Dr. Levente K-Pápai
I have a strong interest in solving biomedical problems, developing novel medical technology and data products by utilising big data and ML techniques.
Gathered widespread interdisciplinary experience, counting 5+ years in academic research, 2.5+ years in machine learning and data wrangling, and 1.5 years in clinical medicine.
Being a passionate lifelong learner allows me to be a competent expert with a wide range of skills.
PhD in Medical Sciences
Research topic: Application of 3D modelling and 3D printing in surgical planning. CFD simulations and AI algorithms for surgical vascular anastomosis evaluation
MSc in Data Science & Artificial Intelligence
Diploma grade: distinction
Modules in statistics, machine learning, neural networks, natural language processing, big data analysis, blockchain programming, social networks & graph analysis, and artificial intelligence
Medical Data Scientist
- Implemented the ETL dataflow and automatization of Computational Fluid Dynamics (CFD) simulation results
- Improved the vascular suture ranking score model, initial MAE reduced by 52%
- Built and refining further algorithms for predicting vascular deterioration, surgical complication and manual error
- Developed and maintaining a data acquisition/annotating platform for 3D objects
- Dockerized and deploying in cloud platforms
- Doctoral research project in the topic of AI in surgical education
- Anesthesia experience in gynecologic, obstetric, oro-maxillofacial, ophtalmic, ENT and urologic surgeries.
- Education experience in high-fidelity simulation skill practices, teaching the BLS/ALS protocols, ABCDE patient assessment and SBAR communication for medical students.
- Research experience in inflammatoric immunophysiology and animal models at the Department of Physiology.
- In vitro research toolset of ELISA, cell-adhesion assays, platelet-activation experiments, Western blot, flow cytometry, cell preparation and cultures.
- Experience with in vivo models of autoimmune diseases, transgenic mice, the Cre-lox system, and haemopoetic chimeras.
Biomedical Engineering for Sustainable DevelopmentGruppo Nazionale di Bioingegneria
Deep Learning Specializationdeeplearning.ai
Data Science SpecializationJohns Hopkins University
Open Innovation Management in HealthcareHealthIL
Honors & Awards
Telekom FutuRE:build Hackathonmentoring and jury member
European Health Forum Gastein Hackathonteam member, winner of the jury and audience prizes
Semmelweis Annual Students’ Conference1st place
The 24th Students’ Scientific Conference of Târgu Muresspecial award
XXXIII. Hungarian National Students’ Scientific Conferencespeaker
- 3D data
- Fluid dynamics
- Computational geometry
- Regression models
- Hypothesis testing
- Data product development
- Computational biology
Main tech skills
- R Studio
- MS Azure
- R Shiny