BOOM 2018 : 3rd IJCAI International Workshop on Biomedical infOrmatics with Optimization and Machine learning (BOOM)
Call For Papers
On behalf of the organizing committee we invite submissions of technical papers and abstracts for the 3rd International Workshop on Biomedical Informatics with Optimization and Machine Learning (BOOM), in conjunction with the Federated AI Meeting of AAMAS, ICML, and IJCAI (FAIM) which will be held in Stockholm from July 10-19, 2018. We welcome submissions with important new theories, methods, applications, and insights at the intersection of artificial intelligence, machine learning, optimization, and biomedical informatics.
The BOOM workshop aims at catalyzing synergies among biomedical informatics, artificial intelligence, machine learning, and optimization. This workshop is targeting an audience of applied mathematicians, computer scientists, industrial engineers, bioinformaticians, computational biologists, clinicians and healthcare researchers who are interested in exploring the emerging and fascinating interdisciplinary topics. It is designed to foster exchange of ideas between often-disparate groups that are unaware of each other's research, and to stimulate fruitful collaborations among different disciplines. In the past, BOOM has been held twice in conjunction with IJCAI (2016, 2017), featured keynote speakers from academia, federal agency, medical practice, and corporates, successfully attracted a broad audience, and published two journal special issues for accepted long articles.
The BOOM Workshop solicits the following submissions.
1. Full papers that describe original research work that have not been published before, which will be published in a special issue of a reputed partner journal (under negotiation).
For reference, full papers from past BOOM have been published in special issues of EURASIP Journal on Advances in Signal Processing (JASP), 2017; and EURASIP Journal on Bioinformatics and Systems Biology (JBSB), 2016.
More details for submission and format of full papers will be announced soon at https://www.ijcai-boom.org/.
Full paper authors are also highly encouraged to submit short abstracts simultaneously through email to: ijcai1boom (AT) gmail (DOT) com for the consideration of workshop presentations.
2. Short abstracts that either highlight significant works that have been published or accepted recently or report unpublished research findings, which will be included in workshop online proceedings (unarchived). Please format short abstracts according to IJCAI latex & word templates at http://ijcai-16.org/downloads/FormattingGuidelinesIJCAI-16.zip, with the page limit of 2 pages including references; and submit through email to: ijcai1boom (AT) gmail (DOT) com.
This year, BOOM will open up a new opportunity: for selected high-quality full paper and short abstracts, we will invite their authors to co-contribute a chapter in an ongoing book, which expects to be published by Elsevier earlier next year.
Both full and short submissions will be considered for oral and poster presentations at BOOM. The decision on presentation format for accepted submissions will be based primarily on an assessment of breadth of interest, and the construction of balanced and topically coherent sessions, while full papers will be given some priority for oral presentations.
Following past BOOM, we will continue to give out two best paper awards (long and short).
The following dates are for short abstracts. Full paper and book chapter submission details will be announced at https://www.ijcai-boom.org/submission.html
Abstract submission due: May 20, 2018
Abstract notification: June 1, 2018
Camera-ready due: June 15, 2018
List of Topics
We encourage submissions on topics including, but not limited to, the following inter-linked ones:
Category I: Machine Learning and Optimization Algorithms
Developing and applying cutting-edge machine learning (e.g., deep learning) and optimization (e.g., large-scale optimization) techniques to tackle real-world medical and healthcare problems.
Addressing challenges and roadblocks in biomedical informatics with reference to the data-driven machine learning, such as imbalanced dataset, weakly-structured or unstructured data, noisy and ambiguous labeling, and more.
Designing novel, applicable numerical optimization algorithms for biomedical data, that is usually large-scale, high-dimensional, heterogeneous, and noisy.
Re-visiting traditional machine learning topics such as clustering, classification, regression and dimension reduction, that find application values in newly-emerging biomedical informatic problems.
Other closely-related disciplines, such as image processing, data mining, new computing technologies and paradigms (e.g., cloud computing), control theory, and system engineering.
Category II: Biomedical Informatics Applications
Computational Biology, including the advanced interpretation of critical biological findings, using databases and cutting-edge computational infrastructure.
Clinical Informatics, including the scenarios of using computation and data for health care, spanning medicine, dentistry, nursing, pharmacy, and allied health.
Public Health Informatics, including the studies of patients and populations to improve the public health system and to elucidate epidemiology.
mHealth Applications, including the use of mobile apps and wearable sensors for health management and wellness promotion.
Cyber-Informatics Applications, including the use of social media data mining and natural language processing for clinical insight discovery and medical decision making.
Chen Wang (Assistant Professor, Mayo College of Medicine/Mayo Clinic)
Dukka KC (Assistant Professor, North Carolina A&T State University)
Hongfang Liu (Associate Professor, Mayo College of Medicine/Mayo Clinic)
Hongzhi Li (Research SDE, Microsoft Research)
Huan Sun (Assistant Professor, Ohio State University)
Gaurav Pandey (Assistant Professor, Mount Sinai School of Medicine)
Jian Ma (Associate Professor, Carnegie Mellon University)
Jianyang Zeng (Assistant Professor, Tsinghua University)
Jiebo Luo (Professor, University of Rochester)
Jieping Ye (Associate Professor, University of Michigan)
Jinbo Xu (Associate Professor, Toyota Technological Institute at Chicago)
Jingyi Fei (Assistant Professor, University of Chicago)
Linli Xu (Associate Professor, University of Science and Technology of China)
Or Zuk (Assistant Professor, The Hebrew University of Jerusalem)
Peng Qiu (Assistant Professor, Georgia Institute of Technology)
Qi Wang (Associate Professor, Northwestern Polytechnical University)
Qing Ling (Associate Professor, University of Science and Technology of China)
Shaoting Zhang (Assistant Professor, University of North Carolina at Charlotte)
Shiyu Chang (Research Staff Member, IBM Thomas J. Watson Research Center)
Shuiwang Ji (Associate Professor, Washington State University)
Tongliang Liu (Lecturer, University of Technology Sydney)
Xi Peng (Research Scientist, A*STAR Singapore)
Xia Ben Hu (Assistant Professor, Texas A&M University)
Xin Gao (Assistant Professor, King Abdullah University of Science and Technology)
Xinchao Wang (Postdoctoral Fellow, University of Illinois at Urbana–Champaign)
Xinghua Mindy Shi (Assistant Professor, University of North Carolina at Charlotte)
Xuesong Yang (Ph.D. candidate, University of Illinois at Urbana–Champaign)
Yao Xie (Assistant Professor, Georgia Institute of Technology)
Yang Shen (Assistant Professor, Texas A&M University)
Zhangyang (Atlas) Wang (Assistant Professor, Texas A&M University)
Shuai Huang (Assistant Professor, University of Washington)
Jiayu Zhou (Assistant Professor, Michigan State University)
Qing Ling (Assistant Professor, Sun Yat-Sen University, China)
The 1-day workshop will be held in conjunction with the Federated AI Meeting of AAMAS, ICML, and IJCAI (FAIM) which will be held in Stockholm, Sweden, July 10-19, 2018. The joint AAMAS-ICML-IJCAI workshops including BOOM will be held July 13-15, 2018.
All questions about submissions should be emailed to ijcai1boom (AT) gmail (DOT) com