Dr. Mourad Khayati | Data Quality | Best Researcher Award

University of Fribourg | Switzerland

Publication Profile

🌟 EARLY ACADEMIC PURSUITS

Dr. Mourad Khayati began his academic journey with a solid foundation in computer science, obtaining his MSc in 2007 from the University of Jendouba (Tunisia) and INSA-Lyon (France). His passion for data analytics led him to pursue a PhD in Computer Science from the University of Zürich (Switzerland), where he earned his doctorate in 2015 under the guidance of Prof. Michael H. Böhlen. His early research explored matrix decomposition techniques, particularly in recovering missing values in time series data, an area that would become central to his career. 🎓

🏢 PROFESSIONAL ENDEAVORS AND ACADEMIC LEADERSHIP

Currently a Senior Lecturer at the University of Fribourg in Switzerland, Dr. Khayati is involved in cutting-edge research and teaching. His expertise spans data analytics, time series repair, benchmarking, and IoT analytics. Over the years, he has not only contributed to significant advancements in these fields but also played an essential role in mentoring the next generation of computer scientists. As a co-supervisor for PhD students and a supervisor for MSc and BSc theses, his leadership in the academic community is evident. 🏫

💡 CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Khayati’s research focuses on enhancing data analytics with repair functionalities, especially in handling “dirty” data. His work in the field of time series repair, IoT analytics, and benchmarking has provided novel methodologies for improving the accuracy and reliability of data. His contributions have extended to European projects such as the FashionBrain project, where he led the technical efforts to analyze Europe’s vast fashion data universe. Through the development of tools like ImputeBench and the ORBITS framework, Dr. Khayati has pushed the boundaries of data repair, helping businesses and researchers leverage incomplete data effectively. 📊

🌍 IMPACT AND INFLUENCE

Dr. Khayati’s work has had significant real-world applications. His research in missing data recovery has been applied in diverse fields, from fashion trend prediction to environmental hazard forecasting. His innovative tools have not only shaped academic research but have also influenced data-driven industries, highlighting the value of accurate, repaired datasets. Through collaborations and workshops, Dr. Khayati has spread knowledge on the importance of data integrity and the repair process across global academic and industrial forums. 🌐

🏆 ACADEMIC CITATIONS AND RECOGNITION

Dr. Khayati’s research has received widespread acclaim, evidenced by his numerous high-impact publications. His work on time series data repair has been published in prestigious journals such as VLDB, IEEE, and the Journal of Knowledge and Information Systems. With a solid record of conference presentations and awards (including the Best Experiments and Analysis Paper Award at PVLDB’20), Dr. Khayati’s contributions are frequently cited by peers, solidifying his reputation as a thought leader in the field. 🏅

💼 LEGACY AND FUTURE CONTRIBUTIONS

Looking forward, Dr. Khayati’s research continues to evolve, focusing on more efficient and scalable data repair solutions. With his ongoing supervision of PhD and MSc students and involvement in international collaborations, his legacy in the field of data science is secure. His ongoing projects promise to address new challenges, such as multimodal data repair and handling extreme-scale time series data, ensuring his continued influence on the future of data analytics. 🔮

🔑 KEY MILESTONES AND ACHIEVEMENTS

ProvDS Project: Dr. Khayati led a project funded by the Swiss National Science Foundation (SNSF), exploring uncertain provenance management over incomplete linked data, a critical advancement for data provenance and reliability.
FashionBrain Project: As the technical lead, Dr. Khayati made significant contributions to understanding Europe’s fashion data universe, combining research and industry application.
Awards & Distinctions: He has received several awards for his work, including the Chair Award at ICWE’16 and the Excellence MSc Scholarship from the Tunisian Ministry of Education.
Influence in Academic Service: Serving as a committee member for PhD defenses, program committee member for renowned conferences, and as a reviewer for top-tier journals, Dr. Khayati actively shapes the academic landscape.

Publication Top Notes

ImputeVIS: An Interactive Evaluator to Benchmark Imputation Techniques for Time Series Data

- Authors: Mourad Khayati, Quentin Nater, Jacques Pasquier
- Journal: Proceedings of the VLDB Endowment (Proc. VLDB Endow.)
- Year: 2024 🗓️

SEER: An End-to-End Toolkit for Benchmarking Time Series Database Systems in Monitoring Applications

- Authors: Luca Althaus, Mourad Khayati, Abdelouahab Khelifati, Anton Dignös, Djellel Eddine Difallah, Philippe Cudré-Mauroux
- Journal: Proceedings of the VLDB Endowment (Proc. VLDB Endow.)
- Year: 2024 🗓️

A survey of multimodal event detection based on data fusion

- Authors: Manuel Mondal, Philippe Cudré-Mauroux, Hông-Ân Sandlin, Philippe Cudré-Mauroux
- Journal: The VLDB Journal
- Year: 2024-12-15 🗓️

TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications

- Authors: Abdelouahab Khelifati, Mourad Khayati, Anton Dignös, Djellel Difallah, Philippe Cudré-Mauroux
- Journal: Proceedings of the VLDB Endowment (Proc. VLDB Endow.)
- Year: 2023-07 🗓️

Peer Grading the Peer Reviews: A Dual-Role Approach for Lightening the Scholarly Paper Review Process

- Authors: Mourad Khayati
- Journal: WWW ’21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia
- Year: 2021 🗓️

Dr. JunYun Zhang l Data Quality | Best Researcher Award

Peking University, China

Author Profile

👨‍🔬 Dr. JunYun Zhang – Academic Profile

Dr. JunYun Zhang is an Associate Professor at the School of Psychological and Cognitive Sciences at Peking University, China. He has been a key figure in the academic world since 2012, holding various positions, including Assistant Professor at Peking University and a visiting scholar/postdoc at the University of California, Berkeley. His diverse career also includes a lecturer role at the Institute of Cognitive Neuroscience & Learning, Beijing Normal University.

🎓 Educational Background

Dr. Zhang completed his Ph.D. in Neurobiology from the Institute of Neuroscience, Chinese Academy of Sciences, where he worked under the mentorship of Cong Yu. His academic journey began with a B.S. in Special Education from East China Normal University, laying the foundation for his future research in cognitive sciences.

🧠 Research Interests

His primary research areas encompass visual perception and cognition, as well as learning and memory. Notably, Dr. Zhang explores topics such as perceptual learning, amblyopia (a visual disorder), and visual crowding, where he investigates how the brain processes and learns visual stimuli, even in challenging conditions.

💡 Research Grants

Dr. Zhang has received several prestigious grants, including significant funding from the Natural Science Foundation of China for projects spanning 2024 to 2027, 2020 to 2023, and earlier years. These grants support his ongoing research into visual perception and learning mechanisms.

🎤 Conference Presentations & Moderation

Dr. Zhang has actively contributed to numerous conferences, where he not only presents his work but also moderates sessions. He has been a part of invited symposia and workshops worldwide, including events in Geneva, Switzerland, and Nara, Japan. His conference talks span high-profile events such as the Vision Science Society and European Conference on Visual Perception.

⚙️ Professional Activities

Dr. Zhang plays a vital role in the academic community through editorial duties. He is an Associate Editor for Frontiers in Psychology – Consciousness Research and reviews for multiple prestigious journals like Vision Research and PLOS One. He is a member of renowned organizations such as the Vision Sciences Society and the Society for Neuroscience.

📚 Teaching Contributions

Dr. Zhang’s commitment to education is evident through his involvement in both undergraduate and graduate courses. He teaches a variety of subjects, including Vision & Visual Arts, Experimental Psychology, and Perceptual Learning, and has developed specialized graduate courses on research methods and perceptual processing. His passion for cognitive sciences and his experience continue to inspire future generations of researchers.

Dr. Zhang is a dedicated scholar, deeply engaged in both research and teaching, with a significant impact in the fields of visual perception and cognitive neuroscience. 🌍

📖 Top Noted Publications

Feature variability determines specificity and transfer in multiorientation feature detection learning

Authors: Zhu, J.-P., Zhang, J.-Y.
Journal: Journal of Vision
Year: 2024

Contour integration deficits at high spatial frequencies in children treated for anisometropic amblyopia

Authors: Jiang, S.-Q., Chen, Y.-R., Liu, X.-Y., Zhang, J.-Y.
Journal: Frontiers in Neuroscience
Year: 2023

The impact of training on the inner–outer asymmetry in crowding

Authors: Chen, Y.-R., Zhang, Y.-W., Zhang, J.-Y.
Journal: Journal of Vision
Year: 2023

Dichoptic perceptual training in children with amblyopia with or without patching history

Authors: Liu, X.-Y., Zhang, Y.-W., Gao, F., Chen, F., Zhang, J.-Y.
Journal: Investigative Ophthalmology and Visual Science
Year: 2021

Dichoptic de-masking learning in adults with amblyopia and its mechanisms

Authors: Liu, X.-Y., Zhang, J.-Y.
Journal: Investigative Ophthalmology and Visual Science
Year: 2019

Vernier learning with short- and long-staircase training and its transfer to a new location with double training

Authors: Zhang, J.-Y., Yu, C.
Journal: Journal of Vision
Year: 2018

Mourad Khayati | Data Quality | Best Researcher Award