I am working on Pleistocene mammal extinctions. Co-developer of R packages to download data from open access databases (rAvis and paleobioDB), and team member of www.ecoClimate.org, an open access repository to access climatic data for the past, present and future.
I am a marine biologist working as a fishery and benthic researcher at the Institute for Marine Resources and Biotechnologies (IRBIM) of the National Researche Council (CNR) in Ancona, Italy. I held my PhD in 2010 at the The Open University (Milton Keynes, UK) working at the Stazione Zoologica A. Dohrn of Naples (Italy) where I conducted a study on the spatial and temporal distribution of macro benthic assemblages associated to Posidonia oceanica seagrass and on several features of the plant itself. I got a Master degree in 2005 at the Polytechnic University of Marche after the Bachelor's degree in Marine Biology at the same university in 2004. I participated in several surveys at sea in the last years as well as to several diving expeditions in the Indian Ocean and Mediterranean Sea.
Professor of Psycholinguistics at the Department of Linguistics, University of Potsdam, Germany. Specialization in computational models of sentence comprehension; sentence processing in aphasia; working memory and language comprehension; Bayesian statistics.
Dr. Chaman Verma is an Assistant Professor at the Department of Media and Educational Informatics, Faculty of Informatics, Eötvös Loránd University. He is also the project leader and chief researcher of his project sponsored by National Research, Development and Innovation (NRDI) Hungary. He also won a young educator scholarship for novel research sponsored by the EKÖP, NRDI Fund, and the Hungarian Government.
He pursued a post-doctorate at the Faculty of Informatics, Eötvös Loránd University, Budapest, Hungary, sponsored by UNKP, MIT (Ministry of Innovation and Technology), the National Research, Development and Innovation (NRDI) Fund, and the Hungarian Government. He received a Ph.D. in informatics from the Doctoral School of Informatics, Eötvös Loránd University, Budapest, Hungary, with the Stipendium Hungaricum Scholarship funded by the Tempus Public Foundation, Government of Hungary. During his Ph.D., he won the EFOP Scholarship, co-founded by the European Union Social Fund and the Government of Hungary, as a professional research assistant in a real-time system from 2018 to 2021. He also received the Stipendium Hungaricum Dissertation Scholarship of Tempus Public Foundation, Government of Hungary, from 2021 to 2022.
He has been awarded several Erasmus Scholarships for conducting international research and academic collaboration with European and non-European universities. He received the best scientific publication award from the Faculty of Informatics, Eötvös Loránd University, Budapest, Hungary, In the years 2021-2024. He has also been awarded the ÚNKP scholarship for research by the Ministry of Innovation and Technology and the National Research, Development and Innovation (NRDIO) Fund, Government of Hungary, 2021-2023.
He has around ten years of experience in teaching and industry. He has over 150 scientific publications in the IEEE, Elsevier, Springer, IOP Science, Walter de Gruyter and MDPI. His research interests include data analytics, feature engineering, real-time systems, and educational informatics. He is a life member of ISTE, New Delhi, India. He is a member of the editorial board and a reviewer of various international journals and scientific conferences. He was the leading guest editor of the special issue Advancement in Machine Learning and Applications in Mathematics, IF- 2.25, MDPI, Basel, Switzerland, in 2022. He was also a guest editor in two Springer journals. He is a co-editor in the series of conference proceedings of ICRIC-2021-24 published by Springer, Singapore. He reviews many scientific journals, including IEEE, Springer, Elsevier, Wiley, and MDPI. He has Scopus citations of 1603 with an H-index of 24. He has Web of Science citations of 355 with an H-index of 13.
I am a statistician who works with biological and genomic datasets to understand the mechanisms underlying human disease and identify possible treatments. My main focus is on autoimmune diseases.
Dr. Shibiao Wan is currently an Assistant Professor in the Department of Genetics, Cell Biology and Anatomy, and the Co-Director for the Bioinformatics and Systems Biology (BISB) PhD Program at University of Nebraska Medical Center (UNMC). He is also an Assistant Professor (courtesy) in the Department of Biostatistics at UNMC.
With more than 15 years of experience in machine learning, bioinformatics, and computational biology, Dr. Wan has published >60 articles in top-tiered journals such as Genome Research, Nature Communications, Science Advances, Circulation Research, Briefings in Bioinformatics, and Bioinformatics. Dr. Wan is the Editor-in-Chief for Current Proteomics, and an Associate Editor/Academic Editor/Editorial Board Member for a series of prestigious journals such as Briefings in Functional Genomics, Heliyon, BMC Bioinformatics, International Journal of Microbiology, PeerJ Computer Science, BioMed Research International, and Computational and Mathematical Methods, and a guest associate editor for multiple high-impact journals.
He is a Scientific Program Committee (SPC) member for American Medical Informatics Association (AMIA) Annual Symposium and a Technical Program Committee (TPC) member for >20 machine learning related international conferences including IEEE ICTAI. Dr. Wan is also a reviewer for >70 prestigious journals including Nature Biotechnology, Nature Methods, Nature Communications, Nature Computational Science, Science Advances, Nucleic Acids Research, Advanced Science, Cancer Research, Genome Biology, and Genome Medicine. Dr. Wan has received a number of accolades including the Springer Nature Editor of Distinction Award in 2025 by Springer Nature, the New Investigator Award in 2024 by UNMC, the FIRST Award in 2023 by Nebraska EPSCoR, the Outstanding Young Alumni Award in 2022 by HK PolyU as well as the Global Peer Review Awards (top 1%) in “Cross-Field” and “Biology and Biochemistry” in 2019 by Clarivate. Dr. Wan is a member of AACR, AMIA, ISCB and ACM and an IEEE Senior Member.
Dr Dapeng Wang is a Senior Bioinformatician in Integrative Analysis at the COMBAT consortium at the University of Oxford using multi-omics techniques in combination with the cutting-edge bioinformatic approaches and statistical methods to explore the pathogenesis of COVID-19 and stratification of patients as well as inform the treatment strategy based on genomics information.
Dr Wang received a bachelor’s degree in mathematics from the Shandong University in 2006 and obtained a PhD degree in bioinformatics from the Beijing Institute of Genomics of the Chinese Academy of Sciences in 2011. After his graduation, he continued to conduct research at the same institute from 2011 to 2014 and afterwards moved to the UK to take up various roles at the Cancer Institute at the University College London (2014-2016), the Department of Plant Sciences at the University of Oxford (2016-2018) and the LeedsOmics at the University of Leeds (2018-2020).
Qiang Wang received a Ph.D in Environmental Science from the Chinese Academy of Science in 2009, was an Associate Professor (2010) at the Qingdao Institute Of Bioenergy & Bioprocess Technology, Chinese Academy Of Sciences, and a Professor (2011-16) at Xinjiang Ecology And Geography Institute, Chinese Academy Of Sciences, and then moved to China University of Petroleum (2016-2022). His research focuses on energy-environment-health issues through multidisciplinary research methods
Through clever use of time series statistical models (e.g., joint regression models, variable intercept models, variable coefficient models), high-precision combined forecasting models (e.g. gray forecasting and neural network models combined forecasting models), multilateral input-output models, decomposition models (e.g. index decomposition method, structural decomposition method), Dr. Wang has published more than 180 peer-reviewed papers (corresponding author) in high profile English journals.
These papers have been cited over 8,800 (Google Scholar)/ 7,100(Scopus)/ 6,200 (WoS) times by October 2022. 19 papers are selected as global ESI 0.1% Hot Papers, and 36 papers are selected as global ESI 1% Highly Cited Papers that perform in the top 1%. Dr. Wang’s h index is 53 (Google Scholar)/ 49(Scopus)/ 46 (WoS).
I’m a statistician / quantitative ecologist at the Northwest Fisheries Science Center (NOAA) in Seattle and an affiliate professor at the School of Aquatic and Fishery Sciences (SAFS) at the University of Washington. I work on a wide range of statistical problems – population dynamics, extinction risk, conservation genetics, fisheries stock assessment, reproductive success studies, etc. Most of the species I study are fish, but I also work with data from marine mammals, seabirds, and turtles. Much of my recent modeling interests have been pursuing applications of multivariate state-space time series and spatio-temporal models, isotope mixing models, and Bayesian model selection techniques.
Associate Professor in the Department of Wildlife Ecology and Conservation at the University of Florida. Moore Foundation Investigator in Data-Driven Discovery. National Science Foundation CAREER 'Young Investigators' Award recipient. Member of the Data Carpentry and Impactstory boards of directors.
My research focuses on data-intensive questions in ecology, using large ecological datasets, advanced statistical/machine learning methods, and theoretical modeling to understand ecological patterns.
Robert Winkler is Principal Investigator of the Laboratory of Biochemical and Instrumental Analysis at the CINVESTAV Unidad Irapuato and faculty member for the postgraduate programs Plant Biotechnology and Integrative Biology. His research topics include novel mass spectrometry techniques such as low-temperature plasma ionization and covalent protein staining, new approaches in the high-throughput metabolomic profiling of plants, computational mass spectrometry and proteomics.
I develop statistical methodology and software for the analysis of -omics data. I am particularly interested in the regulation of transcription: the molecular mechanism as well as its association with disease.