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Karatzas Kostas

Titles

Editorial Board member and Conference Chair

Τομέας: Energy 

Βαθμίδα: Professor 

Ειδικότητα: Environmental Informatics 

Τηλέφωνο: +302310994176 

Email: kkara@auth.gr 

Website: https://new-meng.web.auth.gr/en/node/483/edit/en 

Γραφείο: Building E14, Ground Floor 

Ώρες Συνεργασίας: Tuesday & Wednesday 12:30-14:00 (it is advisable to email me in advance). Alternative days and hours also available on the basis of email communication 

tmm_building

Ερευνητικά Ενδιαφέροντα: 

Research fields:

Scientific activities

Graduate courses taught:

  • Informatics
  • Environmental Informatics
  • Air Pollution

 

MSc courses taught:

Summer Schools

Current and future airt pollution management: perspectives of new sensor technologies (September 2019)

 

Επιλεγμένες Δημοσιεύσεις: 

In year descenting order

  1. Bagkis E., Kassandros Th., Karatzas K., (2022). Learning calibration functions on the fly: Hybrid batch-online stacking ensembles for the calibration of low-cost air quality sensor networks in the presence of concept drifts, Atmosphere, 13(3), 416. https://doi.org/10.3390/atmos13030416
  2. Kontos Y.N., Kassandros T., Perifanos K., Karampasis M., Katsifarakis K.L., Karatzas K. (2022), Machine Learning for Groundwater Pollution Source Identification and Monitoring Network Optimization, Neural Computing and Applications, https://doi.org/10.1007/s00521-022-07507-8
  3. Viana, M.; Karatzas, K.; Arvanitis, T.; Reche, C.; Escribano, M.; Ibarrola-Ulzurrun, E.; Adami, P.E.; Garrandes, F.; Bermon, S (2022), Air Quality Sensors Systems as Tools to Support Guidance in Athletics Stadia for Elite and Recreational Athletes. J. Environ. Res. Public Health 2022, 19(6), 3561; https://doi.org/10.3390/ijerph19063561
  4. Bagkis Ε., Kassandros T., Karteris Μ., Karteris Α., Karatzas Κ (2021), Analyzing and Improving the Performance of a Particulate Matter Low Cost Air Quality Monitoring Device. Atmosphere 12(2), 251. https://doi.org/10.3390/atmos12020251
  5. Furxhi I., Murphy F., Mullins M., Arvanitis A., Poland C. (2020), Practices and Trends of Machine Learning Application in Nanotoxicology, Nanomaterials 10(1):116; doi:10.3390/nano10010116
  6. Vohland K., Sauermann H., Antoniou V., Balazs B., Göbel C., Karatzas K., Mooney P., Perelló J., Ponti M., Samson R. and Winter S. (2020). Citizen Science and Sustainability Transitions. Research Policy 49(5), https://doi.org/10.1016/j.respol.2020.103978
  7. Borrego C., Costa A.M., Ginja J., Amorim M., Karatzas K., Sioumis Th., Katsifarakis N., Konstantinidis K., De Vito S., Esposito E., Smith P., André N., Gérard P., Francis L.A.,. Castell N., Viana M., Minguillón M.C., Reimringen W., Otjes R.P., v.Sicard O., Pohle R., Elen B., Suriano D., Pfister V., Prato M., Dipinto S., Penza M. (2018), Assessment of air quality microsensors versus reference methods: The EuNetAir joint exercise– part II, Atmospheric Environment 193, pp. 127-142, https://doi.org/10.1016/j.atmosenv.2018.08.028
  8. Karatzas K., Papamanolis L., Katsifarakis N., Riga M.  B. Werchan, M. Werchan, U. Berger, and K.C. Bergmann (2018), Google Trends reflect allergic rhinitis symptoms related to birch and grass pollen seasons, Aerobiologia 34(4), pp. 437-444, https://doi.org/10.1007/s10453-018-9536-4
  9. Karatzas K. and Katsifarakis N. (2018), Modelling of Household Electricity Consumption with the Aid of Computational Intelligence Methods.  Advances in Building Energy Research 12(1), pp. 84-96, https://doi.org/10.1080/17512549.2017.1314831
  10. Katsifarakis N., Riga M., Voukantsis D. and Karatzas K. (2016), Computational Intelligence methods for rolling bearing fault detection, Journal of the Brazilian Society of Mechanical Sciences and Engineering 38 (6), pp. 1565-1574. doi:10.1007/s40430-015-0458-6
 

Υποψήφιοι Διδάκτορες: 

  • Theodosios Kassandros (Dipl. Phys., MSc. Comp. Phys): Analysis and modelling of environmental sensors
  • Evangelos Bagkis (Dipl. Phys., MSc. Comp. Phys): Computational improvement of low-cost sensors in real time
  • Thomas Tasioulis (MEng in Civil Engineering, MSc Env. Prot. & Sust. Dev., MSc in Data Science): Development of a computational framework for the analysis and explainable modelling of environmental – air quality data

PhDs:

 

 

 

Βιογραφικό Σημείωμα: Συνημμένο Αρχείο 

Titles

Editorial Board member and Conference Chair

Field: Energy 

Rank: Professor 

Expertise: Environmental Informatics 

Telephone: +302310994176 

Email: kkara@auth.gr 

Website: https://new-meng.web.auth.gr/en/node/483/edit/en 

Office: Building E14, Ground Floor 

Student Reception: Tuesday & Wednesday 12:30-14:00 (it is advisable to email me in advance). Alternative days and hours also available on the basis of email communication 

tmm_building

Research fields: 

Research fields:

Scientific activities

Graduate courses taught:

  • Informatics
  • Environmental Informatics
  • Air Pollution

 

MSc courses taught:

Summer Schools

Current and future airt pollution management: perspectives of new sensor technologies (September 2019)

 

Papers: 

In year descenting order

  1. Bagkis E., Kassandros Th., Karatzas K., (2022). Learning calibration functions on the fly: Hybrid batch-online stacking ensembles for the calibration of low-cost air quality sensor networks in the presence of concept drifts, Atmosphere, 13(3), 416. https://doi.org/10.3390/atmos13030416
  2. Kontos Y.N., Kassandros T., Perifanos K., Karampasis M., Katsifarakis K.L., Karatzas K. (2022), Machine Learning for Groundwater Pollution Source Identification and Monitoring Network Optimization, Neural Computing and Applications, https://doi.org/10.1007/s00521-022-07507-8
  3. Viana, M.; Karatzas, K.; Arvanitis, T.; Reche, C.; Escribano, M.; Ibarrola-Ulzurrun, E.; Adami, P.E.; Garrandes, F.; Bermon, S (2022), Air Quality Sensors Systems as Tools to Support Guidance in Athletics Stadia for Elite and Recreational Athletes. J. Environ. Res. Public Health 2022, 19(6), 3561; https://doi.org/10.3390/ijerph19063561
  4. Bagkis Ε., Kassandros T., Karteris Μ., Karteris Α., Karatzas Κ (2021), Analyzing and Improving the Performance of a Particulate Matter Low Cost Air Quality Monitoring Device. Atmosphere 12(2), 251. https://doi.org/10.3390/atmos12020251
  5. Furxhi I., Murphy F., Mullins M., Arvanitis A., Poland C. (2020), Practices and Trends of Machine Learning Application in Nanotoxicology, Nanomaterials 10(1):116; doi:10.3390/nano10010116
  6. Vohland K., Sauermann H., Antoniou V., Balazs B., Göbel C., Karatzas K., Mooney P., Perelló J., Ponti M., Samson R. and Winter S. (2020). Citizen Science and Sustainability Transitions. Research Policy 49(5), https://doi.org/10.1016/j.respol.2020.103978
  7. Borrego C., Costa A.M., Ginja J., Amorim M., Karatzas K., Sioumis Th., Katsifarakis N., Konstantinidis K., De Vito S., Esposito E., Smith P., André N., Gérard P., Francis L.A.,. Castell N., Viana M., Minguillón M.C., Reimringen W., Otjes R.P., v.Sicard O., Pohle R., Elen B., Suriano D., Pfister V., Prato M., Dipinto S., Penza M. (2018), Assessment of air quality microsensors versus reference methods: The EuNetAir joint exercise– part II, Atmospheric Environment 193, pp. 127-142, https://doi.org/10.1016/j.atmosenv.2018.08.028
  8. Karatzas K., Papamanolis L., Katsifarakis N., Riga M.  B. Werchan, M. Werchan, U. Berger, and K.C. Bergmann (2018), Google Trends reflect allergic rhinitis symptoms related to birch and grass pollen seasons, Aerobiologia 34(4), pp. 437-444, https://doi.org/10.1007/s10453-018-9536-4
  9. Karatzas K. and Katsifarakis N. (2018), Modelling of Household Electricity Consumption with the Aid of Computational Intelligence Methods.  Advances in Building Energy Research 12(1), pp. 84-96, https://doi.org/10.1080/17512549.2017.1314831
  10. Katsifarakis N., Riga M., Voukantsis D. and Karatzas K. (2016), Computational Intelligence methods for rolling bearing fault detection, Journal of the Brazilian Society of Mechanical Sciences and Engineering 38 (6), pp. 1565-1574. doi:10.1007/s40430-015-0458-6
 

PhD Candidates: 

  • Theodosios Kassandros (Dipl. Phys., MSc. Comp. Phys): Analysis and modelling of environmental sensors
  • Evangelos Bagkis (Dipl. Phys., MSc. Comp. Phys): Computational improvement of low-cost sensors in real time
  • Thomas Tasioulis (MEng in Civil Engineering, MSc Env. Prot. & Sust. Dev., MSc in Data Science): Development of a computational framework for the analysis and explainable modelling of environmental – air quality data

PhDs:

 

 

 

CV: Attached File