Calendar

A two-day conference on the philosophy of deep learning, organized by Ned Block (New York University), David Chalmers (New York University) and Raphaël Millière (Columbia University), and jointly sponsored by the Presidential Scholars in Society and Neuroscience program at Columbia University and the Center for Mind, Brain, and Consciousness at New York University.

About

The conference will explore current issues in AI research from a philosophical perspective, with particular attention to recent work on deep artificial neural networks. The goal is to bring together philosophers and scientists who are thinking about these systems in order to gain a better understanding of their capacities, their limitations, and their relationship to human cognition.

The conference will focus especially on topics in the philosophy of cognitive science (rather than on topics in AI ethics and safety). It will explore questions such as:

• What cognitive capacities, if any, do current deep learning systems possess?
• What cognitive capacities might future deep learning systems possess?
• What kind of representations can we ascribe to artificial neural networks?
• Could a large language model genuinely understand language?
• What do deep learning systems tell us about human cognition, and vice versa?
• How can we develop a theoretical understanding of deep learning systems?
• How do deep learning systems bear on philosophical debates such as rationalism vs empiricism and classical vs. nonclassical views of cognition.
• What are the key obstacles on the path from current deep learning systems to human-level cognition?

A pre-conference debate on Friday, March 24th will tackle the question “Do large language models need sensory grounding for meaning and understanding ?”. Speakers include Jacob Browning (New York University), David Chalmers (New York University), Yann LeCun (New York University), and Ellie Pavlick (Brown University / Google AI).

Conference speakers

• Cameron Buckner (University of Houston)
• Rosa Cao (Stanford University)
• Ishita Dasgupta (DeepMind)
• Nikolaus Kriegeskorte (Columbia University)
• Brenden Lake (New York University / Meta AI)
• Grace Lindsay (New York University)
• Tal Linzen (New York University / Google AI)
• Raphaël Millière (Columbia University)
• Nicholas Shea (Institute of Philosophy, University of London)

Call for abstracts

We invite abstract submissions for a few short talks and poster presentations related to the topic of the conference. Submissions from graduate students and early career researchers are particularly encouraged. Please send a title and abstract (500-750 words) to phildeeplearning@gmail.com by January 22nd, 2023 (11.59pm EST).

https://philevents.org/event/show/106406

The International Conference on Brain Informatics (BI) series has established itself as the world’s premier research conference on Brain Informatics, which is an emerging interdisciplinary and multidisciplinary research field that combines the efforts of Cognitive Science, Neuroscience, Machine Learning, Data Science, Artificial Intelligence (AI), and Information and Communication Technology (ICT) to explore the main problems that lie in the interplay between human brain studies and informatics research.

The 16th International Conference on Brain Informatics (BI’23) provides a premier international forum to bring together researchers and practitioners from diverse fields for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences on brain Informatics research, brain-inspired technologies and brain/mental health applications.

The key theme of the conference is “Brain Science meets Artificial Intelligence“.

The BI’23 solicits high-quality original research and application papers (both full paper and abstract submissions). Relevant topics include but are not limited to:

• Track 1: Cognitive and Computational Foundations of Brain Science
• Track 2: Human Information Processing Systems
• Track 3: Brain Big Data Analytics, Curation and Management
• Track 4: Informatics Paradigms for Brain and Mental Health Research
• Track 5: Brain-Machine Intelligence and Brain-Inspired Computing

Keynote Speakers

Professor Emery N. Brown

MIT, Massachusetts General Hospital, USA

Profile: Emery Neal Brown is the Warren M. Zapol Professor of Anesthesia at Harvard Medical School and at Massachusetts General Hospital (MGH), and a practicing anesthesiologist at MGH. At MIT he is the Edward Hood Taplin Professor of Medical Engineering and professor of computational neuroscience, the Associate Director of the Institute for Medical Engineering and Science, and the Director of the Harvard–MIT Program in Health Sciences and Technology. Brown is one of only 19 individuals who has been elected to all three branches of the National Academies of Sciences, Engineering, and Medicine, as well as the first African American and the first anesthesiologist to be elected to all three National Academies.

Professor Bin He

Carnegie Mellon University, USA

Profile: Bin He is the Trustee Professor of Biomedical Engineering, Professor of the Neuroscience Institute, and Professor by courtesy of Electrical and Computer Engineering at Carnegie Mellon University. Dr. He has made significant research and education contributions to the field of neuroengineering and biomedical imaging, including functional biomedical imaging, noninvasive brain-computer interface (BCI), and noninvasive neuromodulation. His pioneering research has helped transforming electroencephalography from a 1-dimensional detection technique to 3-dimensional neuroimaging modality. His lab demonstrated for the first time for humans to fly a drone and control a robotic arm just by thinking about it using a noninvasive BCI. He is an elected Fellow of International Academy of Medical and Biological Engineering (IAMBE), American Institute of Medical and Biological Engineering (AIMBE), Biomedical Engineering Society (BMES), and IEEE. Dr. He served as a Past President of the IEEE Engineering in Medicine and Biology Society, the Editor-in-Chief of IEEE Transactions on Biomedical Engineering from 2013-2018, the Chair of the International Academy of Medical and Biological Engineering from 2018-2021. Dr. He has been a Member of NIH BRAIN Initiative Multi-Council Working Group from 2014-2019.

Professor John Ngai

NIH BRAIN Initiative, USA

Profile: John J. Ngai, Ph.D., is the Director of the NIH’s Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) Initiative. Dr. Ngai earned his bachelor’s degree in chemistry and biology from Pomona College, Claremont, California, and Ph.D. in biology from the California Institute of Technology (Caltech) in Pasadena. He was a postdoctoral researcher at Caltech and at the Columbia University College of Physicians and Surgeons before starting his faculty position at the University of California at Berkeley. During more than 25 years as a Berkeley faculty member, Dr. Ngai has trained 20 undergraduate students, 24 graduate students and 15 postdoctoral fellows in addition to teaching well over 1,000 students in the classroom. His work has led to the publication of more than 70 scientific articles in some of the field’s most prestigious journals and 10 U.S. and international patents. Dr. Ngai has received many awards including from the Sloan Foundation, Pew Charitable Trusts, and McKnight Endowment Fund for Neuroscience. As a faculty member, Dr. Ngai has served as the director of Berkeley’s Neuroscience Graduate Program and Helen Wills Neuroscience Institute. He has also provided extensive service on NIH study sections, councils and steering groups, including as previous co-chair of the NIH BRAIN Initiative Cell Census Consortium Steering Group. Dr. Ngai oversees the long-term strategy and day-to-day operations of the NIH BRAIN Initiative as it strives to revolutionize our understanding of the brain in both health and disease.

Professor Helen Mayberg

Icahn School of Medicine at Mount Sinai, USA

Profile: Helen Mayberg is a neurologist recognized for her neuroimaging studies of brain circuits in depression and their translation to the development of deep brain stimulation as a novel therapeutic for treatment resistant patients. Born and raised in Southern California, she received a BA in Psychobiology from UCLA and a MD from the University of Southern California, then trained in Neurology at Columbia’s Neurological Institute in New York and did a research fellowship in nuclear medicine at Johns Hopkins. She had early academic appointments at Johns Hopkins and the University of Texas Health Sciences Center in San Antonio, held the inaugural Sandra Rotman Chair in Neuropsychiatry at the University of Toronto, the first Dorothy C. Fuqua Chair in Psychiatric Imaging and Therapeutics at Emory University and is now the Mount Sinai Professor of Neurotherapeutics at the Icahn School of Medicine where she is founding Director of the Nash Family Center for Advanced Circuit Therapeutics. She is a member of the both the National Academy of Sciences and the National Academy of Medicine as well as the National Academy of Inventors and American Academy of Arts and Sciences.

Professor Vinod Goel

York University, Canada

Profile: Vinod Goel is a professor of cognitive neuroscience at York University, Toronto, Canada. He completed his PhD in cognitive science at UC-Berkeley, and received postdoctoral training in neuroscience at the NIH (NINDS) and the Wellcome Department of Cognitive Neurology, Institute of Neurology, UCL, UK. He has made significant empirical contributions to our understanding of the roles of prefrontal cortex in real-world problem solving and reasoning, hemispheric asymmetry in prefrontal cortex, and models of rationality, using the methodologies of fMRI and lesion studies. He has most recently completed a book reconstructing the role of rationality in human behavior entitled “Reason and Less: Pursuing Food, Sex, and Politics” (The MIT Press, 2022). His current project is to explore the implications of this work on our understanding of reason and legal responsibility.

Professor Amy Kuceyeski

Cornell University, USA

Profile: Amy Kuceyeski is an Associate Professor of Mathematics and Neuroscience in Radiology at Weill Cornell Medicine and the Computational Biology Department at Cornell University. She is the director of the Computational Connectomics (CoCo) Laboratory and the Machine Learning in Medicine group at Cornell. Over the past 14 years, she has been working to understand the human brain using quantitative modeling approaches, including machine learning, to map anatomical and physiological characteristics to behavior. Specifically, she is interested in understanding how brains recover from injury so we can devise strategies, possibly via non-invasive neuromodulation, to support natural recovery processes. She also performs research at the intersection of biological and artificial neural networks that aims to understand how human brains process incoming visual information.

Professor Patrick Purdon

Harvard Medical School, USA

Profile: Patrick L. Purdon, Ph.D., is an Associate Professor of Anaesthesia at Harvard Medical School and the Nathaniel M. Sims Endowed Chair in Anesthesia Innovation and Bioengineering at Massachusetts General Hospital.  Dr. Purdon received his A.B. in Engineering Sciences from Harvard College in 1996, his M.S. in Electrical Engineering from MIT in 1998, and his Ph.D. in Biomedical Engineering from MIT in 2005.  Dr. Purdon’s research in neuroengineering encompasses the mechanisms of anesthesia, Alzheimer’s disease and brain health, anesthesia and the developing brain, neural signal processing, and the development of novel technologies for brain monitoring. He has published over 90 peer-reviewed publications, is an inventor on 16 pending patents, and is a Fellow of the American Institute for Medical and Biological Engineering.  Dr. Purdon has won numerous awards, including the prestigious National Institutes of Health Director’s New Innovator Award.

Important Dates

• 15 April 2023: Full paper submission deadline

• 20 April 2023: Workshop proposal deadline

• 10 May 2023: Abstract presentation submission deadline

• 30 May 2023: Final paper and abstract acceptance notification

• 20 Jun 2023: Accepted paper and abstract registration deadline

• 1-3 Aug 2023: The Brain Informatics Conference

Paper Submission and Publications

Full Paper (Regular):

1. 9-12 pages are strongly encouraged for the regular papers including figures and references in Springer LNCS Proceedings format(https://www.springer.com/us/computer-science/lncs/conference-proceedings-guidelines). Over length papers will be charged for 100$ per page.
2. All papers will be peer-reviewed and accepted based on originality, significance of contribution, technical merit, and presentation quality.
3. All papers accepted (and all workshop & special sessions’ full-length papers) will be published by Springer as a volume of the Springer-Nature LNAI Brain Informatics Book Series(https://link.springer.com/conference/brain).

Abstract (Only for Workshops/Special Sessions):

Research abstracts are encouraged and will be accepted for presentations in an oral presentation format and/or poster presentation format. Each abstract submission should include the title of the paper and an abstract body within 500 words. The abstract will not be included in the conference proceedings to be published by Springer.

Journal Opportunities:

High-quality BI conference papers will be nominated for a fast-track review and publication at the Brain Informatics Journal, (https://braininformatics.springeropen.com/) an international, peer-reviewed, interdisciplinary Open Access journal published by Springer Nature. Discount or no open access article-processing fee will be charged for BI conference paper authors.

Special Issues & Books Opportunities:

Workshop/special session organizers and BI conference session chairs may consider and can be invited to prepare a book proposal of special topics for possible book publication in the Springer-Nature Brain Informatics & Health Book Series (https://www.springer.com/series/15148), or a special issue at the Brain Informatics Journal.

Poster-Conference Publication

1. Accepted full papers will be selected to publish in the Brain Informatics Journal upon revision.

2. Discount or no article-processing fee will be charged for authors of Brain Informatics conference (https://braininformatics.springeropen.com/).

3. The organizers of Workshops and Special-Sessions are invited to prepare a book proposal based on the topics of the workshop/special session for possible book publication in the Springer-Nature Brain Informatics and Health book series (http://www.springer.com/series/15148).

https://philevents.org/event/show/109301