Chris von Csefalvay has been active in the research and development of new technologies, ideas and solutions for perennial problems. Of these, a significant part is unfortunately subject to non-disclosure and governmental secrecy provisions for national security and miscellaneous other reasons. His principal areas of interest and investigation are:

• epidemiology: computational epidemiology, especially modeling disease-avoidant behaviour and general modeling, as well as signal identification from mining passive reporting pharmacovigilance systems (specific emphasis on VAERS)
• operations research: efficient spatial optimisation of critical public resources, mixed quadratic programming, pursuit/evasion
• mathematics: zero-knowlege proofs of CBRN decommissioning with a specific emphasis on neutron spectroscopy
• computer science: graph algorithms, sensor fusion computation, computer vision and deep learning, autonomous systems

Selected research papers by Chris von Csefalvay

• Mutua V, Newnex M, Bundi B, von Csefalvay C, Oriko D, Kitunguu P. Sudden bilateral lower limb paralysis with dural ectasia in Neurofibromatosis type 1: A case report. Med Case Rep Study Protoc. 2021;2:9(e0165)
• von Csefalvay, C. (2021). Anaphylactic events in mRNA vaccines: a reporting case-control study. medRxiv:2021.07.19.21260714.
• von Csefalvay, C. (2021). A case-control study of autoimmune AEFIs following COVID-19 vaccination reported to VAERS. medRxiv:2021.07.06.21260074. Submitted to PLOS One.
• von Csefalvay, C. (2021). VAERS data reveals no increased risk of neuroautoimmune adverse events from COVID-19 vaccines. medRxiv:2021.06.13.21258851. Submitted to Frontiers in Pub Health.
• von Csefalvay, C. (2021). Early evidence for the safety of certain COVID-19 vaccines using empirical Bayesian modeling from VAERS. medRxiv:2021.06.10.21258589.
• von Csefalvay, C. (2020). Vector quantisation and partitioning of COVID-19 temporal dynamics in the United States. arXiv:2008.00559.
• von Csefalvay, C. (2020). Statistical dynamics of SARS-CoV-2 as a differential game. arXiv:2007.13734. Submitted to Systems.
• Foldi, T., von Csefalvay, C. and Perez, N.A. (2020). JAMPI: Efficient matrix multiplication in Spark using Barrier Execution Mode. arXiv:2007.01811. Big Data Cogn Comp 4(4) (2020), 32.
• von Csefalvay, C. and Foldi, T. (2020). PAWS: Towards a globally integrated outbreak surveillance system for public health. doi:10.5281/zenodo.3782877
• von Csefalvay, C. (2019). Novel quantitative indicators of digital ophthalmoscopy image quality. arXiv:1903.02695
• von Csefalvay, C. (2015). Ecological metrics of diversity in understanding social media. arXiv:1501.07621.
• von Csefalvay, C. (2009). On Good Intentions and Poor Outcomes: A Critical Retrospective on Chester v Afshar. 9 U. C. Dublin L. Rev. 46.

Data sets by Chris von Csefalvay

Chris von Csefalvay is a strong supporter of open data and have curated and/or contributed to several public data sets for research use.

• Starschema COVID-19 Data Set
• 2019 Samoan measles outbreak epidemiological data
• 2018 DRC Ebola outbreak epidemiological data
• CODRAS (COnsolidated Diabetic Retinopathy Assessment Set)

Selected patents & applications by Chris von Csefalvay

• A Method, Software and Architecture for the Monitoring of Data Flows in ETL Systems, GB1420320.2 (15 November 2014)
• A method, software and architecture for a graphical user interface for creating, editing, visualizing and authenticating smart contracts, GB1605154.2 (11 May 2016)
• Preventing repeated malicious online communications using a proof of work approach, GB1607128.4 (08 June 2016)

Thesis supervision

Chris von Csefalvay currently supervises thesis students for the Faculty of Mathematics, Budapest University of Technology and Economics. Aspiring third-years should get in touch via the contact panel as early as possible. There are typically two thesis slots per semester, and preference goes to students on the Data Science track.