About the Laboratory
Welcome to the AIC Lab. We create cutting-edge deep learning technologies for biomolecular medical data analysis to be used in life sciences and biomedical applications. We are an international, English-speaking, multidisciplinary group with a background in computer science, math, and molecular biology.
Join the English-speaking AIC Lab and gain hands on experience with high-performance computing technologies, statistical testing methods, and deep learning methods applied on interesting real-life applications. Research projects are available at any levels (BSC, MSc, PhD, Post-doc, summer practice, and summer internships).
Attila Kertes-Farkas received the best award for his presentation at IMLC 2023 conference
The head of AIC Laboratory, Attila Kertes-Farkas, was awarded for the best presentation at the ICMLC 2023 conference.
Congratulations to the Head of Laboratory on AI for Computational Biology Kertesz-Farkas Attila on receiving the well-deserved award
The head of the laboratory is presented for the award.
International seminar "Light scattering techniques – versatile tools to study nanoparticle dispersions"
An international seminar was held jointly with the University of Szeged.
Attila Kertesz-Farkas successfully defended Doctoral Thesis
On May 19th, 2022, Attila Kertesz-Farkas defended the doctoral thesis.
Attila Kertesz-Farkas had a talk on FCS's Colloquium meeting
AIC LAB Head had a talk at traditional colloquium.
Seminar "Neuro-Symbolic approaches in Visual Question Answering problems"
The next workshop of the laboratory took place.
Seminar "Computational methods for tandem mass spectrometry data annotation"
On November 26, 2021 an online seminar was held on the results of a study by the head of the laboratory Attila Kertesz-Farkas.
Seminar "Deep Convolutional Neural Networks Help Scoring Tandem Mass Spectrometry Data in Database-Searching Approaches"
A workshop of the laboratory was held.
Researchers Discover How to Obtain ‘Ideal’ 3D Cell Cultures for Cancer Research
A group of scientists from Hungary, Russia and Finland have developed a system capable of selecting cancer cells of a specific shape and size—spheroids. SpheroidPicker, the first AI device of its kind, enables a more standardized approach to working with tumour samples. The results of the research have been published in the journal Scientific Reports. One of researchers who worked on the project is Nikita Moshkov, Junior Research Fellow of the Laboratory on AI for Computational Biology.