Early Stage Researchers
Indhika Fauzhan Warsito is a PhD student at the Biomedical Engineering group of the Technische Universität Ilmenau under supervision of Prof. Jens Haueisen. He was born in Jakarta (Indonesia) and received his B. Sc. degree (2016) in Mechatronic Engineering from Türk Hava Kurumu Üniversitesi (Ankara, Turkey). He received a double Master degree M. Sc./ M. Phil. in Biomedical Engineering from Technische Universität Ilmenau (Ilmenau, Germany) and Universiti Teknologi Malaysia (Johor, Malaysia) in 2019. His research interests include neonatal bioelectric measurement, biosignal analysis and modelling/simulation for 3D CAD. His PhD project deals with the development of novel, dry, flexible electrodes for neonatal bioelectric measurements.
Milana Komosar is currently a doctoral student at the Biomedical Engineering group of the Technische Universität Ilmenau under supervision of Prof. Jens Haueisen. She was born in Prijedor, Bosnia and Herzegovina. She received B.Sc. (2018) and M.Sc. (2019) degrees in Electric and Computer Engineering of Faculty of Technical Sciences, University of Novi Sad (Novi Sad, Serbia). During her Master thesis project, she was a researcher at TU Ilmenau for 8 months at the Department of Lightning and overvoltage protection. Her currently field of interest are neuroscience, processing and analysis of biosignals. She is employed as ESR2 in INFANS project with the topic Novel Spatial Harmonic Decomposition for real-time dimension reduction of EEG signals.
Tim Kalla is a PhD student at the Università degli Studi G. d'Annunzio Chieti-Pescara (Italy) under the supervision of Prof. Silvia Comani. He is recruited as ESR3 in the INFANS project and his PhD project is entitled “Novel method for artefact correction in neonatal EEG signals”. Tim was born in Germany and obtained a Bachelor and Master of Science in Biomedical Engineering at Technische Universität Ilmenau, specializing in Electromedical Engineering. His research interests are generally in the field of software development, especially in the processing and analysis of biological signals.
Khadijeh Raeisi is a PhD candidate at the Neuroscience and Imaging group of the Università degli Studi G. d'Annunzio Chieti-Pescara under the supervision of Prof. Filippo Zappasodi. She received her B.Sc. and M.Sc. degree in biomedical engineering from Isfahan University (Isfahan, Iran) and Khajeh Nasir Toosi University of Technology (Tehran, Iran) with specialization on signal processing and machine learning. She is employed as ESR4 as a part of INFANS project to estimate the brain maturity using Neonatal functional connectivity pattern on short-term EEG.
Mohammad Khazaei received the B.Sc. and M.Sc. degree in biomedical engineering from Sahand University of Technology (Tabriz, Iran) and Iran University of Science and Technology (Tehran, Iran) with specialization on adaptive and robust control approaches applied to cats’ hindlimb movement control. His research interests include biological signal processing, bio-instruments designing and biological system modeling. Currently, he is a Ph.D. student at University “G. D'Annunzio” of Chieti-Pescara, Italy. His role in the INFANS project (ESR5) is to define the best topological measures to characterize the brain networks properties in stable neonates/infants for differential diagnosis purposes and develop a toolbox for the analysis of short-term EEG data for estimation of brain efficiency.
Mohammed-Reda Mejbar is currently a doctoral student at eemagine Medical Imaging Solutions GmbH in Germany and enrolled in the PhD program at the Technische Universität Ilmenau under supervision of Prof. Jens Haueisen. He was born in Fes, Morocco where he received B.Sc. (2011) in Scientific computing and applications. He received an Erasmus Joint Master in Clinical linguistics (2019) from the University of Groningen (Netherlands), University of Eastern Finland (Finland), and University of Potsdam (Germany). His current research interests include cognitive and clinical neuroscience, brain-computer interface, and biological sensors and signal analysis. Reda is recruited as ESR6 within the INFANS project focusing on developing a novel adaptive cap and sensors for neonates and infants.
Vignesh Nandagopal is from Chennai, India. He received his Master's in Biomedical Engineering from the Chalmers University of Technology in Gothenburg, Sweden. He pursued his Bachelor's in Electrical Engineering from Anna University in India. His research interests involve neuroscience, biomedical signal processing, brain imaging technologies, machine learning and integrating neuroscience with software advancements.
Amirreza Asayesh is a PhD candidate in Neuroscience at BABA Center of the University of Helsinki under the supervision of Prof. Sampsa Vanhatalo and Prof. Jens Haueisen. He received his B.Sc. and M.Sc. degrees in biomedical engineering-bioelectric, from Islamic Azad University of Tabriz (Iran) and The University of Tabriz (Iran), respectively. His research interests include neuroscience, brain imaging methods, EEG signal recording and processing, bio instrumentation design, and wearable technologies. He is recruited as ESR8 within the INFANS project for Clinical multicentre validation by focusing on the novel dry electrode, cap, and short-term EEG monitoring.
Saeed Montazeri Moghadam (M.Sc., Ph.D. candidate) is currently a doctoral student in Neuroscience at BABA Center (University of Helsinki) under supervision of Prof. Sampsa Vanhatalo. He received his B.Sc. and M.Sc. degrees in biomedical engineering, bioelectric, from Islamic Azad University of Mashhad (Iran) and Amirkabir University of Technology (Tehran Polytechnics, Iran), respectively. His research interests include neuroscience, signal and image analysis using machine learning tools mainly deep neural networks. He is recruited as ESR9 within the INFANS project, focusing on design of novel GUI components, design of measures for assessment of brain maturity and to develop iterative validation tests for short-term EEG monitoring.
Tim Hermans is a doctoral student in Electrical Engineering at KU Leuven (Belgium) as part of the biomedical data processing research group BioMed, under supervision of Prof. Sabine Van Huffel. He was born in Maastricht (The Netherlands) and received his B. Sc. degree in Biomedical Engineering (2016) and M. Sc. degree in Medical Engineering (2019) from the University of Technology in Eindhoven (The Netherlands). His main research interests include medical signal analysis and machine learning. The aim of his PhD project is to develop software for automated EEG scoring, cerebral autoregulation assessment and quantification of linked dynamics between EEG activity and cerebral oxygenation for use in computer-aided prediction of neurological outcome in neonates in intensive care units.
Ana Borovac is a doctoral student in Computer Science at University of Iceland. She was born in Kranj (Slovenia) and received her Bachelor's degree in Mathematics (2017) and Master's degree in Computer Science and Mathematics (2019) from the Faculty of mathematics and physics, University of Ljubljana, Slovenia. Her main research interests include biomedical signal processing, machine learning and data mining. As part of INFANS project she will design and develop a monitoring system that incorporates technologies and algorithms.
Elizaveta Genke is employed as an early stage researcher (ESR12) at the company Artinis Medical Systems. She was born in Tashtyp (Russia) and obtained her B.Sc. degree in Biomedical Engineering from Tomsk Polytechnic University (Tomsk, Russia) in 2017. She received a joint master degree in Medical Image and Applications from Université de Bourgogne (Dijon, France), Università degli Studi di Cassino e del Lazio Meridionale (Cassino, Italy) and Universitat de Girona (Girona, Spain) in 2019. Her master thesis internship took place in Donders Centre for Cognition (Nijmegen, the Netherlands). Her current interests include machine learning, image processing, data science, cognitive neuroscience. In the INFANS project she is going to be working on optimal optode placement for high density diffuse optical tomography and machine learning-based NIRS signal processing algorithms.
Naser Hakimi received his B.Sc. and M.Sc. degrees in Electrical and Biomedical Engineering from Shahid Beheshti University (Tehran, Iran) in 2015 and University of Tehran (Tehran, Iran) in 2018. His main research during his Master was the extraction of heart rate signal from functional near-infared spectroscopy (NIRS) and investigating its feasibility in stress assessment. Naser is employed as an early stage researcher (ESR13) at Artinis Medical Systems. He is currently working on NIRS signal quality measurement and physiological information estimation from NIRS signal.
Xiaowan Wang is a doctoral student at the Wihelmina Children’s Hospital (WKZ) of the University Medical Center Utrecht under supervision of Dr. Jeroen Dudink. She was born in China and received her Bachelor’s degree in Engineering from Communication University of China and Master’s degree in Cognitive Neuroscience from Southwest University of China. Her research interests include neonatology, statistical learning, clinical and network neuroscience. She is employed as ESR14 within the INFANS project, with a research focus on long-term EEG-NIRS monitoring and sleep detection algorithm development for preterm born babies.
Emad Arasteh is currently a PhD student at the Utrecht University working on signal processing of NIRS and aEEG data for pre-term infants. His main field of research is statistical analysis and signal processing in cognitive neuroscience. He holds both the B. Sc. And M. Sc. degrees in Electrical Engineering from Iran. For his Master thesis (in University of Tehran), he has worked on a bio-electromagnetic project including design and implementation of a hyperthermia system for cancer treatments. Through this experience, he got enthusiastic about biomedical studies. After M. Sc. graduation, he worked on some biomedical projects like diagnosis of Parkinson’s disease from EEG data and coupling between brain neural oscillations and vital signs of neurodegenerative disease patients.