Research Interests

Machine learning, natural-language processing, bayesian neural networks & analytics, neural extraction & classification, human-computer interaction focused on medical device as well as aviation systems safety including big data analysis & visualisation: human er- ror, empirical experimentation, perceptual interference, probabilistic timing analysis, software modeling, autonomous systems, robotics, unmanned-areal vehicle control systems, flight-deck system safety, digital ledger, cyber-security, forensics

King’s College London

I am currently working on the Robotreviewer (MRC/NIH Fellowship) project: working on novel methods for automatic bias assessment in systematic reviews based on natural language processing and state-of-the-art deep-learning algorithms; supervising user-experience studies; evaluating neural text extraction and classification models

Research Grant

My research is supported by NVIDIA Corporation via the NVIDIA academic GPU grant program.

Referred Journal Articles

Soboczenski, F., Trikalinos T., Kuiper J., Bias R., Wallace, B. & Marshall I., (2018). Machine learning to help researchers evaluate biases in clinical trials: a prospective, randomized user study. Journal of American Medical Informatics Association, in review

Soboczenski, F., Trikalinos T., Kuiper J., Bias R., Wallace, B. & Marshall I., (2018). Machine learning to help researchers evaluate biases in clinical trials: a prospective, randomized user study. Journal of American Medical Informatics Association, in review

Soboczenski, F., Hudson M. & Cairns P., (2016). The Effects of Perceptual Interference on Number-Entry Errors. Interacting with Computers (IwC), 28, vol (2), p. 208 - 218, doi: 10.1093/iwc/iwv034

Conference Publications

Soboczenski, F., Himes, M. D., O’Beirne, M. D., Zorzan, S., Baydin, A. G., Cobb, A. D., Angerhausen, D., Arney, G. N. & Domagal-Goldman, S. D. Bayesian Deep Learning for Exoplanet Atmospheric Retrieval. Accepted to the Bayesian Deep Learning Workshop at the 32nd Conference on Neural Information Processing Systems (NIPS), Montreal, (2018).

Griffin, D., Lesage, B., Bate, I., Soboczenski, F. & Davis, R., (2017). Forecast-Based Interference: Modelling Multicore Interference from Observable Factors. Proceedings of the 25th International Conference on Real-Time Networks and Systems - RTNS ’17 (2017).

Lesage, B., Griffin, D., Bate, I. & Soboczenski, F., (2017). Exploring and Understanding Multicore Interference from Observable Factors. In Proceedings of Automotive - Safety & Security (2017)

Griffin, D., Bate, I., Lesage, B. & Soboczenski, F., (2016). Evaluating Mixed Criticality Scheduling Algorithms with Realistic Workloads. In Proceedings of the 3rd Workshop on Mixed Criticality Systems (2016)

Maxim, D., Soboczenski, F., Bate, I. & Tovar, E., (2015). Study of the Reliability of Sta- tistical Timing Analysis for Real-Time Systems. Proceedings of the 23rd International Conference on Real Time and Networks Systems - RTNS ’15 (2015)

Lesage, B., Griffin, D., Soboczenski, F., Bate, I., & Davis, R., (2015). A Framework for the Evaluation of Measurement-based Timing Analyses. Proceedings of the 23rd International Conference on Real Time and Networks Systems - RTNS ’15 (2015)

Griffin, D., Lesage B., Soboczenski F., Bate, I. & Davis, R., (2015). Modelling Fault Dependencies when Execution Time Budgets are Exceeded. Proceedings of the 23rd International Conference on Real Time and Networks Systems - RTNS ’15 (2015)

Borghouts, J., Soboczenski, F., Cairns P. & Brumby, D., (2015). Visualising Magnitude: Graphical Number Representations Help Users Detect Large Number Entry Errors. In proceedings of the Human Factors and Ergonomics Society (HFES) 2015 International Annual Meeting, Los Angeles - (Best Paper Award)

Soboczenski, F., Hudson M. & Cairns P., (2014). The Effects of Perceptual Interference on Number- Entry Errors. Proceedings of the first Int. conf. on Interaction Design and Human Factors, Kochi Japan.

Soboczenski, F., Cairns, P., & Cox, A. L. (2013). Increasing Accuracy by Decreasing Pre- sentation Quality in Transcription Tasks. In Human-Computer Interaction Proc. Interact 2013, Springer LNCS 8118 (pp. 380-394)

Soboczenski, F., Datta, A. & Cairns, P. (2013). Reducing Number-Entry Errors in Medical Systems: A Tale of Two Studies. In proceedings of the 6th York Doctoral Symposium on Computer Science and Electronics 2013 (pp. 94)

Conference Posters

Soboczenski, F., Himes, M. D., O’Beirne, M. D., Zorzan, S., Baydin, A. G., Cobb, A. D., Angerhausen, D., Arney, G. N. & Domagal-Goldman, S. D. INARA: Intelligent exoplaNet Atmospheric RetrievAl. Deep Learning Workshop at the 32nd Conference on Neural Information Processing Systems (NIPS), Montreal, (2018).

Soboczenski, F. (2014). 5-Key interfaces for medical devices. British Computer Society - Doctoral Consortium on design and interfaces.

Soboczenski, F. (2013). Reducing Number-Entry Errors in Healthcare. Poster presented at the BCS Health Informatics Conference Scotland 2013

Soboczenski, F. (2013). A tale of two studies. Poster presented at the 6th York Doctoral Symposium on Computer Science and Electronics 2013

Other Publications

Himes, M. D., O’Beirne, M. D., Soboczenski, F., Zorzan, S., Baydin, A. G., Cobb, A. D., Angerhausen, D., Arney, G. N. & Domagal-Goldman, S. D. (2018) NASA Fron- tier Development Lab: Astrobiology Team II: From Biohints to Confirmed Evidence of Life: Possible Metabolisms Within Extraterrestrial Environmental Substrates. NASA Technical Memorandum, submitted and under review by the agency.

Soboczenski, F. (2014) The Effect of Interface Elements on Transcription Tasks to Reduce Number-Entry Errors. PhD thesis, University of York.

Soboczenski, F. (2009) Ontology Based Modeling Rules for the Unified Modeling Language (UML). Diploma thesis, Deggendorf Institute of Technology, Germany.

Items in preparation

Soboczenski, F. (2018). An introduction to R - from simple statistics to machine learning applications. First manuscript available on Github

Students advising

Joyce Tlhoolebe - MSc
Graduate student in Cyber-Security, University of York. Object selection as a biometric authentication system, (2016).

Qianyun Jiang - MSc
Graduate student in Cyber-Security, University of York. Malware Identification, (2016).

Raya Al-Khayari - MSc
Graduate student in Cyber-Security, University of York. An analysis of vulnerability disclosure mechanisms, (2016).

Rashid Al-Saidi - MSc
Graduate student in Cyber-Security, University of York. Detecting and distinguishing encrypted from compressed containers, (2016).

Judith Borghouts - MSc (Co-supervised with Dr. Paul Cairns)
Graduate student in Human-Centered Interactive Technologies, University of York. The effect of different design features on reducing number-entry errors in medical devices, (2013).

Aniket Datta - BSc
Undergraduate student in Human-Centered Interactive Technologies, University of York. Chevron interface studies on reducing number-entry errors in medical devices, (2013).

Google scholar

A full list of publications is available at the above Google scholar link.