March 2026 - Comp-neuro - lists.cnsorg.org

DeepLearn 2026: early registration March 29

by David Silva - IRDTA

****************************************************** 13th INTERNATIONAL SCHOOL ON DEEP LEARNING DeepLearn 2026 Orléans, France July 20-24, 2026 https://deeplearn.irdta.eu/2026/ ****************************************************** Co-organized by: University of Orléans Centre Val de Loire Doctoral College Institute for Research Development, Training and Advice – IRDTA Luxembourg/London ****************************************************** Early registration: March 29, 2026 ****************************************************** SCOPE: DeepLearn 2026 will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, Guimarães, Luleå, Bournemouth, Bari, and Porto. Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, biomedicine and healthcare, medical image analysis, recommender systems, advertising, fraud detection, robotics, games, business and finance, biotechnology, physics and astrophysics, biometrics, communications, climate sciences, geographic information systems, signal processing, genomics, materials design, video technology, social systems, earth and sustainability, mathematical proofs, etc. etc. The field is also raising a number of relevant questions about efficiency and robustness of the algorithms, explainability, transparency, interpretability, risks and safety, as well as important ethical concerns at the frontier of current knowledge that deserve careful multidisciplinary discussion. Most deep learning subareas will be displayed and main challenges identified through 16 four-hour and a half courses, 2 keynote lectures, 1 round table, and a hackathon competition among participants. Renowned academics and industry pioneers will lecture and share their views with the audience. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely. ADDRESSED TO: Graduates, postgraduates and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, hence people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2026 is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators. VENUE: DeepLearn 2026 will take place in Orléans, located in the heart of the Loire Valley, which was declared by UNESCO a World Heritage Site in 2000. The venue will be: University of Orléans Faculty of Law, Economics and Management 11 rue de Blois 45100 Orléans, France https://www.univ-orleans.fr/en STRUCTURE: 3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another. All lectures will be videorecorded. Participants will be able to watch them again for 45 days after the event. An open session will give participants the opportunity to present their own work in progress in 5 minutes. Also companies will be able to present their industrial developments for 10 minutes. The school will include a hackathon, where participants will be able to work in teams to tackle several machine learning challenges. Full live online participation will be possible. The organizers highlight, however, the importance of face to face interaction and networking in this kind of research training event. KEYNOTE SPEAKERS: Yingbin Liang (Ohio State University), Convergence Theory: How Fast Do Discrete Diffusion Models Generate? Le Song (Mohamed bin Zayed University of Artificial Intelligence), Towards AI-Driven Digital Organism: A System of Multiscale Foundation Models for Biology PROFESSORS AND COURSES: Nitesh Chawla (University of Notre Dame), [intermediate] Learning from Imbalanced Data Yuejie Chi (Yale University), [introductory/intermediate] Statistical and Algorithmic Foundations of Reinforcement Learning Bo Han (Hong Kong Baptist University), [introductory/intermediate] Trustworthy Machine Learning from Data to Models Jiawei Han (University of Illinois Urbana-Champaign), [intermediate] Structure-Guided, Theme-Based Knowledge Discovery with Large Language Models Mingyi Hong (University of Minnesota), [intermediate] Modern Optimization Algorithms for Large Language Models Cho-Jui Hsieh (University of California Los Angeles), [intermediate/advanced] Optimizers for Large Language Model Training Furong Huang (University of Maryland), [advanced] Generative AI Agents Tara Javidi (University of California San Diego), [intermediate] Active Physical Intelligence for Industrial Scale Monitoring Yan Liu (University of Southern California), [intermediate] Time Series Foundation Models: From Forecasting to Reasoning Zhijin Qin (Tsinghua University), [intermediate/advanced] Semantic Communications Aarti Singh (Carnegie Mellon University), [intermediate] Human Centered AI: Challenges and Opportunities Suvrit Sra (Technical University of Munich), [introductory/intermediate] Introduction to the Theory of Learning with Transformers Ivor Tsang (A*STAR Centre for Frontier AI Research), [introductory/intermediate] Long-Horizon Agentic Intelligence Ming-Hsuan Yang (University of California Merced), [advanced] Recent Advances in Multimodal Understanding and Generation Tong Zhang (University of Illinois Urbana-Champaign), [introductory/intermediate] Reinforcement Learning for Large Language Models Jun Zhu (Tsinghua University), [introductory/advanced] Generative Models: from Virtual to Physical World OPEN SESSION: An open session will collect 5-minute voluntary oral presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david(a)irdta.eu by July 12, 2026. INDUSTRIAL SESSION: A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Abstracts have to be submitted to david(a)irdta.eu by July 12, 2026. HACKATHON: A hackathon will take place, where participants can voluntarily work in teams to tackle several machine learning challenges. They will be coordinated by Professor Sergei V. Gleyzer (University of Alabama). The challenges will be released 2 weeks before the beginning of the school. A jury will judge the submissions and the winners of each challenge will be announced by the end of August 2026. The winning teams will receive a modest monetary prize and the runners-up will get a certificate. SPONSORS: Companies/institutions/organizations willing to be sponsors of the event can download the sponsorship leaflet from https://deeplearn.irdta.eu/2026/sponsors/ ORGANIZING COMMITTEE: Karim Abed-Meraim (Orléans, local co-chair) Sergei V. Gleyzer (Tuscaloosa, hackathon chair) Meryem Jabloun (Orléans, local co-chair) Carlos Martín-Vide (Tarragona, program chair) Santiago Montes (Tarragona, webpage) Sara Morales (Luxembourg, finances) Florian Nowicki (Orléans, social networks) Philippe Ravier (Orléans, local chair) David Silva (London, organization chair) REGISTRATION: It has to be done at https://deeplearn.irdta.eu/2026/registration/ The selection of 6 courses requested in the registration template is only tentative and non-binding. For logistical reasons, it will be helpful to have an estimation of the respective demand for each course. Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event. FEES: Fees comprise access to all program activities and lunches. There are several early registration deadlines. Fees depend on the registration deadline. The fees for on site and for online participation are the same. ACCOMMODATION: Accommodation suggestions are available at https://deeplearn.irdta.eu/2026/accommodation/ CERTIFICATE: A certificate of successful participation will be delivered indicating the number of hours of academic activities (40). This should be sufficient for those participants who plan to request ECTS recognition from their home university. QUESTIONS AND FURTHER INFORMATION: david(a)irdta.eu ACKNOWLEDGMENTS: Université d’Orléans Collège Doctoral Centre-Val de Loire Universitat Rovira i Virgili Institute for Research Development, Training and Advice – IRDTA, Luxembourg/London

March 7, 2026

🧠[Meetings] [CFP] IEEE SMC 2026 Workshop - NeuroWearX for Empowered Co-Intelligence: Advancing Human–Machine Interfaces by Integrating Biological, Physical, and Spatial Intelligence with Generative AI

by NeuroWearX

Call for Papers 2026 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2026) https://www.ieeesmc2026.org/ IEEE SMC Workshop: NeuroWearX for Empowered Co-Intelligence: Advancing Human–Machine Interfaces by Integrating Biological, Physical, and Spatial Intelligence with Generative AI Overview Wearables, assistive robots, and smart IoT systems are rapidly becoming part of everyday life. However, many of today’s wearable computing and human–machine interfaces still feel “smart, yet not quite helpful.” They are often fragmented, difficult to personalize, and frequently struggle to transform rich but noisy multimodal signals, such as physiology (e.g., heart rate, neural/muscle activity), body movement, and environmental context, into reliable, meaningful real-world support. At the same time, generative AI and foundation/world models are reshaping the landscape, shifting the paradigm beyond isolated sensors and single-purpose algorithms toward integrated, adaptive, context-aware Human–AI–Machine systems. To make the use of these technologies feel like a natural extension of ourselves, this workshop brings together researchers and practitioners across biosensing and measurement, neuroscience, AI, robotics, ubiquitous computing, and human-centered design to define the next frontier of Empowered Co-Intelligence: wearable interfaces that fuse three complementary “intelligences”—(1) biological intelligence, to infer human state and intent by modeling how people naturally think and behave; (2) physical/embodied intelligence, which understands body dynamics and real-world physics so interaction and assistance remain safe and effective; and (3) spatial intelligence, to leverage nearby sensors, IoT devices and smart environments for continuous situational awareness. These capabilities are further amplified by generative AI—models trained on large-scale data that can integrate heterogeneous signals to predict, reason, and adapt—enabling systems to become more personalized and context-aware. Together, these capabilities can overcome the limits of noisy on-body sensing and constrained wearable computing by turning fragmented measurements into coherent, actionable assistance. Our vision is an AI that operates quietly in the background, like an invisible layer of artificial cortex, running in parallel with our own cerebral cortex and coordinating across different lobes: not simply following rules, but learning your patterns, anticipating your needs, and adjusting in real time. The result is 24/7 support for thinking, decision-making, and physical action that feels intuitive, seamless, and requires minimal cognitive effort. Beyond new algorithms, we also emphasize human-centered evaluation, trust, accessibility, and inclusive augmentation, with the goal of accelerating research that advances wearable computing into reliable, scalable, and equitable systems—technologies that truly co-evolve with users over time. Topics of Interest We welcome research papers, short/WiP papers, and position/vision papers on (but not limited to) the following areas aligned with multimodal perception–decision–action cycles, shared autonomy, personalization, safety, and real-world robustness on wearable technologies. (A) Biological intelligence: sensing human state & intent ● Multimodal biosensing: EEG/EMG/ECG/EDA/PPG/respiration, inertial + physiological fusion ● Robust biosignal decoding in-the-wild: drift handling, motion artifacts, missing data, calibration-free methods ● Intent recognition and user-state estimation (fatigue, stress, attention, readiness, motor intent) ● Personalized adaptation across users: domain adaptation, continual learning, few-shot personalization ● Privacy-preserving on-body learning and secure biosignal pipelines (B) Physical intelligence: embodied assistance & safe action ● Embodied AI for wearable augmentation: biomechanics, dynamics, control, and safe shared autonomy ● Wearable robotics and human–robot physical interaction (exoskeletons, prostheses, assistive devices) ● Safety, stability, and fail-safe design in closed-loop wearable control ● Human factors and ergonomics for physical assistance; workload-aware support ● Verification/validation of embodied policies for assistive wearable systems (C) Spatial intelligence: context from environments, robots & smart IoT ● Context-aware wearable computing using smart environments, robots, and IoT integration ● Scene understanding for assistance: activity context, objects, layout, hazards, and social context ● Multi-device sensing orchestration (wearable + phone + AR + ambient sensors) ● Real-world robustness and interoperability across heterogeneous devices (D) Generative AI & foundation/world models for wearables ● Generative AI / foundation models for wearable time-series, biosignal representation learning, multimodal fusion ● World models for prediction, planning, and co-adaptation in human-centered wearable interaction ● Edge/on-body inference: efficiency, compression, distillation, and low-power deployment ● Uncertainty-aware assistance, reliable decision-making, and “AI-in-the-background” support (E) Human-centered NeuroDesign, evaluation & impact ● Human-centered interface design: intuitive/subconscious interaction, trust, transparency, explainability ● UX evaluation in real-world settings: accessibility, equity, inclusive augmentation ● Ethical, privacy, and governance considerations for always-on wearable intelligence ● Application domains: assistive augmentation, rehabilitation, health monitoring, everyday support Submission Instructions ● Submission deadline: March 22, 2026 ● Submission site at 2026 IEEE International Conference on Systems, Man, and Cybernetics (Papercept): https://conf.papercept.net/conferences/scripts/start.pl ● Submission code: dt3i1 (Use the submission code "dt3i1" during the Papercept submission process to route your paper to this workshop.) ● Please follow the IEEE SMC 2026 submission guidelines and formatting requirements. IEEE SMC 2026 submission guidelines: https://www.ieeesmc2026.org/call-for-papers Best regards, Organizing Committee 🧠 NeuroWearX Workshop @ IEEE SMC 2026 [image: FullLogo_Transparent_NoBuffer.png] Website: https://www.ieeesmc2026.org/Content/3015153.html Email: info.neurowearx(a)gmail.com

March 6, 2026

WashU CTCN Postdoc Fellows

by Goodhill, Geoffrey

POSTDOCTORAL FELLOWSHIPS AVAILABLE AT WASHINGTON UNIVERSITY IN ST LOUIS The Center for Theoretical and Computational Neuroscience (ctcn.wustl.edu) at Washington University in St Louis invites applications from outstanding Postdoctoral Fellows to work at the interface between theoretical and experimental neuroscience labs at WashU. Deadline for applications is May 1st 2026. The CTCN is a joint initiative between the Schools of Medicine, Engineering, and Arts and Sciences at WashU, and provides a hub for neuroscientists to collaborate with mathematicians, physicists and engineers to find creative solutions to some of the most difficult problems currently facing neuroscience and artificial intelligence. Each CTCN Postdoctoral Fellow is based in at least two labs, but also has the opportunity to seek out new collaborations which help build new connections within the WashU community. We are looking for people with drive, independence and outstanding prior achievement, who are committed to leveraging interdisciplinary collaboration to drive forward the field of theoretical and computational neuroscience. Washington University in St Louis is ranked in the top 10 worldwide for Neuroscience and Behavior. Salary for CTCN Fellows is significantly above standard NIH postdoc rates, and funds for conference travel are included. In addition, WashU offers excellent benefits and comprehensive access to career development, professional and personal support. The St Louis metropolitan area has a population of almost 3M and is rich in culture, green spaces and thriving music and arts scenes, with a highly accessible cost of living. For more details on this prestigious Fellowship opportunity, including how to apply, please see https://ctcn.wustl.edu/postdoc-fellows Professor Geoffrey J Goodhill Departments of Developmental Biology and Neuroscience Affiliate appointments: Physics, Biomedical Engineering, Computer Science and Engineering, and Electrical and Systems Engineering Washington University School of Medicine 660 S. Euclid Avenue St. Louis, MO 63110 g.goodhill(a)wustl.edu https://neuroscience.wustl.edu/people/geoffrey-goodhill-phd

March 5, 2026

NEST Conference 2026 Abstract Submission and Registration open

by Hans Ekkehard Plesser

Dear Colleagues, The NEST Initiative is excited to invite everyone interested in Neural Simulation Technology and the NEST Simulator to the NEST Conference 2026. The NEST Conference provides an opportunity for the NEST Community to meet, exchange success stories, swap advice, learn about current developments in and around NEST spiking network simulation and its application. Take the opportunity to advance your skills in using NEST at our hands-on workshops! We explicitly encourage young scientists to participate in the conference! This year's conference will again take place as a virtual conference on Tuesday/Wednesday 16/17 June 2026. We are delighted to welcome * Marja-Leena Linne, Tampere University * Maxime Carriere and Fynn Dobler, Freie Universität Berlin * Agnes Korcsak-Gorzo, Forschungszentrum Jülich * Pablo Martínez Cañada, University of Granada as one of our keynote speakers at this year’s conference. Registration and submission of contributions are now open! We are inviting you to submit contributions in the form of talks and "posters". Please register and submit your contribution(s) via the conference website https://nest-simulator.org/conference. Important dates: 10 April 2026 - Deadline for submission of contributions 05 May 2026 - Notification of acceptance 09 June 2026 - Registration deadline We are looking forward to seeing you all in June! Hans Ekkehard Plesser and the conference organizing committee -- Prof. Dr. Hans Ekkehard Plesser Research Committee Chair, Faculty of Science and Technology Department of Data Science Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

March 5, 2026

Study Computational & AI-Centered Cognitive Science in Vienna

by Moritz Grosse-Wentrup

Do you want to revolutionize how we understand the mind and brain using AI, machine learning, and data-driven methods? The **Middle European interdisciplinary master’s programme in Cognitive Science (MEi:CogSci@Univie)** is a two-year, English-taught master program at the University of Vienna that combines - **strong training in quantitative methods** (statistics, programming, signal processing, machine learning, AI) and - **flexible, student-driven specialization in one or more core domains of cognitive science** - you choose your focus area(s) from among neuroscience, biology, linguistics, anthropology, philosophy, and psychology, and can tailor your curriculum accordingly, - with **early involvement in research** in small, interdisciplinary, and international teams. We are looking for applicants who either - hold a bachelor degree in one of the core disciplines of cognitive science (biology, computer science, linguistics, philosophy, psychology, social and cultural anthropology, cognitive science) and wish to develop a strong computational and AI-focused profile, or - hold a bachelor degree in a field with a strong background in quantitative methods (e.g. mathematics, physics, engineering, or other natural sciences) and wish to build on this foundation to master AI techniques and apply their knowledge to a domain of cognitive science of their choice. **Key facts for the new cohort (winter term 2026/27):** - **Application period:** Open now; closes on 7 April - **Details and online application:** https://ssc-phil.univie.ac.at/studien/middle-european-interdisciplinary-mas… - **Start of semester:** 1 October 2026 If you are excited about using AI to push the boundaries of cognitive science - and want the freedom to shape your own specialization - we encourage you to apply for the MEi:CogSci@Univie cohort starting in the winter term 2026/27. Best regards, Moritz Grosse-Wentrup Study Director MEi:CogSci@Univie University of Vienna

March 5, 2026

Neural Data Analysis Workshop before FENS forum (Jun 3-4, 2026)

by Edoardo Balzani

Excited to share a great opportunity for systems neuroscientists! This July, right before the FENS forum, the Flatiron Institute Center for Computational Neuroscience of the Simons Foundation is hosting a hands-on workshop <https://www.simonsfoundation.org/event/ccn_fens2026/?swcfpc=1> on neural data analysis in Barcelona, Spain. *Workshop Details:* *What: *2-day workshop on pynapple <https://pynapple.org/> & NeMoS <https://nemos.readthedocs.io/en/latest/#> *When: *Jul 3–4, 2026 *Where: *Melia Barcelona Sky Hotel Pere IV, 272 - 286 Spain *Who:* Grad students & postdocs analyzing electrophysiology or calcium imaging data*. *Applicants located in Europe and Africa will be prioritized. Via live-coding and hands-on group projects, you will learn to: - Use pynapple for neural data manipulation and exploration - Build statistical models with NeMoS (powered by JAX with GPU acceleration) *Cost:* Accommodation & meals provided, no participation fees. Both packages are open-source Python tools developed at Flatiron CCN <https://www.simonsfoundation.org/flatiron/center-for-computational-neurosci…> to streamline neural data analysis and modeling. *Apply here:* https://simonsfoundation.formstack.com/forms/neural_data_analysis_workshop_… *Learn more:* https://www.simonsfoundation.org/event/ccn_fens2026/?swcfpc=1 Please feel free to share with anyone who might be interested! Best regards, Edoardo Balzani -- *Edoardo Balzani* Associate Research Scientist Center for Computational Neuroscience Flatiron Institute

March 4, 2026

Call for Proposals for Satellite Workshops at the Bernstein Conference 2026 is open now

by Bernstein Conference

+++ The Bernstein Network Computational Neuroscience invites proposals for Satellite Workshops at the Bernstein Conference 2026 in Frankfurt am Main, Germany. +++ ____ *Bernstein Conference* Each year, the Bernstein Network invites the international computational neuroscience community to the Bernstein Conference for intensive scientific exchange. It has established itself as one of the most renowned conferences worldwide in this field, attracting students, postdocs, and PIs from around the world to meet and discuss new scientific discoveries.** https://www.bernstein-conference.de/ <https://www.bernstein-conference.de/> ____ ** *Satellite Workshops* Satellite Workshops at the Bernstein Conference 2026 provide a forum to discuss topical research questions, novel scientific approaches, and challenges in computational neuroscience and related fields. Ideally, the format should foster extensive scientific discussions and debates, and go beyond a mere series of talks. https://bernstein-network.de/bernstein-conference/call-for-satellite-worksh… <https://bernstein-network.de/bernstein-conference/call-for-satellite-worksh…> ____ ** *Important Dates* Satellite Workshops: *September 28 - 29, 2026* ·Monday, Sep 28, 14:00 - 18:30 CEST ·Tuesday, Sep 29, 8:30 - 12:30 CEST Main Conference: September 29 - October 1, 2026 Deadline for Satellite Workshop proposal submission: *April 29, 2026 at 15:00 CEST* Notification of Satellite Workshop acceptance: May 2026 ____ ** *Benefits* For each workshop, the organizers will receive *one fee waiver* for the Satellite Workshops, which they can award to one of the workshop speakers. We strongly recommend that the waiver is issued giving consideration to aspects of inclusion. ** ____ *INVITED SPEAKERS* Roshan Cools (Donders Institute for Brain, Cognition and Behaviour, The Netherlands) Benjamin Grewe (Institute of Neuroinformatics of the ETH and UZH, Switzerland) Andreas Herz (LMU Munich, Germany) Ewelina Knapska (Nencki Institute of Experimental Biology, Poland) John Krakauer (Champalimaud Foundation, Portugal) Jeehyun Kwag (Seoul National University, Korea) Anna Levina (University of Tübingen, Germany) Bence Ölveczky (Harvard University, USA) Sandro Romani (Janelia Research Campus, USA) ____ *CONFERENCE COMMITTEE* Stefan Rotter (Conference Chair) Matthias Kaschube (Conference Host) Tim Vogels (Program Chair) Panayiota Poirazi (Program Vice Chair) Katharina Wilmes (Workshop Chair) Juan Álvaro Gallego(Workshop Vice Chair) & Nicolas Brunel, Alex Cayco-Gajic, Monika Jadi, Jennifer Li, Scott Linderman, Wiktor Młynarski, Richard Naud, Joseph Raimondo, Tatyana Sharpee, Taro Toyoizumi, Eleni Vassilaki ____ For any further questions, please contact: bernstein.conference(a)fz-juelich.de <mailto:bernstein.conference@fz-juelich.de>

March 4, 2026

[COMPLEX NETWORKS 2026] CFP — Submission Now Open (Granada, Dec 2–4, 2026)

by Hocine Cherifi

*Complex Networks 2026* 15th International Conference on Complex Networks and Their Applications 📍 Granada 🗓 December 02–04, 2026 (Tutorials: December 01) 📝 Submission deadline: September 02, 2026 The website and submission system are now open. We invite original research contributions on theoretical foundations, methodological advances, and interdisciplinary applications of complex networks across data science, physics, computer science, mathematics, and the social sciences. Accepted papers will be published in the conference proceedings. Selected high-quality contributions will be invited to submit extended versions to special issues in journals such as: o Applied Network Science <https://appliednetsci.springeropen.com/> edited by Springer o Advances in Complex Systems <https://www.worldscientific.com/toc/acs/24/02> edited by World Scientific o Complex Systems <https://www.complex-systems.com/about/> o Entropy <https://www.mdpi.com/journal/entropy> edited by MDPI o PLOS COMPLEX SYSTEMS <https://journals.plos.org/complexsystems/> o PLOS <https://journals.plos.org/plosone/> one <https://journals.plos.org/plosone/> o Social Network Analysis and Mining <https://link.springer.com/journal/13278> edited by Springer Conference website: https://complexnetworks.org/ Submission portal: [https://cmt3.research.microsoft.com/COMPLEXNETWORKS2026/] <https://cmt3.research.microsoft.com/COMPLEXNETWORKS2026/> We look forward to welcoming the community to Granada in December 2026. The Organizing Committee Join us at COMPLEX NETWORKS 2026 <https://www.complexnetworks.org/> *-------------------------* Hocine CHERIFI Laboratoire* I*nterdisciplinaire *C*arnot de *B*ourgogne - ICB UMR 6303 CNRS Université Bourgogne Europe Editor in Chief Plos Complex Systems <https://plos.org/complex-systems-research-journal/#:~:text=PLOS%20Complex%2….> Founding & Adisory Editor Applied Network Science <https://appliednetsci.springeropen.com/> Editorial Board member IEEE ACCESS <https://ieeeaccess.ieee.org/?http%3A%2F%2Fieeeaccess_ieee_org%2F>, Scientific Reports <https://www.nature.com/srep/>, Journal of Imaging <https://www.mdpi.com/journal/jimaging>, Quality and Quantity <https://www.springer.com/journal/11135/>, Computational Social Networks <https://computationalsocialnetworks.springeropen.com/>, Complex Systems <https://www.complex-systems.com/> Evolutionary Intelligence <https://link.springer.com/journal/12065>

March 4, 2026

CFP - Simulation of Adaptive Behavior (SAB 2026)

by Jeffrey L Krichmar

From Animals to Animats 18: The 18th International Conference on Simulation of Adaptive Behavior (SAB 2026) Where: TU Berlin, Germany When: 19-22 October 2026 Website: https://www.sab-conference.org Important Dates Submission deadline: 15 May 2026 Notification of acceptance:19 June 2026 Camera-ready paper version due: 17 July 2026 Conference takes place: 19-22 October 2026 Objectives: The interdisciplinary conference on the Simulation of Adaptive Behavior: From Animals to Animats (SAB) 2026 brings together researchers from artificial intelligence, robotics, behavioral biology, psychology, neuroscience, and many other fields. The conference offers a unique opportunity to exchange ideas across disciplinary boundaries. We believe this exchange is necessary to advance our understanding of the mechanisms that enable general and robust behavior in natural animals and artificial agents. The conference focuses on characterizing and comparing organizational principles and architectures underlying adaptive behavior in animals and animats. Animats denote the conceptual connections between animals and synthetic agents. The conference therefore actively seeks submissions that bridge several of the aforementioned disciplines, combining their methodological foundations to arrive at novel insights and approaches. Of particular interest are research projects which connect natural behavior to synthetic agents, including those leveraging modern machine learning and deep learning techniques for behavioral modeling, analysis, and synthesis. Selected papers will be invited to a special issue in the journal Adaptive Behavior and will be published with Springer Nature. SAB accepts submissions in several tracks: - Conference papers are peer-reviewed. Accepted papers will be published in conference proceedings “From Animals to Animats 18: SAB 2026” Lecture Notes in Artificial Intelligence, Springer Nature. - Conference papers without inclusion in the proceedings. These papers will undergo a light peer-review. Papers will be included on the conference website but they will not be formally published so that your research results can still appear in your disciplinary journals. - Poster abstracts are peer-reviewed for general suitability of the content. Accepted posters will be presented at a poster session and, time permitting, will be able to present a spotlight presentation to the conference attendees. - Position papers are peer reviewed; they offer a novel, visionary perspective on the convergence of different branches of behavior-based research in both artificial and biological systems. These papers are supposed to trigger a lively discussion. - Workshop or Tutorial proposals will be peer reviewed. Workshops and Tutorials will take place on September 20. The event should be relevant to the expected audience of SAB. Topics of interest: Artificial Intelligence, Artificial Life, and Computational neuroscience o Action selection, behavioral sequencing o Communication and language o Emotion and motivation o Internal models and representations o Reinforcement learning o Sensory-motor coordination, motor control o Software agents and virtual creatures Philosophical Issues o Consciousness o Ethics o Mind/Body problem Robotics o Autonomous robotics o Bio-inspired and hybrid robotics o Cognitive robotics o Developmental robotics o Humanoid robotics o Navigation and mapping o Neurorobotics Self-Organizing Systems o Body and brain co-evolution o Collective and social behavior o Dynamical systems approaches o Evolutionary and co-evolutionary approaches o Self-assembling and self-replication Paper and Abstract Submission: Author Guidelines for All Tracks All submissions must be written in English and formatted in the Springer LNCS style. Please refer to the LNCS Springer style guide for style templates and formatting instructions. We strongly encourage authors to prepare papers using LaTeX. The LNCS package for LaTeX and the instructions file can be downloaded directly from Springer’s website. https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu… Additional Guidelines for Conference and Position Papers All submitted papers (conference papers with and without inclusion in the proceedings, as well as position papers) must not exceed 12 pages, including references. Additional Guidelines for Poster Abstracts All submitted poster abstracts must not exceed 3 pages, including references. How to Submit All submissions will be handled through the CMT (Conference Management Toolkit) system. Authors must create a CMT account before submitting their paper. (For instructions: https://sab2026.scioi.de/call-for-contributions/ ) Where to Submit SAB submission website (CMT) https://cmt3.research.microsoft.com/User/Login?ReturnUrl=%2FSAB2026%2FSubmi… Paper Review & Acceptance: All submitted full papers will be peer-reviewed based on relevance, originality, quality of presentation, and technical quality. The authors of all accepted papers are kindly requested to revise their papers following the reviewers’ comments. Authors of accepted papers will be invited to present their research work either as an oral presentation or as a poster. Workshop Tutorial Proposals: We will consider proposals for workshops and tutorials. Workshops and tutorials will be held on the first day of the conference (19 October 2025) and must be held in-person. Proposals will be reviewed by the Organizing Committee. To submit a workshop or tutorial, please follow the below template and submit here: https://cmt3.research.microsoft.com/SAB2026/Track/6/Submission/Create Template Similar to paper submissions, please follow the LNCS Springer style guide for templates and formatting instructions. For your workshop or tutorial proposal, please include the following information, as displayed on our website. https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu… https://sab2026.scioi.de/call-for-contributions/ Publication: All accepted papers (oral and poster presentations) will be published by Springer Nature in the Lecture Notes in Artificial Intelligence series. https://link.springer.com/conference/sab Program Committee: Francisco Javier Bellas Bouza – Universidade da Coruña Maren Bennewitz – Universität Bonn Marcel Brass – Humboldt-Universität zu Berlin Lola Cañamero – CY Cergy Paris Université Nikolaus Correll – University of Colorado Boulder Richard José Duro Fernández – Universidade da Coruña Heiko Hamann – Universität Konstanz Alex Kacelnik – University of Oxford Jens Krause – Humboldt-Universität zu Berlin Oliver Kroemer – Carnegie Mellon University Poramate Manoonpong – Vidyasirimedhi Institute of Science and Technology Justus Piater – Universität Innsbruck Tony Prescott – University of Sheffield Pawel Romanczuk – Humboldt-Universität zu Berlin Gregor Schöner – Ruhr-Universität Bochum Dylan Shell – Texas A&M University Gaurav Sukhatme – University of Southern California Jochen Triesch – Frankfurt Institute for Advanced Studies Elio Tuci – Université de Namur Myra Wilson – Aberystwyth University Florentin Wörgötter – Universität Göttingen Program Chairs: Oliver Brock – Technische Universität Berlin Jeff Krichmar – University of California, Irvine The conference will be held at Science of Intelligence/TU Berlin and the Universität der Künste (UDK), Berlin, Germany. We look forward to welcoming you at SAB 2026! Best regards, SAB Organizing Committee organisers(a)sab-conference.org Jeff Krichmar Department of Cognitive Sciences 2328 Social & Behavioral Sciences Gateway University of California, Irvine Irvine, CA 92697-5100 jkrichma(a)uci.edu http://www.socsci.uci.edu/~jkrichma

March 3, 2026

Postdoctoral Position in Electrophysiology and Computational Modeling of Language

by Kuperberg, Gina R.

Postdoctoral Position in Electrophysiology and Computational Modeling of Language (Start date: by June 1, 2026) The NeuroCognition of Language Lab (PI: Gina Kuperberg), jointly based at Tufts University and the Martinos Center for Biomedical Imaging at Massachusetts General Hospital (Boston), invites applications for a fully funded, two-year postdoctoral position. Applications will be reviewed on a rolling basis until the position is filled, with an intended start date of June 1, 2026 This position offers opportunities to pursue theory-driven research at the intersection of psycholinguistics, computational neuroscience, and electrophysiology. We are especially interested in applicants whose expertise aligns with one or more of the following areas: 1. Electrophysiology and predictive processing in sentence and discourse comprehension Using MEG and/or EEG to characterize the spatiotemporal dynamics of predictive processing during real-time language comprehension, with an emphasis on sentence- and discourse-level mechanisms. 2. Computational modeling of comprehension Developing mechanistic models (e.g., predictive coding simulations), and linking model behavior to behavioral and neural signatures of comprehension. We are also interested in decision-making and confidence-updating frameworks that formalize how comprehenders evaluate uncertainty, accumulate error evidence, and engage reprocessing following linguistic errors. 3. Language production in schizophrenia and computational language analysis Analyzing large-scale corpora of patient speech, using computational language methods, including Large Language Models (LLMs), to quantify and understand disorganized language production in schizophrenia. Applicants must hold a Ph.D. in cognitive science, psycholinguistics, psychology, linguistics, neuroscience, computational neuroscience, or a related field. Candidates may be strongest in one area (electrophysiology, computational modeling, or NLP/LLM-based language analysis), while demonstrating interest in the broader research program. Core qualifications * Strong interest in mechanistic accounts of sentence and discourse comprehension and its neural implementation * Strong computational and programming skills (Python, MATLAB, and/or R) * Experience with linear mixed-effects models and related statistical approaches Additional qualifications (one or more, depending on area of focus) * Experience collecting and/or analyzing EEG and/or MEG data * Experience developing and testing computational models of comprehension, for example predictive coding simulations * Experience applying computational language analysis methods, including distributional semantic similarity and embedding-based metrics, topic models, and LLM-based approaches, to understanding behavioral and neural data from naturalistic language paradigms For more about our lab, see our website: https://kuperberglab.com/ Massachusetts General Hospital and Tufts University are equal opportunity and affirmative action employers. Full-time employees receive full benefits. To apply, please send the following materials to Gina Kuperberg, M.D., Ph.D. (gkuperberg(a)mgh.harvard.edu<mailto:gkuperberg@mgh.harvard.edu>) and cc Arim Choi (arim.choi(a)tufts.edu<mailto:arim.choi@tufts.edu>): 1. Cover letter describing research experience and interests, including (i) which project area(s) you are applying to, and (ii) a brief statement of fit connecting your interests to the lab’s approach (for example, by referencing 1–2 relevant papers from our group or closely related work) 2. Curriculum Vitae 3. Names and contact details of references 4. PDFs of published or submitted papers ---------------------------------- Gina Kuperberg, MD PhD Dennett Stibel Professor in Cognitive Science, Department of Psychology, Tufts University Psychiatrist, Department of Psychiatry, Mass. General Hospital Tel: 617 863-0727 Fax: 617 812-4799 email: Gina.Kuperberg(a)tufts.edu OR GKuperberg(a)mgh.harvard.edu website: https://kuperberglab.com/

March 3, 2026