About TS-Analytics
TS-Analytics is led by Thomas Suppan, an electrical engineer and applied statistician with a background in statistical signal processing, measurement science, probabilistic modeling, and clinical research data analysis.
The work of TS-Analytics is centered on rigorous methodology, reproducible analysis, and uncertainty-aware interpretation of complex data — especially where signals, models, and domain knowledge need to be combined.
TS-Analytics is led by Thomas Suppan, an electrical engineer and applied statistician with a background in statistical signal processing, measurement science, probabilistic modeling, and clinical research data analysis.
The work of TS-Analytics is centered on rigorous methodology, reproducible analysis, and uncertainty-aware interpretation of complex data — especially where signals, models, and domain knowledge need to be combined.
TS-Analytics is led by DI Dr.techn. Thomas Suppan, an electrical engineer and applied statistician with a background in statistical signal processing, measurement science, probabilistic modeling, and clinical research data analysis.
The work of TS-Analytics is centered on rigorous methodology, reproducible analysis, and uncertainty-aware interpretation of complex data — especially where signals, models, and domain knowledge need to be combined.
Scientific and Engineering Background
My professional path began with vocational training as an industrial electrician, followed by a second-chance education pathway and subsequent Bachelor’s, Master’s, and Doctoral degrees in Electrical Engineering. During my doctoral research at the Institute of Electrical Measurement and Sensor Systems at Graz University of Technology, I worked on statistical signal processing, inverse problems, physical modeling of measurement systems, uncertainty analysis, and numerical optimization. My dissertation focused on electrical capacitance tomography for industrial flow measurement in pneumatic conveying systems and received the Award of Excellence 2024 from the Austrian Federal Ministry of Education, Science and Research.
Clinical Research and Applied Statistics
In parallel to my engineering research, I expanded my work toward medical statistics and clinical research data analysis through a research appointment at the Medical University of Graz. My contributions include Bayesian analysis, statistical modeling, study data analysis, diagnostic and performance evaluation, and publication-ready statistical outputs. I have been involved in interdisciplinary and international research projects, including multicenter clinical studies. To support this work in a clinical research environment, I completed Good Clinical Practice (GCP) training and certification.
Publications and Research Output
My peer-reviewed work spans engineering, measurement science, and clinical research, with methodological contributions in measurement science, statistical signal processing, inverse problems, Bayesian methods, and applied medical statistics.
A complete publication record is available via Google Scholar and ORCID.
Industry and Interdisciplinary Work
Beyond academia, I have worked in industry as a technical project lead in automotive measurement, gaining hands-on experience with real-world data, complex measurement chains, and industrial development processes. Across engineering, medicine, and industry, a central part of my work has been the translation between disciplines — connecting statistical methods, technical measurement problems, clinical research questions, and practical implementation.
Clear Methods, Transparent Results
Alongside my research activities, I have been involved in teaching and supervision at Graz University of Technology, including lectures in statistical signal processing, laboratory courses in electrical engineering and measurement technology, and the supervision of master’s theses. This experience has shaped the way TS-Analytics approaches analytical work: complex methods are structured clearly, results are communicated transparently, and workflows are documented so they can be understood, reviewed, and reproduced.
Why TS-Analytics?
TS-Analytics was founded to provide specialized analytical support for technical and scientific projects involving complex data, signals, models, and uncertainty. The focus lies on model-based signal processing, statistical analysis, probabilistic inference, and reproducible computational workflows — with the aim of producing results that are transparent, interpretable, and scientifically sound.
Interested in scientific exchange, collaboration, or future project discussions?
Free initial call · NDA possible · Remote collaboration across AT/DE/EU