José Ángel González (jose.gonzalez@symanto.com) is Principal Research Scientist at Symanto since November 2022. He holds a cum laude international PhD in Computer Science from Universitat Politècnica de València, while he was member of the Language Engineering and Pattern Recognition (ELIRF) research group in the Valencian Research Institute for Artificial Intelligence (VRAIN). He works in Natural Language Processing fields such as summarization, affective analysis, and language modeling, proposing efficient solutions based on deep learning. José Ángel won the 21st Edition of the SEPLN Award for the Best Doctoral Thesis in NLP and participated in several IberLEF and IberEval workshops under the umbrella of the ELiRF-UPV team with seven winning participations since 2017. He also serves as Adjunt Professor at European University of Madrid and University of Barcelona, and previously he was Teaching Assistant at Polytechnic University of Valencia. José Ángel also organized the AuTexTification and IberAuTextification shared tasks at IberLEF 2023 and 2024. He participated in the MGT detection subtask in Task 8 in Semeval@NAACL2024, proposing the winning system for the monolingual track.
Areg Sarvazyan (areg.sarvazyan@symanto.com) has been a Junior Research Scientist at Symanto since October 2022. He previously developed Automatic Speech Recognition systems at Stadler and was a member of the Machine Learning and Language Processing (MLLP) research center of the Valencian Research Institute for Artificial Intelligence (VRAIN) at Universitat Politècnica de València (UPV), where he worked on simultaneous and streaming machine translation systems. These projects, together with experience obtained through deep learning competitions, aided him in building a strong foundation in data science, machine learning and deep learning. He obtained his bachelor’s degree in computer science and Master’s Degree in Artificial Intelligence, Pattern Recognition and Digital Imaging in the UPV. Areg organized the AuTexTification and IberAuTexTification shared tasks at IberLEF 2023 and 2024, with more than one hundred participants, which are highly related to the present proposal. He also participated in the MGT detection subtask in Task 8 in Semeval@NAACL2024, proposing the winning system for the monolingual track.
Angelo Basile (angelo.basile@symanto.com) is a Research Scientist at Symanto Research since October 2018: he works on building classification models and internal ML tools. He previously worked in the Bixby Team for Samsung, where he took care of the NLG module for Italian. He is an Erasmus Mundus Language and Communication Technology alumnus and obtained a master in Linguistics from the University of Groningen (The Netherlands) and a master’s in computer science from the University of Malta (The Maltese Islands). He worked on detecting language variation using syntactic features and neural models.
Ian Borrego (ian.borrego@symanto.com) has been a Data Scientist at Symanto since June 2022. He has worked as a consultant in the banking and financial evaluation sectors, applying various valuation models and uncovering the inner workings of corporate banking institutions. Gradually, his curiosity for data science grew after participating in different training programs at his previous companies. He wanted to learn more about the world of data, so he began using self-taught methods. Eventually, he decided to shift his career and join a data science bootcamp to improve and solidify his skills as a Data Scientist. At Symanto, he applies his financial experience and data science tools to products related to finance. He not only relies on traditional machine learning models but also specializes in natural language processing and network analysis.
Mara Chinea (mara.chinea@symanto.com) is Research Scientist at Symanto since September 2018. Previously, she had been member of Pattern Recognition and Human Language Technology (PRHLT) research center, where she worked on statistical machine translation. She obtained her PhD from Univeritat Politècnica de València for her work on advanced techniques of domain adaptation in machine translation. Her long term research goal is to develop natural language processing techniques to build learning systems with little human supervision.
Francisco Rangel (francisco.rangel@symanto.com) is Chief Product Officer at Symanto since 2019 where he leads the productisation of the NLP capabilities of the company to bring them to market. Francisco obtained his cum laude PhD in Computer Science in 2016 from the Universitat Politècnica de València (Spain) and has won several awards for his research such as MAVIR 2007 for the best master thesis and SEPLN 2017 for the best doctoral thesis. Francisco’s areas of interest lead him to collaborate in the organisation of several evaluation tasks such as the Author Profiling series at PAN lab at CLEF since 2013 (Rangel et al., 2013) (Bevendorff et al., 2022) or at PAN lab at FIRE in 2016 (Rangel et al., 2016) and 2017 (Litvinova et al., 2017), the HatEval shared task at SemEval 2019 (Basile et al., 2019), or the StanceCat (Taulé et al., 2017) and MultiStanceCat (Taulé et al., 2018) tasks at IberEval 2017 and 2018 respectively, and he is chair of IberLEF since 2021.