Experience

• Feb 2024 - Present
  Computational Neuroscientist @ Sonera

  Developing machine learning methods for analyzing and decoding multichannel electrophysiology data.




• Apr 2023 - Present
  Technical Specialist @ BCI Stealth Startup

  I am a former co-founder and current specialist at a BCI stealth startup.




• Jul 2023 - Dec 2023
  Scientific Consultant @ Sonera

  Developed machine learning methods for analysis and decoding of multichannel electrophysiology data.




• Oct 2020 - Dec 2023
  PhD in Machine Learning + Neuroscience @ University of Oxford

  My research at Oxford is threefold.
  First, I successfully designed and executed inner speech EEG and MEG experiments. I collected over 40 hours of data, which I analysed using signal processing, machine learning, and innovative interpretability and visualization methods.
  
  Second, I pioneered the use of a new noninvasive device, optically-pumped magnetometers (OPM). I successfully demonstrated the effectiveness of language decoding in OPMs in a first-of-its-kind experiment.
  
  Finally, my research in deep learning methods has led to significant advancements in group-level decoding of brain data, resulting in two publications and presentations at multiple international conferences. For example, I adapted the conditional Wavenet model to generate and decode brain data, through both discriminative and generative frameworks. My model increased the multi-subject decoding accuracy of visual images from MEG data, from 15% to 50%. I also adapted the GPT2 model for multichannel MEG forecasting and showed that generated data resembles real data in a number of metrics. Generated data can be used as pretraining for a decoder to improve performance.




• Feb 2020 - Jun 2020
  M.S. Erasmus Semester @ KU Leuven

  I participated in the Erasmus program at KU Leuven, taking 4 courses: Bioinformatics, Brain Computer Interfaces, Topics in Behavioural Neuroscience, Artificial Neural Networks and Deep Learning.




• Sep 2018 - Jun 2020
  Computer Science Engineering M.S. @ Budapest University of Technology

  Excellent with Highest Honours, 4.73/5.00 degree grade. During my Master's I worked on dialogue modeling research, detailed in my Natural Language Processing Researcher experience description. I presented at 6 conferences and meetups and I was awarded the prestigious National Excellence Scholarship. I also attended EEML, a machine learning summer school in Romania.




• Feb 2018 - Oct 2019
  Natural Language Processing Researcher @ Budapest University of Technology

  As a researcher during my Master's, I developed one of the first Transformer-based chatbots in 2017. This project and a comprehensive review of 100+ publications received over 400 GitHub stars and earned me a national research competition win. Despite having no prior Python or deep learning experience, I achieved these accomplishments in under a year. My research included the development of new methods and datasets for improving chatbots, resulting in multiple actively used GitHub repositories (10-100 stars) and a publication at the Association for Computational Linguistics, the leading conference in the field.
  
  I also developed an online deep learning chatbot, utilized by hundreds. I modified and trained GPT-2 on a dataset containing 14.8 million utterances in 7 languages, that I created from books. I integrated the models into the backend of my website with a response time of less than 1 second, capable of handling tens of simultaneous users. These accomplishments also earned me a national excellence scholarship and a salary from the university, a rare achievement for a Master's student.




• Jul 2017 - Aug 2018
  Software Engineer @ Bosch

  As a data-driven problem solver at Bosch, I successfully applied deep learning techniques to improve parking space segmentation through my self-initiated project. By developing an OpenGL-based user interface in both C++ and Python, I was able to manipulate parking spots in real-time, overlaid on a car's camera feed. I collected and labelled 10,000 images with the help of a test driver and modified the YOLO computer vision model achieving impressive results. These efforts led to the allocation of a dedicated team and additional funding for the project by upper management. Throughout the project, I navigated cross-functional (economic, social, engineering, software) challenges with ease, collaborating with engineering groups to drive success.




• Sep 2014 - Jan 2018
  Mechatronics Engineering B.S. @ Budapest University of Technology

  Excellent with Highest Honours, 4.79/5.00 degree grade. During my B.S. I took part in a research project and implemented a molecular circuit simulation platform in C++, winning 2nd place at a university conference.