Reem Suwaileh
Reem Suwaileh received her B.Sc. (2014), MSc (2018), and PhD (2023) degrees from Computer Science and Engineering Department at Qatar University. Reem had led the top 500 distinguished graduates of QU, class 2023.
Reem joined the bigIR team in 2015. She had been working as a research assistant from July 2015 to August 2018, where she worked on ArTest and BigGraphs NPRP projects. Since then, her scholarly focus is on constructing Arabic datasets and test collections. Her research interest involves Information Retrieval (IR) and Natural Language Processing (NLP) with an emphasis on social media applications such as real-time summarization and location mention prediction. She has been a regular member of the Qatar University team participating at TREC since 2015, where her team was ranked second in 2015 and first in 2016 in the real-time summarization track. Her Ph.D. work is on Time-Critical Geolocation for Social Good. Her LMR module was integrated into AIDR system that has UN OCHA as a partner.
Reem published in top conferences such as SIGIR, ECIR, LREC, and COLING. She also published in top journals such as IP&M, IJDRR and IRJ, and authored a book chapter at IHDR. Reem served as a Program Committee member in SIGIR, ACL, CIKM, ECIR, LREC, ICTIR, CLEF, ISCRAM and ArabicNLP Conferences, and the WANLP workshop. She served as a reviewer in AAAI and ICIoT conferences, OSACT workshop, and TALLIP and IP&M Journals. She also judged school research projects in the National Scientific Research and Innovation Week (NSRIW) in 2021 and 2022.
Reem co-organized the BroDyn workshop in 2018, four editions of CheckThat! (Automatic Identification and Verification of Claims) Lab at CLEF in 2018, 2019, 2020, and 2024. She lead the GeoAI-LMR task (both ITU GeoAI challenge and Tanzania IndabaX) in 2022, and 2023. She also co-organized ArAIEval and ArabicNLU shared tasks at ArabicNLP 2024. Reem was a WiDS ambassador and organizer of the 4th annual WIDS conference in Qatar, in 2020. She also delivered a tutorial on geo-tagging text documents at the Artificial Intelligence for Collective Intelligence (AI4CI).
