Nice to meet you!
I am a scientist–engineer with a dual foundation in chemical engineering and computer science, shaped by a long-standing drive to question assumptions and redesign how things work. My professional center of gravity lies in digital transformation for life sciences, where I combine data science, process systems thinking, and user-driven design to build solutions that are both technically robust and operationally meaningful. What differentiates me is a concept-builder mentality: I enjoy synthesizing insights across disciplines, exposing constraints early, and architecting systems that scale rather than merely optimizing what already exists. I am deeply analytical, yet equally reflective—constantly examining whether data-driven approaches truly generate insight or simply add noise, and how technology choices shape long-term capability rather than short-term output. Colleagues describe me as curious, creative, and intellectually rigorous. I thrive in environments that value depth of thought, cross-functional collaboration, and the courage to rethink established workflows. My energy comes from turning ambiguity into clarity, and transforming promising ideas into practical, well-structured solutions. Outside of work, I pursue travel, photography, writing, and sports—activities that mirror my inclination to explore, observe, and understand the world from multiple angles.
G. Tancev, “Reliable Air Quality Monitoring with Low-Cost Gas Sensor Systems in Smart Cities,” 2023. Dissertation.
G. Tancev and F. G. Toro, “Towards a Digital Twin for Air Quality Monitoring Networks in Smart Cities,” in ISC2 2022 - 8th IEEE International Smart Cities Conference, IEEE, 2022, pp. 1–4, ISBN: 9781665485616. DOI: 10.1109/ISC255366.2022.9921782.
G. Tancev, A. Ackermann, G. Schaller, and C. Pascale, “Efficient and Automated Generation of Orthogonal Atmospheres for the Characterization of Low-Cost Gas Sensor Systems in Air Quality Monitoring,” IEEE Transactions on Instrumentation and Measurement, vol. 71, 2022. DOI: 10.1109/TIM.2022.3198747.
G. Tancev and F. Grasso Toro, “Stochastic Online Calibration of Low-Cost Gas Sensor Networks with Mobile References,” IEEE Access, vol. 10, pp. 13901–13910, 2022. DOI: 10.1109/access.2022.3145945.
G. Tancev and F. Grasso Toro, “Variational Bayesian calibration of low-cost gas sensor systems in air quality monitoring,” Measurement: Sensors, vol. 19, p. 100365, 2022. DOI: 10.1016/j.measen.2021.100365.
G. Tancev and F. Grasso Toro, “Sequential Recalibration of Wireless Sensor Networks with (Stochastic) Gradient Descent and Mobile References,” vol. 18, 2021, p. 100115. DOI: 10.1016/j.measen.2021.100115.
V. Gotta, G. Tancev, O. Marsenic, J. E. Vogt, and M. Pfister, “Identifying key predictors of mortality in young patients on chronic haemodialysis - A machine learning approach,” Nephrology Dialysis Transplantation, vol. 36, no. 3, pp. 519–528, 2021. DOI: 10.1093/ndt/gfaa128.
S. Horender, G. Tancev, K. Auderset, and K. Vasilatou, “Traceable PM2.5 and PM10 Calibration of Low-Cost Sensors with Ambient-Like Aerosols Generated in the Laboratory,” Applied Sciences, vol. 11, p. 9014, 2021. DOI: 10.3390/app11199014.
G. Tancev, “Relevance of Drift Components and Unit-to-Unit Variability in the Predictive Maintenance of Low-Cost Electrochemical Sensor Systems in Air Quality Monitoring,” Sensors, vol. 21, no. 9, p. 3298, 2021. DOI: 10.3390/s21093298.
G. Tancev and C. Pascale, “The Relocation Problem of Field Calibrated Low-Cost Sensor Systems in Air Quality Monitoring: A Sampling Bias,” Sensors, vol. 20, no. 21, 2020. DOI: 10.3390/s20216198.
K. D. Singh, G. Tancev, F. Decrue, et al., “Standardization procedures for real-time breath analysis by secondary electrospray ionization high-resolution mass spectrometry,” Analytical and Bioanalytical Chemistry, vol. 411, no. 19, pp. 4883–4898, 2019. DOI: 10.1007/s00216-019-01764-8.