Proposals of technical talk (up to one-page abstract including short Bio of the main speaker). Topics include, but our not limited to: learning optimization models from data, constraint and objective learning, AutoAI, especially if combined with decision optimization models or environments, AutoRL, incorporating the inaccuracy of the automatically learnt models in the decision making process, and using machine learning to efficiently solve combinatorial optimization models. Ting Hua, Chandan Reddy, Lijing Wang, Liang Zhao, Lei Zhang, Chang-Tien Lu, and Naren Ramakrishnan. The workshop page ishttps://sites.google.com/view/aaaiwfs2022, and it will include the most up-to-date information, including the exact schedule. Submission site:https://easychair.org/conferences/?conf=kdf22, Chair:Xiaomo Liu (J.P. Morgan Chase AI Research, xiaomo.liu@jpmchase.com), Zhiqiang Ma (J.P. Morgan Chase AI Research), Armineh Nourbakhsh (J.P. Morgan Chase AI Research), Sameena Shah (J.P. Morgan Chase AI Research), Gerard de Melo (Hasso Plattner Institute), Le Song (Mohamed bin Zayed University of Artificial Intelligence), Workshop URL:https://aaai-kdf.github.io/kdf2022/. ACM, New York, NY, USA, 10 pages. Combating fake news is one of the burning societal crises. Modeling Health Stage Development of Patients with Dynamic Attributed Graphs in Online Health Communities. Incomplete Label Multi-Task Ordinal Regression for Spatial Event Scale Forecasting. A new and comprehensive view of AI Safety must cover a wide range of AI paradigms, including systems that are application-specific as well as those that are more general, considering potentially unanticipated risks. Visualization is an integral part of data science, and essential to enable sophisticated analysis of data. Attendance is open to all prior registration to the workshop/conference. These models can also generate instant feedback to instructors and help them to improve their teaching effectiveness. All deadlines are at 11:59 PM anytime in the world. ECoST: Energy-Efficient Co-Locating and Self-Tuning MapReduce Applications. Track 2 focuses on the state of the art advances in the computational jobs marketplace. Regarding efficiency, it is impractical to train a neural network containing billions of parameters and then deploy it to an edge device in practice. Qingzhe Li, Liang Zhao, Jessica Lin and Yi-ching Lee. SL-VAE: Variational Autoencoder for Source Localization in Graph Information Diffusion. 2022. Hence, this workshop will focus on introducing research progress on applying AI to education and discussing recent advances of handling challenges encountered in AI educational practice. 20, 2022: We have announced Call for Nominations: , Jan. 25, 2022: Sponsorship Opportunities is available at, Jan. 6, 2022: Call for KDD Cup Proposals is available at, Dec. 26, 2021: Call for Workshop Proposals is available at, Dec. 26, 2021: Call for Tutorials is available at, Nov. 24, 2021: Those who are interested in serving as a PC, please feel free to fill in this, Nov. 12, 2021: Call for Research Track Papers is available at, Nov. 12, 2021: Call for Applied Data Science Track Papers is available at. ITCI22 will be a one-day workshop. Aug 14-18. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), accepted. 7, no. Algorithms for secure and privacy-aware machine learning for AI. This workshop wants to emphasize on the importance of integrative paradigms for solving the new wave of AI applications. 32, no. Scientific documents such as research papers, patents, books, or technical reports are one of the most valuable resources of human knowledge. While a variety of research has advanced the fundamentals of document understanding, the majority have focused on documents found on the web which fail to capture the complexity of analysis and types of understanding needed across business documents. Metagraph Aggregated Heterogeneous Graph Neural Network for Illicit Traded Product Identification in Underground Market. Graph Neural Networks: Foundations, Frontiers, and Applications. Each paper will be reviewed by three reviewers in double-blind. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. Guangji Bai, Johnny Torres, Junxiang Wang, Liang Zhao, Carmen Vaca, Cristina Abad. System reports should also follow the AAAI 2022 formatting guidelines and have 4-6 pages including references. Participants will be given access to publicly available datasets and will be asked to use tools from AI and ML to generate insight from the data. Each accepted paper presentation will be allocated between 15 and 20 minutes. Incomplete Label Multi-task Deep Learning for Spatio-temporal Event Subtype Forecasting.Thirty-third AAAI Conference on Artificial Intelligence (AAAI 2019), (acceptance rate: 16.2%), Hawaii, USA, Feb 2019, accepted. We expect ~60 attendees. Full papers: Submissions must represent original material that has not appeared elsewhere for publication and that is not under review for another refereed publication. Malicious attacks for ML models to identify their vulnerability in black-box/real-world scenarios. Guangji Bai, Chen Ling, Liang Zhao. The role of adjacent fields of study (e.g, computational social science) in mitigating issues of bias and trust in AI. How to do good research, Get it published in SIGKDD and get it cited! What techniques and approaches can be used to detect and effectively manage similar scenarios in the future? anomaly detection, and ensemble learning. We will accept both original papers up to 8 pages in length (including references) as well as position papers and papers covering work in progress up to 4 pages in length (not including references).Submission will be through Easychair at the AAAI-22 Workshop AI4DO submission site, Professor Bistra Dilkina (dilkina@usc.edu), USC and Dr. Segev Wasserkrug, (segevw@il.ibm.com), IBM Research, Prof. Andrea Lodi (andrea.lodi@cornell.edu), Jacobs Technion-Cornell Institute IIT and Dr. Dharmashankar Subrmanian (dharmash@us.ibm.com), IBM Research. The 11th International Conference on Learning Representations (ICLR 2023), accepted. The extraction, representation, and sharing of health data, patient preference elicitation, personalization of generic therapy plans, adaptation to care environments and available health expertise, and making medical information accessible to patients are some of the relevant problems in need of AI-based solutions. At the same time, multimodal hate-speech detection is an important problem but has not received much attention. Hence, there is a need for research and practical solutions to ML security problems.With these in mind, this workshop solicits original contributions addressing problems and solutions related to dependability, quality assurance and security of ML systems. Yuyang Gao, Tong Sun, Sungsoo Hong, and Liang Zhao. The workshop attracted about 100 attendees. Registration information will be mailed directly to all invited participants in December. You can optionally export all deadlines to Google Calendar or .ics . We invite a long research paper (8 pages) and a demo paper (4 pages) (including references). What safety engineering considerations are required to develop safe human-machine interaction? Zitao Liu (main contact) , TAL Education Group, liuzitao@tal.com, http://www.zitaoliu.com, Jiliang Tang (Michigan State University, tangjili@msu.edu, https://www.cse.msu.edu/~tangjili/), Lihan Zhao (TAL Education Group, zhaolihan@tal.com), and Xiao Zhai (TAL Education Group, zhaixiao@tal.com), Workshop URL:http://ai4ed.cc/workshops/aaai2022. Amitava Das (Wipro AI Labs; amitava.santu@gmail.com), Workshop Chairs: Amitava Das (Wipro AI Labs) [India], Amit Sheth (University of South Carolina) [USA], Tanmoy Chakraborty (IIIT Delhi) [India], Asif Ekbal (IIT Patna) [India], Chaitanya Ahuja (CMU) [USA], Parth Patwa (UCLA) [USA], Parul Chopra (CMU) [USA], Amrit Bhaskar (ASU) [USA], Nethra Gunti (IIIT Sri City) [USA], Sathyanarayanan R. (IIIT Sri City) [India], Shreyash Mishra (IIIT Sri City) [India], S. Suryavardan (IIIT Sri City) [India], Vishal Pallagani (University of South Carolina), Supplemental workshop site:https://aiisc.ai/defactify/. Yet, most of these efforts highlighted the challenges of model governance and compliance processes. International Journal of Digital Earth, (impact factor: 3.097), 25 Aug 2020, https://doi.org/10.1080/17538947.2020.1809723. There is a need for the research community to develop novel solutions for these practical issues. Innovation, Service, and Rising Star Awards. Shuo Lei, Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu. First, large data sources, both conventionally used in social sciences (EHRs, health claims, credit card use, college attendance records) and unconventional (social networks, fitness apps), are now available, and are increasingly used to personalize interventions. 22, Issue 2. Yevgeniy Vorobeychik (Washington University in St. Louis), Bruno Sinopoli (Washington University in St. Louis), Jinghan Yang (Washington University in St. Louis), Bo Li (UIUC), Atul Prakash (University of Michigan), Supplemental Workshop site:https://jinghany.github.io/trase2022/. July 21: Clarified that the workshop this year will be held in-person. Additionally, adversaries continue to develop new attacks. New theory and fundamentals of AI-aided design and manufacturing. All time are 23:59, AoE (Anywhere on Earth), Hongteng Xu (Renmin University of China, hongtengxu@ruc.edu.cn, main contact), Julie Delon (Universit de Paris, julie.delon@u-paris.fr), Facundo Mmoli (Ohio State University, facundo.memoli@gmail.com), Tom Needham (Florida State University, tneedham@fsu.edu). Submissions will be collected via the OpenReview platform; URL forthcoming on the Workshop website. Junxiang Wang and Liang Zhao. Aryan Deshwal (Washington State University, aryan.deshwal@wsu.edu), Syrine Belakaria (Washington State University, syrine.belakaria@wsu.edu), Cory Simon (Oregon State University, cory.simon@oregonstate.edu), Jana Doppa (Washington State University, jana.doppa@wsu.edu), Yolanda Gil (University of Southern California, gil@isi.edu), Supplemental workshop site:https://ai-2-ase.github.io/. Liang Zhao, Olga Gkountouna, and Dieter Pfoser. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (Impact Factor: 14.255), accepted. Short or position papers of up to 4 pages are also welcome. Submissions of technical papers can be up to 7 pages excluding references and appendices. It is valuable to bring together researchers and practitioners from different application domains to discuss their experiences, challenges, and opportunities to leverage cross-domain knowledge. The industry session will emphasize practical industrial product developments using GNNs. Negar Etemadyrad, Qingzhe Li, Liang Zhao. Liang Gou, Bosch Research (IEEE VIS liaison), Claudia Plant, University of Vienna (KDD liaison), Alvitta Ottley, Washington University, St. Louis, Junming Shao, University of Electronic Science and Technology of China, Visualization in Data Science (VDS at ACM KDD and IEEE VIS), Visualization in Data Science (VDS at ACM KDD and IEEE VIS). in Proceedings of the SIAM International Conference on Data Mining (SDM 2015), (acceptance rate: 22%), Vancouver, BC, pp. Please refer tohttps://rl4ed.org/aaai2022/index.htmlfor additional information. The third AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-22) builds on the success of previous years PPAI-20 and PPAI-21 to provide a platform for researchers, AI practitioners, and policymakers to discuss technical and societal issues and present solutions related to privacy in AI applications. Exploring the limits of self-supervised learning approaches for speech and audio processing, for example, adverse environment conditions, multiple languages, or generalization across downstream tasks. Manuscripts must be submitted as PDF files viaEasyChair online submission system. This workshop starts with acknowledging the fundamental challenges of robustness and adaptiveness in financial services modeling and explores systematic solutions to solve these underlying problems to prevent future failures.