Konstantinos Bromis

Experience

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  Department of IT research (Greek army military service)

  Jan 2009 - Jan 2010

  IT support and network maintenance

  • Responsible for management, operation and maintenance of Greek army’s information systems.• Worked on a collaborative project to develop an electronic prescription system (e-prescription) for the Greek Armed Forces staff.

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  Advantis Medical Imaging

  Jan 2016 - Jan 2016

  Research And Development Specialist

  • Developed the fMRI pipeline (pre-processing & statistical modelling) which is a core module of a web-based platform (BRAINANCE MD) for advanced MRI brain analysis (Python).• Applied good coding practice methods (code testing, code review, version control. Gained experience with pytest and git.

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  University of Sussex

  Jan 2018 - Jan 2019

  Postdoctoral Research Associate

  During my postdoctoral tenure at Sussex University, I spearheaded a groundbreaking fMRI study funded by ERC Research and ESRC which was published in the Journal of Cognitive Neuroscience. The research involved a novel experimental design with 30 participants, aimed at understanding how the brain encodes and distinguishes elements of episodic memories through unique and overlapping events.Project Overview:• Experiment Design: Conducted a dual-session brain imaging study, utilizing a format mimicking a television chat show to create distinct yet interrelated memory events, focusing on the neural representation of repeated versus unique event elements during memory recall.• Methodology: Employed advanced Multi-Voxel Pattern Analysis (MVPA) alongside conventional fMRI analysis (General Linear Model - GLM), providing a comprehensive approach to decode brain activity patterns associated with memory.• Tools & Techniques: Leveraged MATLAB for data analysis, incorporating standard preprocessing protocols to ensure data integrity and reliability of results.• Key Findings:Our results highlighted a significant neural preference for elements commonly encountered across different memories, predominantly activating the posterior midline network. This challenges traditional views on memory processing and has profound implications for theoretical models of episodic memory retrieval.• Impact:This research not only advances our understanding of memory representation in the brain but also enhances the methodologies used in cognitive neuroscience, offering new perspectives on how episodic memories are processed and recalled. Λιγότερα

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  Major Greek Bank

  Jan 2019 - Jan 2019

  Data Science Consultant

  • Built an artificial neural networks (ANN) model and a logistic regression model (Python, Keras, scikit-learn) that predict credit default.• Data cleansing and feature engineering.• Feature selection using Backward Elimination, Information Value and Correlation Analysis.• Extensive comparison using a variety of evaluation metrics (MSE, Adjusted R2, Gini).• Results showed that the ANN model provided better accuracy and discriminatory power. However, the margin was not large enough compared to the logistic regression model which is commonly used in credit risk models. Λιγότερα

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  National Technical University of Athens

  Jan 2020 - now

  Postdoctoral Senior Researcher

  As a Postdoctoral Researcher specializing in healthcare technology, I have contributed to multiple EU-funded projects (More info on Projects section), developing innovative solutions that improve healthcare delivery.Key Contributions:TeleRehaB Project (Jun 2023 - Present):• Developed cloud infrastructure and backend systems using C#, enhancing platform integration and secure data management.• Implemented FHIR server APIs, boosting data interoperability within the healthcare sector.RETENTION Project (Oct 2022 - Sep 2023):• Led the design of data transfer mechanisms, enhancing data security and efficiency across repositories.• Developed RESTful APIs, ensuring HL7 FHIR compliance and supporting secure CRUD operations.SMART BEAR Project (Mar 2021 - Apr 2023):• Created a DSS with integrated alerts and gamification, enhancing patient care and engagement.• Engineered APIs for robust data handling across diverse databases, ensuring compliance and operational efficiency.UNITI Project (Concluded):• Led data science initiatives to develop a DSS for personalized tinnitus treatment plans, successfully concluding with a model that enhances treatment precision.• Presented the model's development and impact at EMBC 2022 and TRI 2023 conferences, showcasing the project's success in integrating personalized medicine into tinnitus treatment.IMPILO Project (Concluded):• Engineered backend solutions using Django for a blockchain-based healthcare network, facilitating secure medical interactions.Technical Skills:RESTful APIs, C#, data science, ML algorithms, Python, Django, HL7 FHIR standards, data encryption, GDPR compliance.Impact:My work has significantly enhanced platform functionality, ensured secure data handling, and improved patient outcomes through technology-driven solutions. Committed to advancing personalized medicine, I continue to push the boundaries of technology in healthcare. Λιγότερα