow and research assistant at the Colorado School of Mines in Golden Colorado where he received his Ph.D. (2021) and M.S. (2019) in Mechanical Engineering studying theoretical and experimental mechanics of inelastic anisotropic and asymmetric materials. Prior to pursuing a graduate degree, Zach gained experience working as a measurements field engineer in the petroleum industry (2013-2015) after earning his B.S. (2013) in Mechanical Engineering from the University of Colorado in Boulder Colorado. 

Zach’s research revolves around as manufactured material property prediction, measurement, and certification. The two major thrusts of his research are: (1) theoretical and experimental mechanics of inelastic anisotropic and asymmetric materials and (2) sensor development for process monitoring and part qualification in directed energy deposition (DED) additive manufacturing (AM) systems. By developing a more complete understanding of the elastic limits of anisotropic and asymmetric materials, we can better describe both the deformation during manufacturing processes such as forging, forming, or rolling and the final strength of as manufactured (conventionally or AM) components. By developing sensor systems to monitor AM processes such as DED, we can begin to better inform the creation of predictive models, identify critical events related to part performance, improve feedback controls for more reliability and repeatability, and ultimately qualify processes and certify components.