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

Jan 2021 - Present

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

Semmelweis University, Department of Anesthesiology and Intensitve Care

Sep 2019 - Jan 2021

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

Sep 2015 - Aug 2018

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

2021 - Present

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

2021 - Present

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

Semmelweis University

2013 - 2019

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 Hackathonmentoring and jury member
2020
European Health Forum Gastein Hackathonteam member, winner of the jury and audience prizes
2017
Semmelweis Annual Students’ Conference1st place
2017
The 24th Students’ Scientific Conference of Târgu Muresspecial award
2017
XXXIII. Hungarian National Students’ Scientific Conferencespeaker