Organizers 👨👩👦👦
José Ángel González (jose.gonzalez@symanto.com) is Senior 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 mainly works on Natural Language Processing (NLP) fields such as summarization, affective analysis, and figurative language, proposing solutions based on deep learning. His main interest is to develop computational models that understand and generate human language in the same way humans do. José Ángel won the 21st Edition of the SEPLN Award to the Best Doctoral Thesis in NLP and participated in several IberLEF and IberEval workshops under the umbrella of the ELiRF-UPV team with excellent results since 2017 (winner in TASS 2017, 2018, 2019, and 2020, IroSVA, and COSET).
Areg Sarvazyan (areg.sarvazyan@symanto.com) is 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 at the UPV and is currently studying its Master’s Degree in Artificial Intelligence, Pattern Recognition and Digital Imaging.
Marc Franco-Salvador (marc.franco@symanto.com) holds a cum laude international PhD in multilingual textual similarity and a MAVIR 2013 Award to the best MSc thesis on Language Technologies applied to Intelligent Systems of Access. He is currently Chief Scientific Officer at Symanto. In this role, he works together with his team to provide our data analysis platform with novel solutions based on the latest techniques of artificial intelligence, natural language processing, machine, and deep learning. He has more than 10 years of experience as a researcher in the natural language processing field. This includes publishing more than 40 research publications, participating in more than eight national and international granted and funded R&D projects, and participating and ranking first in several shared tasks, e.g. SemEval 2016 - task 3: community question answering (Franco-Salvador et al., 2016; Nakov et al., 2016), and eRisk 2021: Early risk prediction on the Internet shared task@CLEF (Basile et al., 2021; Parapar et al., 2021). In addition, this includes being part of the organizational committee at several conferences (Conference on Lexical and Computational Semantics (*SEM 2015), European Chapter of the Association for Computational Linguistics (EACL 2017)) and shared tasks (PAN@Conference and Labs of the Evaluation Forum 2013 - Profiling Cryptocurrency Influencers with Few-shot Learning).
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.
Berta Chulvi (berta.chulvi@upv.es), PRHLT Research Center, Universitat Politècnica de València and Dept. of Social Psychology, Universitat de Valencia. She helped in the organisation of shared tasks on stereotyping in social media against women, immigrants and the LGBTI community (Ortega-Bueno et al., 2022; Fersini et al., 2022).
Paolo Rosso (prosso@dsic.upv.es) is full professor at the Universitat Politècnica de València, Spain. His research interests focus mainly on author profiling, irony detection, fake news and hate speech detection. He has co-organised more than 30 benchmark activities: since 2009 at the PAN Lab (both at CLEF and FIRE), at SemEval (e.g. HatEval in 2019 on multilingual detection of hate speech against immigrants and women in Twitter) , at IberLEF (previously IberEval) and Evalita (e.g. automatic misogyny identification in 2018 in both evaluation forums, and in 2020 at Evalita). He has been track coordinator at FIRE (2018 and 2019), chair of Evalita (2018), and chair of IberLEF (2018-2020).