معرفی
András Kornai serves as Professor at Budapest University of Technology and Economics and Senior Scientific Advisor at the Computer and Automation Research Institute of the Hungarian Academy of Sciences. His career integrates mathematical theory with linguistic computation, contributing to core technologies in language processing.
His academic foundation includes:
- Mathematics degree (1983) from Eötvös Loránd University, Budapest (advisor: Miklós Ajtai)
- Linguistics degree (1991) from Stanford University (advisor: Paul Kiparsky)
Kornai's research pioneers mathematical approaches to natural language phenomena, spanning speech recognition, OCR, and computational linguistics with emphasis on finite-state models and Hungarian language processing. His work bridges theoretical frameworks like hidden Markov models with practical applications in geographic reference analysis, evidenced by co-organizing the 2003 NAACL workshop on geographic information extraction. Current leadership includes directing the HLT research group at BME, advancing NLP infrastructure through mathematical rigor.
He actively mentors students in language technology through the HLT group (http://hlt.bme.hu), focusing on foundational algorithms for text and speech processing. His geographic information extraction work intersects with GIS and spatio-temporal reasoning, contributing to standards for gazetteer integration in multilingual NLP systems.
