2025 Spring Symposium Series

Sponsored by the Association for the Advancement of Artificial Intelligence 

The Association for the Advancement of Artificial Intelligence is pleased to present the 2025 Spring Symposium Series to be held Monday, March 31 – Wednesday, April 2, 2025 at San Francisco Airport Marriott Waterfront in Burlingame, California. The Spring Symposium Series is an annual set of meetings run in parallel at a common site. It is designed to bring colleagues together in an intimate forum while at the same time providing a significant gathering point for the AI community. The two and one-half day format of the series allows participants to devote considerably more time to feedback and discussion than typical one-day workshops. It is an ideal venue for bringing together new communities in emerging fields.

Symposia generally range from 40–75 participants each. Participation was open to active participants as well as other interested individuals on a first-come, first-served basis. Each participant was expected to attend a single symposium. 

The program includes the following symposia: 

• AI for Health Symposium: Leveraging Artificial Intelligence to Revolutionize Healthcare
• GenAI@Edge: Empowering Generative AI at the Edge
• Human-Compatible AI for Well-being: Harnessing Potential of GenAI for AI-Powered Science
• Machine Learning and Knowledge Engineering for Trustworthy Multimodal and Generative AI (AAAI-MAKE)
• Symposium on Child-AI Interaction in the Era of Foundation Models

AAAI Code of Conduct for Events and Conferences 

All persons, organizations and entities that attend AAAI conferences and events are subject to the standards of conduct set forth on the AAAI Code of Conduct for Events and Conferences. 

Registration and General Information 

Important Registration Dates 

• By December 9th:  AAAI opens registration for Spring Symposium Series 
• February 17th: Deadline for Registration Refund Requests – Last day before Late Registration Rate begins (See Fee Schedule Below)

Registration Fees

The conference registration fee includes admission to one symposium, access to the electronic proceedings, coffee breaks, and the opening reception.

Refund Requests

The deadline for refund requests is February 17, 2025. All refund requests must be made in writing to sss@aaai.org. A $50.00 processing fee will be assessed for all refunds.

Registration Fee Schedule

AAAI Silver Registration

(Includes AAAI membership, plus the conference)

Hotel Information 

For your convenience, AAAI has reserved a block of rooms at the San Francisco Airport Marriott Waterfront in Burlingame, CA. The hotel is located in the San Francisco area minutes from SFO airport. Downtown San Francisco is easily accessible which offers great dining and shopping. The hotel also offers complimentary airport shuttle service to and from the International Airport terminals based on availability.

The conference room rate per night is $229.00 (King/Double).  

The above rates are subject to applicable tax which is currently 12% Occupancy Tax + 1.50% San Francisco Peninsula Tourism Marketing District Assessment per room, per night, and is subject to change without notice. Symposium attendees must contact the San Francisco Airport Marriott Waterfront directly. Please request the group rate for the Association for the Advancement of Artificial Intelligence (AAAI) when reserving your room. The cut-off date for reservations is Friday March 7, 2025 at 5:00 PM PST, local time at the hotel. Reservations after this date will be accepted based on availability at the hotel’s prevailing rate. All reservations must be secured by one night’s deposit per room, via credit card. Reservations may be cancelled with no penalty up to 5:00 pm, 72 hours prior to the date of arrival. After that time, a penalty of one night’s room and tax will be incurred. Upon check-in, date of departure must be confirmed. Early departure will result in a fee equal to one night’s guest room rate.

San Francisco Airport Marriott Waterfront in Burlingame, CA. USA
1800 Old Bayshore Hwy, Burlingame, CA 94010

Transportation to the Hotel 

Hotel Parking: On-site parking fee is $12 USD Hourly, $48 Daily

Additional Parking Information

Self-parking USD $12 for first hour, USD $24 for 1-3 hours, USD $36 for 3-6 hours and USD $48 for 6+ hours and overnight

The hotel also offers a complimentary shuttle to and from the SFO Airport based on availability-please reach out to hotel for more information.

Visa Information 

Letters of invitation can be requested by accepted SSS-25 authors or registrants with a completed registration with payment. You can access the visa letter form via the link in your registration confirmation email.

Onsite Registration Schedule 

General Event Schedule 

Each Symposium’s Schedule May Differ

Additional Information: 

General inquiries regarding the symposium series should be directed to AAAI at sss@aaai.org. 

AI for Health Symposium: Leveraging Artificial Intelligence to Revolutionize Healthcare

Artificial Intelligence (AI) is poised to transform healthcare, offering groundbreaking capabilities in disease diagnosis, treatment, drug discovery, and patient care. By improving access to health services, reducing costs, and addressing workforce shortages, AI can play a pivotal role in tackling global health challenges. However, successfully integrating AI into healthcare requires careful consideration of regulatory frameworks, governance structures, data equity, and privacy protections. This symposium will bring together AI researchers, clinicians, and industry experts to foster meaningful dialogues and insights that contribute to responsible AI development.

Traditional AI models in healthcare often rely on limited, isolated datasets, facing challenges like missing values, data imbalance, and insufficient representation of diverse patient populations. These issues can lead to algorithmic biases, diminished generalizability, and reduced accuracy of AI-driven predictions, especially in clinical settings. Ensuring access to large, high-quality datasets is key to addressing these limitations, yet privacy and security constraints often restrict data sharing and collaboration across institutions.

This symposium aims to explore current challenges and forward-looking solutions to enhance AI’s reliability, inclusivity, and ethical impact in healthcare. By bringing together diverse stakeholders, it seeks to foster cross-disciplinary collaborations and promote the development of people-centered, AI-enabled healthcare systems.

Topics:

• AI for medical data analysis
• Clinical decision support systems
• Drug discovery and personalized medicine
• Digital health platforms
• Data equity, privacy, and security in healthcare AI
• Addressing data imbalance and bias challenges
• Building accessible and user-friendly health data management systems

Format of Symposium:

• A two-and-a-half-day workshop, with a combination of paper presentations (3 sessions, each with 4 papers), a keynote talk, invited talks, a panel discussion and poster sessions.
• Attendees will participate in breakout group discussions and interactive sessions.
• Attendance: The symposium is open to researchers, clinicians, and industry professionals with a focus on AI applications in healthcare. There are no specific criteria for attendance beyond relevance to the field.

Submission Requirements:

• Submissions should be in the form of papers or abstracts.
• The length of submissions will be specified on the official submission site.

Submission Site Information:

• Submission Link Coming Soon

Symposium Committee:

• Lifang He, Assistant Professor, Computer Science and Engineering, Lehigh University (lih319@lehigh.edu)
• Mooi Choo Chuah, Full Professor, Computer Science and Engineering, Lehigh University; IEEE Fellow, NAI Fellow (mcc7@lehigh.edu)
• Xiang Li, Assistant Professor, Massachusetts General Hospital and Harvard Medical School, Harvard University (xli60@mgh.harvard.edu)
• Yuan Luo, Chief AI Officer, Full Professor, Feinberg School of Medicine, Northwestern University (yuan.luo@northwestern.edu)

Symposium External URL:

https://sites.google.com/view/aaai25-ai4health

GenAI@Edge: Empowering Generative AI at the Edge

Generative AI and foundation models have revolutionized cloud-based AI applications. At the same time, advancements in embedded machine learning and tinyML are enhancing AI capabilities at the network’s edge. As hardware and algorithms continue to improve, these fields are increasingly converging.

The GenAI@Edge: Empowering Generative AI at the Edge symposium addresses the critical challenge of deploying sophisticated models in edge environments, where computational resources are limited and efficiency is crucial. Traditionally, generative AI models, due to their high computational demands, have relied on powerful centralized servers. However, the growing demand for real-time, on-device AI solutions in mobile devices, IoT, AR/VR, and other edge applications necessitates innovative approaches in model optimization and efficient algorithm design.

For the first time, this symposium will bring together experts in edge AI, foundation models, and generative AI to foster connections that will drive new advancements in AI. The symposium will focus on the current status and future outlook of deploying foundation models and generative AI on resource-constrained embedded devices, integrating them within the edge-to-cloud continuum. We aim to bridge this gap by exploring cutting-edge techniques in novel computing architectures, model compression, and efficient algorithm design tailored for edge computing. The organizing committee, with a strong track record of successfully hosting conferences and workshops, is well-connected to various communities from which they plan to draw participants.

The GenAI@Edge symposium will assemble a diverse group of experts and researchers from a range of disciplines, including machine learning, hardware design, data science, and cybersecurity, to share recent advancements, open problems, and challenges in their respective fields. The symposium’s goal is to brainstorm research directions that will lead to groundbreaking innovations in generative AI systems.

The event will cover various aspects and applications of generative AI, from model optimization and secure data handling to practical implementations in different industries. The primary objective is to explore how generative AI models can be made more efficient in terms of data usage, model architecture, training processes, and inference—especially on edge devices. Through this multifaceted symposium and the talks by expert speakers, we hope to engage the broader AI community in addressing the unique challenges of deploying generative AI at the edge, fostering collaboration and innovation in this dynamic field.

Topics of Interests:

1. Efficient Training and Inference for Generative AI and Foundation Models
   • Optimizing Memory and Computational Resources
   • Efficient Algorithms and Hardware Acceleration
   • Advanced Deployment and Training Techniques
2. Data Efficiency in Generative AI Models
   • Exploring Few-shot Learning
   • Refinement and Fine Tuning
   • Maximizing Data Utility
3. Efficient Generative AI applications on the Edge
   • Computer Vision Applications
   • Neural Rendering
   • Cross-Disciplinary Integration
   • Multimodal Interactions
   • Customization and Editing

Format of Symposium:

The symposium’s program is thoughtfully designed to foster interaction and engagement, featuring invited talks, focused Q&A sessions, and panel discussions structured as mini tutorials. This format provides an excellent opportunity for young researchers to connect with experts in their fields of interest. Additionally, the symposium invites paper submissions, with all accepted papers to be published in the AAAI Proceedings. The symposium will also feature poster sessions for all accepted papers for fostering interactive discussions and networking among attendees.

Submission Requirements:

• Maximum of 8 pages, including references.
• Submissions must be anonymized for double-blind review.
• For paper formatting, please use the AAAI-25 author kit (https://aaai.org/authorkit25/).

Submission Site Information:

Submission Site: Submission Link Coming Soon

Contact: edgegenai@gmail.com

Symposium Committee:

• Tinoosh Mohsenin, Associate Professor, Johns Hopkins University, Email: tinoosh@jhu.edu
• Evgeni Gousev, Senior Director of Engineering, Qualcomm Research, Email: egousev@qti.qualcomm.com
• Eiman Kanjo, Professor, Imperial College London, Email: e.kanjo@imperial.ac.uk
• Dongkuan (DK) Xu, Assistant Professor, North Carolina State University, Email: dxu27@ncsu.edu
• Hasib-Al Rashid, Machine Learning Engineer, Zywie Healthcare, Email: hrashid1@umbc.edu
• Pretom Roy Ovi, Assistant Professor, University of North Texas, Email: Pretomroy.Ovi@unt.edu
• Binazir Karimzadeh, Postdoctoral Fellow, Georgia Institute of Technology, Email: binazir.bfk@gmail.com
• Arnab Neelim Mazumder, Postdoctoral Fellow, Los Alamos National Laboratory, Email: arnabm1@umbc.edu

Symposium External URL:

https://sites.google.com/view/gen-ai-edge

Human-Compatible AI for Well-being: Harnessing Potential of GenAI for AI-Powered Science

The rapid evolution of Artificial Intelligence (AI), particularly Generative AI (GenAI), presents transformative opportunities and challenges for enhancing individual and societal well-being. This symposium will explore two key perspectives:

Human-Compatible AI for Safeguarding Human Values

This focus area emphasizes the development of AI systems that align with human-defined values such as autonomy, fairness, and transparency. Discussions will examine how such systems can enhance personal decision-making, foster trust, and mitigate risks such as biases, privacy violations, and manipulation.

AI-Powered Science for Real-World Applications

This perspective explores the practical applications of AI technologies like GenAI in sectors such as healthcare, education, and creative industries. The discussions will focus on maximizing their potential while addressing ethical concerns, including bias detection, equitable workforce transitions, and AI-driven advancements across diverse fields.

The symposium aims to integrate these approaches, ensuring that AI technologies are both practically beneficial and aligned with human values. Discussions will address AI’s dual role in driving scientific innovation and safeguarding well-being in real-world contexts.

Topics

We invite contributions addressing the following themes, including but not limited to:

• Human-Compatible AI:
  • Responsible AI for personalized healthcare and education
  • Interpretable AI for critical decision-making

Ethical guidelines for designing GenAI systems

• AI-Powered Science:
  • Fairness and bias mitigation in machine learning
  • AI’s role in societal transformations and public discourse
  • Innovative applications in healthcare and creative industries

Submissions that integrate technical insights with philosophical and ethical considerations are particularly encouraged.

Format

The symposium will feature the following:

• Invited talks
• Technical paper presentations
• Poster and demonstration sessions
• Panel discussions on emerging challenges and opportunities

Submission Information

Interested participants should submit full papers (8 pages maximum) or extended abstracts (2 pages maximum). Abstracts must specify the intended presentation format: long paper, short paper, demonstration, or poster presentation.

All submissions must follow AAAI’s format guidelines and be submitted via EasyChair at https://easychair.org/conferences/?conf=sss25. Additionally, email submissions to sss2025-hcai[at]cas.lab.uec.ac.jp by December 30th, 2024.

Important Dates

• Submission Deadline: December 30th, 2024
• Author Notification: January 17th, 2025
• Camera-Ready Deadline: January 31st, 2025
• Registration Deadline: February 17th, 2025
• Symposium Dates: March 31st – April 2nd, 2025
• Proceedings Publication: October 31st, 2025 (tentative)
• Co-Chairs:

Takashi Kido (Teikyo University, Japan)

Keiki Takadama (The University of Tokyo, Japan)

For more information

please visit the symposium website:
http://www.cas.lab.uec.ac.jp/wordpress/aaai_spring_2025/

Machine Learning and Knowledge Engineering for Trustworthy Multimodal and Generative AI (AAAI-MAKE)

AAAI-MAKE 2025 aims to bring together a diverse group of researchers and practitioners to explore integrating machine learning (ML) and knowledge engineering (KE) in hybrid, multimodal AI systems. By focusing on the hybrid AI MAKE paradigm, the symposium will examine how combining symbolic reasoning with machine learning across multiple modalities—such as text, speech, image, video, radar, and lidar—can pave the way for trustworthy, generative AI. The symposium will serve as a platform for presenting cutting-edge research and facilitating collaboration between academia and industry, addressing the challenges of creating AI systems that are robust, explainable, and capable of human-like reasoning across diverse applications.

Topics

Key topics of discussion will include, but are not limited to:

• Machine Learning, Deep Learning, and Neural Networks
• Knowledge Engineering, Representation, and Reasoning
• Multimodal, Trustworthy, Commonsense, and Explainable AI
• Hybrid AI and Neuro-Symbolic AI
• Generative AI and Large Language Models (LLMs)
• Human-Centered AI, Dialogue Systems, and Conversational AI
• Hybrid (Human-Artificial) Intelligence and Human-in-the-Loop AI

AAAI-MAKE serves as a platform to shape the future of hybrid AI by bridging the gap between machine learning and knowledge engineering. It emphasizes the importance of multimodal systems and generative AI in creating robust, reliable, and transparent AI technologies.

Format and Keynotes

The 2.5-day event will follow the traditional AAAI Spring Symposium Series schedule, with keynotes and morning and afternoon sessions for full, position, and short-paper presentations. We are pleased to announce the following keynote speakers and invited talks:

• Andrei Barbu is a research scientist at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Center for Brains, Minds, and Machines (CBMM).
• Leilani H. Gilpin is an assistant professor in Computer Science and Engineering at the University of California, Santa Cruz, and a Science & Justice Research Center affiliate.
• Alessandro Oltramari is the president of the Carnegie Bosch Institute and a senior research scientist at the Bosch Research and Technology Center in Pittsburgh.
• Pradeep Ravikumar is a professor in the Machine Learning Department of the School of Computer Science at Carnegie Mellon University.

Submission

We solicit full papers (6 to 8 pages) and position or short papers (2 to 4 pages) that can include recent or ongoing research, challenges with datasets, and surveys.

All submissions must reflect the formatting instructions of the AAAI author kit (https://www.aaai-make.info/authorkit) and be submitted through EasyChair (Link coming soon).

The invitation of contributors and presenters will be based on a rigorous single-blinded review of papers by the program committee. Submissions that do not adequately address hybrid, multimodal or trustworthy AI may be desk rejected at the editors’ discretion. Accepted papers shall be published as part of the “Proceedings of the AAAI Symposium Series” by the AAAI Library.

Important Dates

• Abstract submission: 23^rd of December 2024
• Paper submission: 30^th of December 2024
• Notification: 20^th of January 2025
• Camera-ready submission: 3^rd of February 2025
• Symposium: 31^st of March-2^nd of April 2025

Organizing Committee

Symposium Webpage

https://www.aaai-make.info

Symposium on Child-AI Interaction in the Era of Foundation Models

Foundation models such as large language models (LLMs), vision language models (VLMs), and speech foundation models, can enable more effective, natural, and engaging child-AI interactions. Both academic researchers and industry practitioners are increasingly interested in leveraging these models to provide accessible, personalized support for children in areas such as education, entertainment, health, and well-being. However, the opportunities presented by foundation models are accompanied by significant risks and ethical concerns, especially in the context of child-AI interactions. Notable concerns include privacy, bias, and the potential of exposure to harmful and illegal content. The proposed symposium aims to bring together an interdisciplinary group of presenters and participants from relevant fields including, but not limited to, human-robot interaction (HRI), human-computer interaction (HCI), natural language processing (NLP), spoken language understanding (SLU), machine learning (ML), education, and pediatric healthcare. The symposium aims to offer a unique opportunity for researchers across these disciplines to foster mutual understanding and facilitate collaborations, paving the way for future advancements in child-AI interaction.

Topics:

This symposium aims to include topics from key disciplines that study child-AI interaction. These topics may be categorized into two related categories.

1. Child-Centered Interaction Research: This category focuses on work that creates novel interactions for children; this includes both interactions that currently leverage AI and interactions that do not yet leverage AI. We invite submissions across different research fields, including but not limited to human-robot interaction, human-computer interaction, social science, education, and pediatrics.

2. Child-Centered AI Research: This category welcomes submissions that explore novel machine learning methods across various sub-fields that have implications in child-AI interactions. We solicit work that includes but is not limited to natural language processing, speech processing, computer vision, and multimodal machine learning.

Format of Symposium:

The symposium will include the following activities: 1) invited presentations that foster understanding across different research topics or fields; 2) student paper presentations to facilitate in-depth discussions on up-and-coming work; 3) open-format panels to encourage free discussions and Q&A between speakers and participants; and 4) breakout rooms to provide opportunities for networking and tailored discussions based on participants’ research interests.

Submission Requirements: 

Poster/short/position papers: Recommended 2 pages and Maximum 4 pages excluding references. Full papers: Maximum 8 pages excluding references. 

Submission Website:

Submission Site Link Coming Soon

Submission Deadlines:

All deadlines are 11:59pm In Anywhere on Earth (AoE) time zone.

• Deadline for submission: January 10 
• Notification of acceptance or rejection: January 26
• Camera-ready papers for symposium proceedings: February 1

Symposium Committee:

• Zhonghao Shi (University of Southern California) zhonghas@usc.edu
• Nathan Dennler (University of Southern California) dennler@usc.edu
• Amy O’Connell (University of Southern California) amy.dell@usc.edu
• Maja Matarić (University of Southern California) mataric@usc.edu
• Leigh Levinson (Indiana University, Bloomington) lmlevins@iu.edu
• Selma Šabanović (Indiana University, Bloomington) selmas@iu.edu
• Nicholas Georgiou (Yale University) nicholas.georgiou@yale.edu
• Brian Scassellati (Yale University) brian.scassellati@yale.edu
• Xuan Shi (University of Southern California) xuanshi@usc.edu
• Tiantian Feng (University of Southern California) tiantiaf@usc.edu
• Shrikanth Narayanan (University of Southern California) shri@usc.edu
• Jieyu Zhao (University of Southern California) jieyuz@usc.edu
• Robin Jia (University of Southern California) robinjia@usc.edu

Symposium External URL:

https://sites.google.com/iu.edu/childai-aaai2025/home.
If you have questions about the symposium, please feel free to contact Zhonghao Shi (zhonghas@usc.edu) and Nathan Dennler (dennler@usc.edu).