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.
Research
5+ years
Data
2.5+ years
Clinical medicine
1.5 years
Education
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
Experience
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
Medical Doctor
- 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.
Undergraduate Researcher
- 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.
Courses
Biomedical Engineering for Sustainable Development
Gruppo Nazionale di BioingegneriaDeep Learning Specialization
deeplearning.aiData Science Specialization
Johns Hopkins UniversityOpen Innovation Management in Healthcare
HealthILHonors & Awards
Telekom FutuRE:build Hackathon
mentoring and jury memberEuropean Health Forum Gastein Hackathon
team member, winner of the jury and audience prizesSemmelweis Annual Students’ Conference
1st placeThe 24th Students’ Scientific Conference of Târgu Mures
special awardXXXIII. Hungarian National Students’ Scientific Conference
speakerSkills
Competencies
- 3D data
- Fluid dynamics
- Computational geometry
- Regression models
- Hypothesis testing
- Data product development
- ETL
- Research
- R&D
- Biomedicine
- Computational biology
Main tech skills
- Python
- R Studio
- SQL
- PHP
- Docker
- Git/GitHub
- MS Azure
- Tableau
- Dataiku
- Unix
Python libraries
- sklearn
- xgboost
- pytorch
- keras
- pandas
- scipy
- statsmodels
- slqalchemy
- nltk
- beautifulsoup
- scrapy
- gensim
- pgmpy
- shap
- vmtk
- vtk
Web
- Symfony6
- HTML/JS/CSS
- Flask
- R Shiny
- npm/yarn
- bootstrap
- webpack
Languages
- English
- Swedish
- Hungarian
- (German)
Contact
ORCID: 0000-0002-2586-8960
ResearchGate: Levente-Kiss-Papai
Scopus: 57201271260
MTMT: 10079459
ResearcherID: GPP-1896-2022