Design of Next-Generation Gas and Biological Sensors: Impact of Materials, Transducers, and Contemporary Multivariate Analytics

#gases #interference #analytics #data-analytics #diagnostics #machine-learning #Sensors;
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Contemporary monitoring requirements of gases and liquids for demanding applications such as environmental surveillance, medical diagnostics, food and industrial safety, biopharmaceutical process control, homeland security, and others push the limits of existing detection concepts where we may reach their fundamental performance limits.  These and other modern monitoring scenarios demand sensing with higher accuracy, enhanced stability, improved sensitivity, and lower power consumption; often all in unobtrusive formats and at low cost. We are developing new generation of sensors that bridge the gap between existing and contemporary required capabilities.  Our sensors utilize radio-frequency and optical detection principles and achieve required performance via system analytics. The system analytics is our methodology to deliver high performance sensing via new sensor design rules that include transducer with several uncorrelated outputs, sensed environment (e.g. sensing film or sensing volume) with diverse intrinsic properties detected by the transducer, and multivariate signal processing algorithms (a.k.a. machine learning). We will illustrate the capabilities of these multivariable (multi-parameter) sensors to quantify individual components in mixtures, reject interferences, and correct for environmental instabilities.  Our multivariable sensors when coupled with edge data analytics boost data analytics accuracy and reduce data analytics demands for computing and electrical power. Examples of scenarios where such developed multivariable sensors are important include wearable and remotely deployed sensors, autonomous robotics, and home health.  In these and many other scenarios, high-performance advantages of traditional mature instruments are cancelled by application-specific requirements that demand unobtrusive form factors, low or no power consumption, no maintenance, and continuous operation.



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  • Macquarie University
  • North Ryde
  • Sydney, New South Wales
  • Australia 2109
  • Building: 9WW
  • Room Number: G65 The Forum

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  • Starts 10 June 2026 02:00 PM UTC
  • Ends 30 June 2026 02:00 PM UTC
  • No Admission Charge


  Speakers

Radislav of GE Vernova Advanced Research Center, Niskayuna, NY, USA

Topic:

Design of Next-Generation Gas and Biological Sensors: Impact of Materials, Transducers, and Contemporary Multivariate An

Contemporary monitoring requirements of gases and liquids for demanding applications such as environmental surveillance, medical diagnostics, food and industrial safety, biopharmaceutical process control, homeland security, and others push the limits of existing detection concepts where we may reach their fundamental performance limits.  These and other modern monitoring scenarios demand sensing with higher accuracy, enhanced stability, improved sensitivity, and lower power consumption; often all in unobtrusive formats and at low cost. We are developing new generation of sensors that bridge the gap between existing and contemporary required capabilities.  Our sensors utilize radio-frequency and optical detection principles and achieve required performance via system analytics. The system analytics is our methodology to deliver high performance sensing via new sensor design rules that include transducer with several uncorrelated outputs, sensed environment (e.g. sensing film or sensing volume) with diverse intrinsic properties detected by the transducer, and multivariate signal processing algorithms (a.k.a. machine learning). We will illustrate the capabilities of these multivariable (multi-parameter) sensors to quantify individual components in mixtures, reject interferences, and correct for environmental instabilities.  Our multivariable sensors when coupled with edge data analytics boost data analytics accuracy and reduce data analytics demands for computing and electrical power. Examples of scenarios where such developed multivariable sensors are important include wearable and remotely deployed sensors, autonomous robotics, and home health.  In these and many other scenarios, high-performance advantages of traditional mature instruments are cancelled by application-specific requirements that demand unobtrusive form factors, low or no power consumption, no maintenance, and continuous operation.

 

Biography:

Radislav Potyrailo is a Senior Principal Scientist at GE Vernova Advanced Research, leading programs on design of sensor systems and bringing innovations from feasibility to commercialization.  His research interests are in design of physical transducers and materials with multi-response mechanisms, multivariate edge-data analytics, and system engineering. Radislav served as a lead on numerous R&D programs transitioned to GE businesses or GE partners for commercialization. Radislav has been a Principal Investigator on US Government programs funded by AFRL, ARPA-E, DARPA, DHS, DOE, DTRA, JPEO, NIH, NIOSH, TSWG, and other agencies.  Examples of his systems as recognized by international industrial awards include sensors for GE Water and for GE Oil & Gas.  He has 165+ granted US Patents and numerous publications (Google Scholar h-index 55).  He serves as an editor of the Springer-Nature book series “Integrated Analytical Systems”.  Radislav is the Chair of the Device Working Group of the MEMS and Sensors Industry Group and the North America Chair of International Society for Olfaction and Chemical Sensing. He is SPIE Fellow and IEEE Fellow, covering the whole electromagnetic spectrum of his sensors. Radislav is 2024-2026 Distinguished Lecturer of the IEEE Sensors Council.

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Address:New York, United States