Academic Editors
The following people constitute the Editorial Board of Academic Editors for PeerJ Computer Science. These active academics are the Editors who seek peer reviewers, evaluate their responses, and make editorial decisions on each submission to the journal. Learn more about becoming an Editor.
Tak-Wah Lam
Tak-Wah Lam received his PhD in Computer Science from the University of Washington. His current research is in the areas of algorithms and bioinformatics. Apart from theoretical work, he is active in working together with the genomics industry to advance the software for NGS data analysis. The most recent software, called MEGAHIT, is targeted to assemble large volume of metagenomics data in a memory-and-time efficient manner.
Alessandro Frigeri
My research interest focuses on Planetary Science, Geoinformatics, and Geophysical data acquisition (both in the field and from remote sensing instruments), processing, and comparative analysis of datasets with different data models (e.g. topography, spectral and visible imagery and radar). I use and develop GIS tools for quantitative spatial analysis in my research activity.
I'm part of Scientific Teams of instruments onboard missions to Mars (ESA's Mars Express and NASA's MRO) and asteroids belt Vesta and Ceres (NASA's Dawn).
Meeyoung Cha
Meeyoung Cha is an associate professor at Graduate School of Culture Technology in KAIST. Her research interests are in the analysis of large-scale online social networks. She received the best paper award from the Usenix/ACM SIGCOMM Internet Measurement Conference 2007 for her work on YouTube and the International Conference on Weblogs and Social Media 2012 for her work on social conventions. Her research has been featured at NYT and HBR.
Michela Quadrini
Current research is focused on Artificial Intelligence, Bioinformatics, Formal methods and Languages for the modelling, analysis and verification of Distributed Systems.
Kjiersten Fagnan
Kjiersten Fagnan joined the JGI in 2012 after completing a petascale postdoctoral fellowship at NERSC and CRD. In 2014 Fagnan became the JGI-NERSC Engagement Lead with a focus on adapting JGI workloads to run on supercomputing hardware. She is also working to understand the data-intensive nature of JGI workloads. Fagnan earned her PhD in Applied Mathematics at the University of Washington in 2010 and her BA from UC Berkeley in 2002.
Jeonghwan Gwak
Dr. Jeonghwan Gwak received his Ph.D. degree in Machine Learning and Artificial Intelligence from Gwangju Institute of Science and Technology, Gwangju, Korea in 2014. From 2002 to 2007, he worked for several companies and research institutes as a Researcher and a chief technician. From 2014 to 2016, he worked as a Postdoctoral Researcher in GIST, and from 2016 to 2017 as a Research Professor. From 2017 to 2019, he was a Research Professor in Biomedical Research Institute & Department of Radiology at Seoul National University Hospital, Seoul, Korea. From 2019, he joined Korea National University of Transportation (KNUT) as an Assistant Professor and since 2021, he is an Associate Professor. He is the Director of the Algorithmic Machine Intelligence laboratory. His current research interests include deep learning, computer vision, image and video processing, AIoT, fuzzy sets and systems, evolutionary algorithms, optimization, and relevant applications of medical and visual surveillance systems.
Cornelia Fermuller
Cornelia Fermüller’s research is in the areas of Computer Vision and Human Vision. She has studied multiple view geometry and statistics, and her work includes view-invariant texture descriptors, 3D motion and shape estimation, image segmentation, and computational explanations and predictions of optical illusions. Her recent work focuses on the integration of perception, action and high-level reasoning to develop cognitive robots that can understand and learn human manipulation actions.
Keli Xiao
Dr. Keli Xiao is an Associate Professor in the College of Business at Stony Brook University. He received his Ph.D. from Rutgers University. Dr. Xiao’s research interests include business analytics, data mining, real estate/urban computing, economic bubbles and crises, and asset pricing. His research has appeared in many high-quality journals and conference proceedings, such as IEEE Transactions on Knowledge and Data Engineering (TKDE), Real Estate Economics, ACM Transactions on Knowledge Discovery from Data (TKDD), ACM Transactions on Management Information Systems (TMIS), ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), etc. He regularly serves as an SPC or PC of numerous prestigious conferences, such as AAAI, IJCAI, KDD, ICDM, SDM, CIKM, etc.. He is a senior member of the IEEE and the ACM.
Biju Issac
Dr Biju Issac is a Computer Science academic staff working at Northumbria University, UK. He has done PhD in Networking and Mobile Communications, MCA (Master of Computer Applications) and BE (Electronics and Communications Engineering). He is a Chartered Engineer (CEng), Senior IEEE member and Fellow of HEA. His research interests are in Wireless Networks, Cybersecurity, AI/Machine Learning applications (security, image processing, text mining etc) and Bio-inspired metaheuristic algorithms. His personal research website: https://www.bijuissac.com/
Cunhua Pan
Cunhua Pan received his B.S. and Ph.D. degrees from the School of Information Science and Engineering, Southeast University, Nanjing, China, in 2010 and 2015, respectively. From 2015 to 2016, he was a Research Associate at the University of Kent, U.K. He held a post-doctoral position at Queen Mary University of London, U.K., from 2016 and 2019, where he is currently a Lecturer.
His research interests mainly include intelligent reflection surface (IRS), machine learning, UAV, Internet of Things, and mobile edge computing.
He serves as a TPC member for numerous conferences, such as ICC and GLOBECOM, and the Student Travel Grant Chair for ICC 2019. He also serves as an Editor of IEEE Wireless Communication Letters, IEEE Communications Letter and IEEE Access.
Feiping Nie
Feiping Nie's research interests are machine learning and its application. He has published more than 100 papers in the following journals and conferences: TPAMI, IJCV, TIP, TNNLS/TNN, TKDE, TKDD, TVCG, TCSVT, TMM, TSMCB/TC, Machine Learning, Pattern Recognition, Medical Image Analysis, Bioinformatics, ICML, NIPS, KDD, IJCAI, AAAI, ICCV, CVPR, SIGIR, ACM MM, ICDE, ECML/PKDD, ICDM, MICCAI, IPMI, RECOMB. According to Google scholar, his papers have been cited more than 2000 times.
Christoph Csallner
My main research interests are in software engineering, especially in program analysis and automated testing.