Empowering student researchers in medical imaging through collaborative dialogue and mentorship at the EMERGE workshop.
We want to foster the educational and professional development needs of early-career researchers and support them in their journey to become independent investigators and mentors. This workshop, organized by students for students, encourages early-career researchers - maximum two years post Ph.D. - to be primary investigators and occupy the first and last author positions on an 8-page paper. These papers will be published in Springer's LNCS format, and the most outstanding contributions will be invited to expand their work for potential publication in MELBA.
Note: Young scientists as last authors preferred but not required. We also welcome joint co-last author, and first author papers by young scientists irrespective of last author status.
The EMERGE workshop is an exciting new event at the MICCAI 2024 conference, offering a platform for early-career researchers within
the MICCAI community to showcase their work. The workshop is tailored to projects where students have a leading role in the research
project, encouraging early-career researchers as the main researchers.
This workshop is a student-led initiative, organized by the MICCAI Student Board, with a panel of experienced researchers
from the MICCAI community. The workshop is an opportunity for students to get feedback from our experienced panel, who will actively engage
with student presentations at the workshop. This student-led initiative reflects a commitment to empowering the next generation of
researchers, providing them with an opportunity to present and discuss their ongoing projects - fostering constructive feedback and
meaningful scientific discourse. Our workshop aims to highlight works from students from around the world, with a special focus on
those in underrepresented regions, including Morocco and other African nations.
The scope of the workshop spans the areas of Medical Image Computing (MIC) and Computer-Assisted Interventions (CAI), aligned with the
scientific focus of the MICCAI Society. We encourage the development and implementation of advanced algorithms to solve a variety of
problems in medical imaging, encompassing a spectrum of imaging modalities, including MRI, ultrasound, X-ray, microscopy, OCT, nuclear
medicine, among others. The event is welcome to students at the undergraduate, master's, and doctoral levels - with an emphasis on works
where the student is the primary contributor.
The EMERGE workshop will be held on 6 October 2024 as an in-person, half day satellite event of MICCAI 2024 at the
Palmeraie Conference Centre in Marrakesh, Morocco. This in-person format allows for early-stage research discussions and student networking,
providing an environment conducive to meaningful exchanges and collaborations. The workshop will conclude with an awards ceremony recognizing
outstanding presentations and research works. In addition to these sessions, two successful early-career independent researchers will deliver
keynote speeches, offering insights into career development paths within the field and an education-focused talk on effective approaches to impactful
research.
Submissions are double-blind reviewed and must adhere to the following guidelines: maximum paper length: 8 pages (text, figures, and tables) and additional 2 pages allowed for references. Details on the template for the paper can be found here . Accepted papers will be published in an LNCS volume by Springer Nature.
The manuscripts can be submitted at https://openreview.net/group?id=MICCAI.org/2024/Workshop/MSB.
Instructions for Camera-Ready Submission
Please submit a PDF version of your paper. Additionally, you will need to submit the following doucments: (i) source files (LaTeX, Word, etc.), (ii) duly signed License to Publish document by one of the authors, and (iii) a separate pdf document outlining the changes made to your paper based on reviewer feedback.
Camera-Ready Submission Guidelines
- Page Limit: The submitted manuscript should be a maximum of 9 pages, plus an additional 2 pages for references. The overall paper length must not exceed 11 pages (including appendix and references).
- Paper Number: Please use your two-digit OpenReview submission number for your paper (e.g., use "01" for submission number 1).
- License to Publish: You can find the appropriate form on: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines. Please be sure to use the following title for the proceedings when completing the License to Publish form: "Medical Information Computing, MImA 2024 + MSB EMERGE 2024 (MICCAI Workshops)".
- ORCID IDs: We request all authors to include their ORCID IDs in the publication. You can find more information about ORCID IDs here: http://bit.ly/2H5xBpN.
Please update your submission on OpenReview by August 30th, 2024. You can do this by editing your original submission and selecting "Camera Ready Version." The system will allow you to update the following fields: Title, Keywords, TL;DR, Abstract, and Camera-Ready ZIP submission (containing your paper, source code, license, and changes document).
All dates are in 23:59 Pacific Time Zone (PT)
May 6, 2024 |
Call for Papers |
June 1, 2024 |
Submission Portal Open |
June 24, 2024 July 1, 2024 |
Paper Submission Deadline |
July 9, 2024 |
Reviews released to the authors |
July 13, 2024 |
Rebuttals due |
July 15, 2024 |
Final Decision |
August 30, 2024 |
Camera Ready Submission |
Mathias Unberath
Mathias Unberath is the John C. Malone Associate Professor in the Department of Computer Science with secondary appointments in the Departments of Ophthalmology and Otolaryngology—Head and Neck Surgery at the School of Medicine. He is also a core faculty member of the Laboratory for Computational Sensing and Robotics (LCSR) and the Malone Center for Engineering in Healthcare and an affiliate faculty member in the Institute for Assured Autonomy.
With his group, the Advanced Robotics and Computationally AugmenteD Environments (ARCADE) Lab, Unberath builds the future of computer-assisted medicine. Through synergistic research on imaging, computer vision, machine learning, and interaction design, he invents human-centered solutions that are embodied in emerging technologies such as mixed reality and robotics.
He has published more than 150 journal and conference articles and has received numerous awards, grants, and fellowships, including the National Institute of Biomedical Imaging and Bioengineering Trailblazer R21 Award, an NSF CAREER Award, a Google Research Scholar Award, a Johns Hopkins Career Impact Award, and an inaugural Johns Hopkins Data Science and AI Institute Junior Faculty Award.
While completing a bachelor’s in physics and master’s in optical technologies at the Friedrich-Alexander University of Erlangen-Nürnberg (FAU), Unberath also studied at the University of Eastern Finland as an Erasmus Mundus scholar in 2011 and joined Stanford University as a DLR-DAAD fellow in 2014. He received his PhD in computer science from FAU and graduated summa cum laude in 2017. Prior to joining as faculty, Unberath was an assistant research professor in the department and a postdoctoral fellow at LCSR.
Time |
Speaker and Title |
08:00 - 08:15 |
Opening Remarks and Introduction |
08:15 - 09:15 |
Oral Session 1: (3 presenters each 15min + 5min Q&A each) |
09:15 - 10:00 |
Keynote Talk: Mathias Unberath |
10:00 - 10:30 |
Break |
10:30 - 12:10 |
Oral Session 2: (5 presenters each 15min + 5min Q&A each) |
12:10 - 12:30 |
Closing Remarks and Awards |
TBD |
Closing |
Naren Akash
IIIT Hyderabad
Website
Moritz Fuchs
Technical University of Darmstadt
Website
Amar Kumar
McGill University
Website
Ahmed Nebli
Forschungszentrum Juelich
Website
Anna Zapaishchykova
Brigham and Women's Hospital
Website
Yanis Najy Miracoui
Standford University
Website
Weina Jin
Simon Fraser University
Website
Harry Anthony
University of Oxford
Website
Amin Ranem
Technical University of Darmstadt
Website
Advaith Veturi
University of Colorado Anschutz Medical Campus
Website
Paul Wilson
Queen's University
Website
Benjamin Killeen
Johns Hopkins University
Website
Constantin Ulrich
German cancer Research Center (DKFZ)
Website
Camila Gonzalez
Stanford University
Website
Antonio R. Porras
University of Colorado Anschutz Medical Campus
Website
Anees Kazi
Massachusetts General Hospital, Harvard Medical School
Website
Aisha Urooj, Mayo Clinic, USA
Arman Gorji, Hamadan University of Medical Science, Iran
Balamurali Murugesan, ETS Montreal, Canada
Berardino Barile, McGill University, Canada
Camila Gonzalez, Stanford University, USA
Divyanshu Tak, Harvard Medical School, USA
Fabian Gröger, University of Basel, Switzerland
Fahad Shamshad, Mohamed Bin Zayed University of Artificial Intelligence, UAE
Favour Nerrise, Stanford University, USA
Henry John Krumb, TU Darmstadt, Germany
Kumar Abhishek, Simon Fraser University, Canada
Magdalini Paschali, Stanford University, USA
Mirko Konstantin, TU Darmstadt, Germany
Pramit Saha, University of Oxford, UK
Raghav Mehta, Imperial College London, UK
Roa'a Al-Emaryeen, University of Jordan, Jordan
Roger David Soberanis-Mukul, Johns Hopkins University, USA
S. Shailja, Stanford University, USA
Samra Irshad, Kyung Hee University, South Korea
Weina Jin, Simon Fraser University, Canada
Yuhan Wang, Kings College London, UK
Ziyun Liang, University of Oxford, UK