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 4+ years in academic research, 1.5+ 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

4+ years

Data

1.5+ years

Clinical medicine

1.5 years

Experience

Medical Data Scientist

Youranastomosis
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  • Implementing the ETL dataflow and automatization of Computational Fluid Dynamics (CFD) simulation results
  • Improving the vascular suture ranking score model, initial MAE reduced by 52%
  • Building and refining further algorithms for predicting vascular deterioration, surgical complication and manual error
  • Developing and maintaining a data acquisition/annotating platform for 3D objects
  • Dockerizing 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

Semmelweis University
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  • 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.

Education

PhD in Medical Sciences

University of Pécs
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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

University of London
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Modules in statistics, machine learning, neural networks, natural language processing, big data analysis, blockchain programming, social networks & graph analysis, and artificial intelligence

Doctor of Medicine

Courses

(currently)
Deep Learning Specialization
deeplearning.ai
2020
Data Science Specialization
Johns Hopkins University
2020
Open Innovation Management in Healthcare
HealthIL
2019
Leveraging E-health Workforce Summer School
EIT & IESE Business School & Semmelweis University

Awards

2020
Telekom FutuRE:build Hackathon
mentoring and jury member
2020
European Health Forum Gastein Hackathon
team member, winner of the jury and audience prizes
2017
Semmelweis Annual Students’ Conference
1st place
2017
The 24th Students’ Scientific Conference of Târgu Mures
special award
2017
XXXIII. Hungarian National Students’ Scientific Conference
speaker

Skills

Programming skills
  • R Studio
  • Python
  • SQL
  • PHP
Data Ops
  • Dataiku
  • MLFlow
  • SHAP
  • Docker
  • Git/GitHub
  • Hadoop
  • Ms Azure
  • Ms SSIS
DS Libraries
  • numpy
  • pandas
  • sklearn
  • xgboost
  • tensorflow
  • keras
  • scipy
  • statsmodels
  • slqalchemy
  • nltk
  • beautifulsoup
  • scrapy
  • gensim
  • pgmpy
  • caret
  • data.table
Data Vis.
  • Tableau
  • matplotlib
  • seaborn
  • plotly
  • ggplot2
Web
  • Symfony5
  • HTML/JS/CSS
  • Flask
  • Django
  • R Shiny
  • npm/yarn
  • bootstrap
Languages
  • English
  • Swedish
  • Hungarian
  • (German)

Contact

ResearchGate: Levente-Kiss-Papai

Scopus: 57201271260

MTMT: 10079459

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