Saiprasad Ravishankar - Michigan State University, USA

Saiprasad Ravishankar is currently an Assistant Professor in the Departments of Computational Mathematics, Science and Engineering, and Biomedical Engineering at Michigan State University. He received the B.Tech. degree in Electrical Engineering from IIT Madras, India, in 2008, and the M.S. and Ph.D. degrees in Electrical and Computer Engineering in 2010 and 2014 respectively, from the University of Illinois at Urbana-Champaign, where he was then an Adjunct Lecturer and a Postdoctoral Research Associate. Since August 2015, he was a postdoc in the Department of Electrical Engineering and Computer Science at the University of Michigan, and then a Postdoc Research Associate in the Theoretical Division at Los Alamos National Laboratory from August 2018 to February 2019. His interests include signal and image processing, biomedical and computational imaging, machine learning, inverse problems, and large-scale data processing and optimization. He has received multiple awards including the Sri Ramasarma V Kolluri Memorial Prize from IIT Madras and the IEEE Signal Processing Society Young Author Best Paper Award for 2016 for his paper "Learning Sparsifying Transforms" published in the IEEE Transactions on Signal Processing. A paper he co-authored won a best student paper award at the IEEE International Symposium on Biomedical Imaging (ISBI) 2018, and other papers were award finalists at the IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2017 and ISBI 2020. He is currently a member of the IEEE Computational Imaging Technical Committee. He has organized special sessions or workshops on computational imaging themes at the Institute for Mathematics and its Applications (IMA), the IEEE Image, Video, and Multidimensional Signal Processing (IVMSP) Workshop 2016, MLSP 2017, ISBI 2018, and the International Conference on Computer Vision (ICCV) 2019.

Bihan Wen - Nanyang Technological University, Singapore

Bihan Wen is currently a Nanyang Assistant Professor at Nanyang Technological University. He received the B.Eng. degree in Electrical and Electronic Engineering (EEE) from Nanyang Technological University (NTU), Singapore, in 2012, the MS and PhD degrees in Electrical and Computer Engineering from University of Illinois at Urbana-Champaign (UIUC), USA, in 2015 and 2018, respectively. His research interests span areas of machine learning, computational imaging, computer vision, image and video processing, and big data applications.

He is a member of the IEEE Computational Imaging (CI) Technical Committee. He regularly serves as the area chair for ICIP and ICASSP, and serves on the program committee members for top computer vision and machine learning conferences (e.g., CVPR, ICCV, ICML, NeurIPS, IJCAI, AAAI). He also co-organized the LCI workshop @ ICCV 2019, CSLSC 2017 and MIPR 2019. He was the recipient of the 2016 Yee Fellowship, and the 2012 Professional Engineers Board (PEB) Gold Medal, Singapore. A paper he co-authored won the best paper runner-up award at the IEEE International Conference on Multimedia and Expo (ICME) 2020, and another paper he co-authored won the top 10% best paper award at the IEEE International Conference on Image Processing (ICIP) 2014.

Raja Giryes - Tel Aviv University, Israel

Raja Giryes is an assistant professor in the school of electrical engineering at Tel Aviv University. He received the B.Sc (2007), M.Sc. (supervision by Prof. M. Elad and Prof. Y. C. Eldar, 2009), and Ph.D. (supervision by Prof. M. Elad 2014) degrees from the Department of Computer Science, The Technion - Israel Institute of Technology, Haifa. Raja was a postdoc at the computer science department at the Technion (Nov. 2013 till July 2014) and at the lab of Prof. G. Sapiro at Duke University, Durham, USA (July 2014 and Aug. 2015). His research interests lie at the intersection between signal and image processing and machine learning, and in particular, in deep learning, inverse problems, sparse representations, computational photography, and signal and image modeling. Raja received the EURASIP best P.hD. award, the ERC-StG grant, Maof prize for excellent young faculty (2016-2019), VATAT scholarship for excellent postdoctoral fellows (2014-2015), Intel Research and Excellence Award (2005, 2013), the Excellence in Signal Processing Award (ESPA) from Texas Instruments (2008) and was part of the Azrieli Fellows program (2010-2013). He has organized workshops and tutorials on deep learning theory in various conferences including ICML, CVPR, and ICCV. He serves as a consultant in various high-tech companies including Innoviz technologies. A computational imaging technology he has developed at Tel Aviv University together with Prof. David Mendelovic serves as the basis for the MultiVu technologies startup that he has co-founded in 2019.

Zhizhen (Jane) Zhao - University of Illinois at Urbana-Champaign, USA

Zhizhen Zhao is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. She joined University of Illinois in 2016. From 2014 to 2016, she was a Courant Instructor at the Courant Institute of Mathematical Sciences, New York University. She received the B.A. and M.Sc. degrees in physics from Trinity College, Cambridge University in 2008, and the Ph.D. degree in physics from Princeton University in 2013. She is a recipient of Alfred P. Sloan Research Fellowship (2020--2022). Her research interests include applied and computational harmonic analysis, signal processing, and computational imaging.

Jong Chul Ye - Korea Advanced Institute of Science and Technology, Korea

Jong Chul Ye is currently KAIST Endowed Chair Professor and Professor of the Dept. of Bio/Brain Engineering and Adjunct Professor at Dept. of Mathematical Sciences of Korea Advanced Institute of Science and Technology (KAIST), Korea. He received the B.Sc. and M.Sc. degrees from Seoul National University, Korea, and the Ph.D. from Purdue University, West Lafayette. Before joining KAIST, he worked at Philips Research and GE Global Research in New York. He has served as an associate editor of IEEE Trans. on Image Processing, and an editorial board member for Magnetic Resonance in Medicine. He is currently an associate editor for IEEE Trans. on Medical Imaging, IEEE Trans. on Computational Imaging, and Journal of Electronic Imaging, and an international advisory board member for Physics in Medicine and Biology. He is also a Senior Editor of IEEE Signal Processing Magazine. He is an elected member of IEEE SPS Technical Committee on Bio-imaging and Signal Processing (BISP), IEEE EMBS Technical Committee on Biomedical Imaging and Image Processing (BIIP), and IEEE SPS Special Interest Group (SiG) on Computational Imaging, and a Technical Liaison Committee of IEEE Trans. on Computational Imaging. He is/was on the organizing committee for IEEE Symp. on Biomedical Imaging (ISBI) 2006, 1st ISMRM Workshop on Machine Learning 2018, and International BASP Frontiers Workshop 2019. He is/was a tutorial/keynote/plenary speaker in various conferences including ISBI, ISMRM, SPIE Medical Imaging, CT Meeting, MICCAI Workshop, IFMIA, etc. His group was the first place winner of the 2009 Recon Challenge at the ISMRM workshop with k-t FOCUSS algorithm, the second winners at 2016 Low Dose CT Grand Challenge organized by the American Association of Physicists in Medicine (AAPM) with the world’s first deep learning algorithm for low-dose CT, and the third place winner for 2017 CVPR NTIRE challenge on example-based single image super-resolution. He was an advisor of student’s best paper awards (1st, and runner-up) at 2013 and 2016 IEEE Symp. on Biomedical Imaging (ISBI). His current research interests include machine learning, compressed sensing and statistical signal processing for various image reconstruction problems in various medical and bioimaging modalities such as MRI, CT, optics, ultrasound imaging, PET, fNIRS, etc.