Curriculum vitae

Forschungsschwerpunkte
  • Thema Doktorarbeit: "Automatisierte Verarbeitung von Biomedizinischen Bildern in Infektionsforschung"
Wissenschaftlicher Werdegang
Since 2021 Doktorand am Hans-Knöll-Institut
2018 - 2021 M.Sc. in Biomedical Engineering an der FH Aachen, Aachen, Deutschland
2017 -2018 Product Specialist am Karl Storz Endoscopy India Private Limited, Indien
2015 - 2017 Senior Application Engineer am Healthware Private Limited, Indien
2014 -2015 Service Engineer am South India Surgical Company Limited, Indien
2010 - 2014 B.Tech in Biomedical Engineering  am JIS College of Engineering, Indien

Publikationen

Graf M*, Sarkar A*, Svensson CM, Munser AS, Schröder S, Hengoju S, Rosenbaum MA#, Figge MT# (2025) Rapid detection of microbial antibiotic susceptibility via deep learning supported analysis of angle-resolved scattered-light images of picoliter droplet cultivations. Sens Actuators B Chem 424, 136866.
Abou-Kandil A*, Tröger-Görler S*, Pschibul A*, Krüger T, Rosin M, Schmidt F, Akbarimoghaddam P, Sarkar A, Cseresnyés Z, Shadkchan Y, Heinekamp T, Gräler MH, Barber AE, Walther G, Figge MT, Brakhage AA, Osherov N#, Kniemeyer O# (2024) The proteomic response of Aspergillus fumigatus to Amphotericin B (AmB) reveals the involvement of the RTA-like protein RtaA in AmB resistance. microLife 6, uqae024.
Sarkar A, Praetorius JP, Figge MT# (2024) Deep learning-based characterization of neutrophil activation phenotypes in ex vivo human Candida blood infections. Comput Struct Biotechnol J 23, 1260-1273.
Belyaev I*, Marolda A*, Praetorius JP, Sarkar A, Medyukhina A, Hünniger K, Kurzai O, Figge MT (2022) Automated characterisation of neutrophil activation phenotypes in ex vivo human Candida blood infections. Comput Struct Biotechnol J 20, 2297-2308.
Sarkar A (2022) Explainable aI and its applications in healthcare. In: Mehta M, Palade V, Chatterjee I (eds.) Explainable AI: Foundations, Methodologies and Applications. 232, pp. 111-133. Springer. ISBN: 978-303112807-3. (Review)
Sarkar A, Vandenhirtz J, Nagy J, Bacsa D, Riley M (2021) Identification of images of COVID-19 from chest X-rays using deep learning: Comparing COGNEX vision Pro deep learning 1.0™ software with open source convolutional neural networks. SN Comput Sci 2(3), 130.