System reports should also follow the AAAI 2022 formatting guidelines and have 4-6 pages including references. DI-2022 accepted papers will not be archived in the main KDD 2022 proceedings. Mingxuan Ju, Wei Song, Shiyu Sun, Yanfang Ye, Yujie Fan, Shifu Hou, Kenneth Loparo, and Liang Zhao. Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet. Functional Connectivity Prediction with Deep Learning for Graph Transformation. Deadline in your local America/New_York timezone: Deadline in timezone from conference website: DASFAA 2022. Programming Languages, Domain specific languages, Libraries and software tools for integration of various learning and reasoning paradigms. An increasing world population, coupled with finite arable land, changing diets, and the growing expense of agricultural inputs, is poised to stretch our agricultural systems to their limits. 41-50, New Orleans, US, Dec 2017. Specific topics of interest for the workshop include (but are not limited to) foundational and translational AI activities related to: The workshop will be a one day meeting comprising invited talks from researchers in the field, spotlight lightning talks and a poster session where contributing paper presenters can discuss their work. This year the AICS emphasis will be on practical considerations in the real world when deploying AI systems for security with a special focus on convergence of AI and cyber-security in the biomedical field. 4498-4505, New Orleans, US, Feb 2018. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), vol. KDD 2022. The aim of this workshop is to focus on both original research and review articles on various disciplines of ITS applications, including particularly AI techniques for ITS time-series data analyses, ITS spatio-temporal data analyses, advanced traffic management systems, advanced traveler information systems, commercial vehicle operation systems, advanced vehicle control and safety systems, advanced public transportation services, advanced information management services, etc. Data-driven Humanitarian Mapping and Policymaking Research Online Flu Epidemiological Deep Modeling on Our goal is to build a stronger community of researchers exploring these methods, and to find synergies among these related approaches and alternatives. Submission at:https://easychair.org/my/conference?conf=edsmls2022. Deep Graph Spectral Evolution Networks for Graph Topological Evolution. LOG 2022 LOG '22 . Submitting a short or long paper to VDS will give authors a chance to present at VDS events at both ACM KDD 2022(hybrid) and IEEE VIS 2022( hybrid). We expect 60-70 participants. July 22: The workshop Programis up! 10, pp. Papers should be up to 4 pages in length (excluding references) formatted using the AAAI template. The workshop will include several technical sessions, a virtual poster session where presenters can discuss their work, to further foster collaborations, multiple invited speakers covering crucial aspects for the practical deep learning in the wild, especially the efficient and robust deep learning, some tutorial talks, the challenge for efficient deep learning and solution presentations, and will conclude with a panel discussion. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (Impact Factor: 14.255), accepted. CFP - EasyChair About 7-8 invited speakers who are distinguished professional in Deep learning on graph will present the frontier research topics. 2020. Accepted papers are likely to be archived. Creative Commons Attribution-Share Alike 3.0 License, 29TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 25TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, Knowledge Discovery and Data Mining Conference, 22nd ACM SIGKDD international conference on knowledge discovery and data mining, 21th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 18th ACM SIGKDD Knowledge Discovery and Data Mining, The 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, The 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, The 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, The 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Recent years have witnessed growing efforts from the AI research community devoted to advancing our education and promising results have been obtained in solving various critical problems in education. BEAN: Interpretable and Efficient Learning with Biologically-Enhanced Artificial Neuronal Assembly. Submission Site: See the webpagehttps://sites.google.com/view/gclr2022/submissions; for detailed instructions and submission link. Gabriel Pedroza (CEA LIST), Jos Hernndez-Orallo (Universitat Politcnica de Valncia, Spain), Xin Cynthia Chen (University of Hong Kong, China), Xiaowei Huang (University of Liverpool, UK), Huascar Espinoza (KDT JU, Belgium), Mauricio Castillo-Effen (Lockheed Martin, USA), Sen higeartaigh (University of Cambridge, UK), Richard Mallah (Future of Life Institute, USA), John McDermid (University of York, UK), Supplemental workshop site:http://safeaiw.org/. 14, 2022: The information of Keynote Speakers is available at, Apr. The IEEE International Conference on Data Mining (ICDM 2022), full paper, (Acceptance Rate: 9.77%), to appear, 2022. SIAM International Conference on Data Mining (SDM 2022), (Acceptance Rate: 26%), accepted. This cookie is set by GDPR Cookie Consent plugin. Ferdinando Fioretto (Syracuse University), Aleksandra Korolova (University of Southern California), Pascal Van Hentenryck (Georgia Institute of Technology), Supplemental Workshop site:https://aaai-ppai22.github.io/. Linear Time Complexity Time Series Clustering with Symbolic Pattern Forest. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. Feng Chen, Baojian Zhou, Adil Alim, Liang Zhao. Kaiqun Fu, Taoran Ji, Liang Zhao, and Chang-Tien Lu. . Ting Hua, Feng Chen, Liang Zhao, Chang-Tien Lu, and Naren Ramakrishnan. May 8, 2022: Student Travel Awards announcement is, Apr. I recommend highly motivated students to reach out to me way earlier than the admission deadline, and figure out a research project project with me, with the goal of a publication. KDD: Knowledge Discovery and Data Mining 2024 2023 2022 - WikiCFP Guangji Bai, Chen Ling, Liang Zhao. Natural language reasoning and inference. All these changes require novel solutions, and the AI community is well-positioned to provide both theoretical- and application-based methods and frameworks. 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. In recent months/years, major global shifts have occurred across the globe triggered by the Covid pandemic. Attendance is open to all. Knowledge Discovery and Data Mining is an interdisciplinary area focusing We are excited to announce our upcoming workshop at KDD 2022 | Washington DC, U.S.: Decision Intelligence and Analytics for Online Marketplaces - Jobs, Ridesharing, Retail, and Beyond. Apr 11-14, 2022. The VTU workshops accepts both short paper (4 pages) and long paper (8 pages). Social Media based Simulation Models for Understanding Disease Dynamics. A 2-day workshop to share knowledge and research on five tracks of DSTC-10 and general related technical track. Each paper will be reviewed by three reviewers in double-blind. We invite the submission of original and high-quality research papers in the topics related to biased or scarce data. The papers may consist of up to seven pages of technical content plus up to two additional pages for references. 19-25, 2016. Integration of declarative and procedural domain knowledge in learning. Note: This is the inaugural event of a conference dedicated to Graph Machine Learning. Attendance is open to all registered participants. Pourya Hoseinip, Liang Zhao, and Amarda Shehu. SL-VAE: Variational Autoencoder for Source Localization in Graph Information Diffusion. Current rates of progress are insufficient, making it impossible to meet this goal without a technological paradigm shift. For example, FL is still at the risk of various kinds of attacks that may result in leakage of individual data source privacy or degraded joint model accuracy. Panel discussion: Interactive Q&A session with a panel of leading researchers. We will specifically invite participants of the DSTC10 tasks, track organizers, and authors of accepted papers in the general technical track. Meta-learning models from various existing task-specific AI models. Generative Deep Learning for Macromolecular Structure and Dynamics, Current Opinion in Structural Biology, (impact factor: 7.108), Section on Theory and Simulation/Computational Methods 67: 170-177, 2021 accepted. We invite workshop participants to submit their original contributions following the AAAI format through EasyChair. We invite paper submission on the following (and related) topics: The workshop will be a 1 day meeting comprising several invited talks from distinguished researchers in the field, spotlight lightning talks and a poster session where contributing paper presenters can discuss their work, and a concluding panel discussion focusing on future directions. . It has profoundly impacted several areas, including computer vision, natural language processing, and transportation. We will also have a video component for remote participation. While the research community is converging on robust solutions for individual AI models in specific scenarios, the problem of evaluating and assuring the robustness of an AI system across its entire life cycle is much more complex. Modeling Health Stage Development of Patients with Dynamic Attributed Graphs in Online Health Communities. Xuchao Zhang, Liang Zhao, Arnold Boedihardjo, and Chang-Tien Lu. As for the Kraken, they made one trade a month ago to acquire a seventh defenceman, Jaycob Megna and did nothing else (from 'Kraken remain quiet as NHL trade deadline passes,' The Seattle . There will be live Q&A sessions at the end of each talk and oral presentation. 1466-1469. Submissions should be formatted using the AAAI-2022 Author Kit. Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data. Zhiqian Chen, Gaurav Kolhe, Setareh Rafatirad, Chang-Tien Lu, Sai Dinakarrao, Houman Homayoun, Liang Zhao. 40 attendees including: invited speakers, authors of accepted papers and shared task participants. The main objective of the workshop is to bring researchers together to discuss ideas, preliminary results, and ongoing research in the field of reinforcement in games. The main research questions and topics of interest include, but are not limited to: This will be a one day workshop, including four invited speakers, one panel session, a number of oral presentations of the accepted long papers and two poster sessions for all accepted papers including short and long. Submissions that do not meet the formatting requirements will be rejected without review. 2022. RLG is a full-day workshop. Accepted submissions will be notified latest by August 7th, 2022. We invite researchers to submit either full-length research papers (8 pages) or extended abstracts (2 pages) describing novel contributions and preliminary results, respectively, to the topics above; a more extensive list of topics is available on the Workshop website. Submit to:https://cmt3.research.microsoft.com/AIBSD2022, Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories, kp388@cornell.edu), Ziyan Wu (UII America, Inc., wuzy.buaa@gmail.com), Supplemental workshop site:https://aibsdworkshop.github.io/2022/index.html. A Systematic Survey on Deep Generative Models for Graph Generation. OARS-KDD2022: KDD 2022 Workshop on Online and Adaptive Recommender Systems Washington DC, DC, United States, August 15, 2022 Topics: data science artificial intelligence recommender system recommendation KDD 2022 Workshop on Online and Adaptive Recommender Systems (OARS) Call For Papers ================== Held in conjunction with KDD'22 Aug 15, 2022 - Washington DC, USA. Submissions should follow the AAAI-2022https://aaai.org/Conferences/AAAI-22/aaai22call/. KDD 2022. The automated processing of unstructured data to discover knowledge from complex financial documents requires a series of techniques such as linguistic processing, semantic analysis, and knowledge representation & reasoning. Submit to: Papers are required to submit to:https://easychair.org/conferences/?conf=dlg22. Online. The workshop will focus on the application of AI to problems in cyber-security. 1953-1970, Oct. 2017. After the submission deadline, the names and order of authors cannot be changed. Deep Learning models are at the core of research in Artificial Intelligence research today. All papers will be peer reviewed, single-blinded. If the admission deadline for international applicants is past, we suggest that you choose another session to begin your studies. Everyone in the Top-10 leaderboard submissions will have a guaranteed opportunity for an in-person oral/poster presentation. What is the status of existing approaches in ensuring AI and Machine Learning (ML) safety, and what are the gaps? Amir A. Fanid, Monireh Dabaghchian, Ning Wang, Pu Wang, Liang Zhao, Kai Zeng. Guangji Bai and Liang Zhao. Junxiang Wang, Hongyi Li, Zheng Chai, Yongchao Wang, Yue Cheng, Liang Zhao. The first achievements in playing these games at super-human level were attained with methods that relied on and exploited domain expertise that was designed manually (e.g. It highlights the importance of declarative languages that enable such integration for covering multiple formalisms at a high-level and points to the need for building a new generation of ML tools to help domain experts in designing complex models where they can declare their knowledge about the domain and use data-driven learning models based on various underlying formalisms. It drives discoveries in business, economy, biology, medicine, environmental science, the physical sciences, the humanities and social sciences, and beyond. Aug 11, 2022: Get early access for registration at L Street Bridge, Washington DC Convention Center, from 4-6 pm, Saturday, August 13. There is increasing evidence that enabling AI technology has the potential to aid in the aforementioned paradigm shift. At the AAAI-22 Workshop on Scientific Document Understanding (SDU@AAAI-22), we aim to gather insights into the recent advances and remaining challenges on scientific document understanding. The following paper categories are welcome: Submission site:https://sites.google.com/view/eaai-ws-2022/call, Silvia Tulli (Dept. Xiaojie Guo and Liang Zhao. What approaches emerge in building fundamentally robust and adaptive AI/ML systems? Liang Zhao, Jiangzhuo Chen, Feng Chen, Fang Jin, Wei Wang, Chang-Tien Lu, and Naren Ramakrishnan. IEEE, 2014. The bottleneck to discovery is now our ability to analyze and make sense of heterogeneous, noisy, streaming, and often massive datasets. Xuchao Zhang, Xian Wu, Fanglan Chen, Liang Zhao, Chang-Tien Lu. IEEE Computer (impact factor: 3.564), vo. We allow both short (2-4 pages) and long papers (6-8 pages) papers. In addition to that, we propose a shared task on one of the challenging SDU tasks, i.e., acronym extraction and disambiguation in multiple languages text. The post-launch session includes the invited talks, shared task winners presentations, and a panel discussion on the resources, findings, and upcoming challenges. For research track papers and applied data science track papers. The AAAI-22 workshop program includes 39 workshops covering a [] Accelerated Gradient-free Neural Network Training by Multi-convex Alternating Optimization. This topic also encompasses techniques that augment or alter the network as the network is trained. Workshop URL:https://rail.fzu.edu.cn/info/1014/1064.htm, Prof. Chi-Hua ChenEmail: chihua0826@gmail.comPostal address: No.2, Xueyuan Rd., Fuzhou, Fujian, ChinaTelephone: +86-18359183858. Yujie Fan, Yanfang (Fanny) Ye, Qian Peng, Jianfei Zhang, Yiming Zhang, Xusheng Xiao, Chuan Shi, Qi Xiong, Fudong Shao, and Liang Zhao. Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao. 2022. Liang Zhao, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan. The 39th IEEE International Conference on Data Engineering (ICDE 2023), accepted. CPM: A General Feature Dependency Pattern Mining Framework for Contrast Multivariate Time Series. This workshop aims to bring together researchers from industry and academia and from different disciplines in AI and surrounding areas to explore challenges and innovations in IML. a fantastic tutorial on SIGKDD'09 by Prof. Eamonn Keogh (UC Riverside). DeepGAR: Deep Graph Learning for Analogical Reasoning. ), Graduate (master's, specialized graduate diploma (DESS), etc. Contrast Pattern Mining in Paired Multivariate Time Series of Controlled Driving Behavior Experiment. Visualization is an integral part of data science, and essential to enable sophisticated analysis of data. A message will appear on your application form if there is a risk that the time required to process the application and to send the answer, in addition to the time you will need to acquire study permits, will be too long for you to arrive for the beginning of the session. Advances in IML promise to make AIs more accessible and controllable, more compatible with the values of their human partners and more trustworthy. Yuanqi du, George Mason University, USA; Jian Pei, Simon Fraser University, Canada; Charu Aggarwal, IBM Research AI, USA; Philip S. Yu, University of Illinois at Chicago, USA; Xuemin Lin, University of New South Wales, Australia; Jiebo Luo, University of Rochester, USA; Lingfei Wu, JD.Com Silicon Valley Research Center, USA; Yinglong Xia, Facebook AI, USA; Jiliang Tang, Michigan State University, USA; Peng Cui, Tsinghua University, China; William L. Hamilton, McGill University, Canada; Thomas Kipf, University of Amsterdam, Netherlands, Workshop URL:https://deep-learning-graphs.bitbucket.io/dlg-aaai22/. Thirty-third AAAI Conference on Artificial Intelligence (AAAI 2020), (acceptance rate: 20.6%), accepted. Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao. 2022. Topics of interest include but are not limited to: (1) Survey papers summarizing recent advances in RL with applicability to ED; (2) Developing toolkits and datasets for applying RL methods to ED; (3) Using RL for online evaluation and A/B testing of different intervention strategies in ED; (4) Novel applications of RL for ED problem settings; (5) Using pedagogical theories to narrow the policy space of RL methods; (6) Using RL methodology as a computational model of students in open-ended domains; (7) Developing novel offline RL methods that can efficiently leverage historical student data; (8) Combining statistical power of RL with symbolic reasoning to ensure the robustness for ED. The excellent papers will be recommended for publications in SCI or EI journals. Deep Spatial Domain Generalization. Paper Submission:November 12, 2021, 11:59 pm (anywhere on earth) Author Notification: December 3, 2021Full conference:February 22 March 1, 2022Workshop:February 28 March 1, 2022. However, most models and AI systems are built with conservative operating environment assumptions due to regulatory compliance concerns. These complex demands have brought profound implications and an explosion of interest for research into the topic of this workshop, namely building practical AI with efficient and robust deep learning models. Data science is the practice of deriving insights from data, enabled by statistical modeling, computational methods, interactive visual analysis, and domain-driven problem solving. Proposals of technical talk (up to one-page abstract including short Bio of the main speaker). Virtual . Submission site:https://openreview.net/group?id=AAAI.org/2022/Workshop/AIAFS, Girish Chowdhary (University of Illinois, Urbana Champaign), Baskar Ganapathysubramanian (Iowa State University; contact: baskarg@iastate.edu), George Kantor (Carnegie Mellon University), Soumyashree Kar (Iowa State University), Koushik Nagasubramanian (Iowa State University), Soumik Sarkar (Iowa State University), Katia Sycara (Carnegie Mellon University), Sierra Young (North Carolina State University), Alina Zare (University of Florida, Gainesville), Supplemental workshop site:https://aiafs-aaai2022.github.io/. Conference Deadlines - I.timyang.vip ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), accepted. Realizing the vision of Document Intelligence remains a research challenge that requires a multi-disciplinary perspective spanning not only natural language processing and understanding, but also computer vision, layout understanding, knowledge representation and reasoning, data mining, knowledge discovery, information retrieval, and more all of which have been profoundly impacted and advanced by deep learning in the last few years. The current research in this area is focused on extending existing ML algorithms as well as network science measures to these complex structures. The 21st IEEE International Conference on Data Mining (ICDM 2021), (Acceptance Rate: 9.9%), accepted. Check the deadlines for submitting your application. ADMM for Efficient Deep Learning with Global Convergence. [Best Paper Candidate], Minxing Zhang, Dazhou Yu, Yun Li, Liang Zhao. [code] This is a 1-day workshop involving talks by pioneer researchers from respective areas, poster presentations, and short talks of accepted papers. How can the financial services industry balance the regulatory compliance and model governance pressures with adaptive models, Methods to combine scientific knowledge and data to build accurate predictive models, Adaptive experiment design under resource constraints, Learning cheap surrogate models to accelerate simulations, Learning effective representations for structured data, Uncertainty quantification and reasoning tools for decision-making, Explainable AI for both prediction and decision-making, Integrating AI tools into existing workflows, Challenges in applying and deployment of AI in the real-world. Information extraction and information retrieval for scientific documents; Question answering and question generation for scholarly documents; Word sense disambiguation, acronym identification and expansion, and definition extraction; Document summarization, text mining, document topic classification, and machine reading comprehension for scientific documents; Graph analysis applications including knowledge graph construction and representation, graph reasoning and query knowledge graphs; Biomedical image processing, scientific image plagiarism detection, and data visualization; Code/Pseudo-code generation from text and im-age/diagram captioning, New language understanding resources such as new syn-tactic/semantic parsers, language models or techniques to encode scholarly text; Survey or analysis papers on scientific document under-standing and new tasks and challenges related to each scientific domain; Factuality, data verification, and anti-science detection. Conference stats are visualized below for a straightforward comparison. Generative Adversarial Learning of Protein Tertiary Structures. Three specific roles are part of this format: session chairs, presenters and paper discussants. It is expected that one of the authors of accepted contributions will register and attend the workshop to present the work in video in-person in the workshops Paper Sessions. Yanfang Ye, Yiming Zhang, Yujie Fan, Chuan Shi and Liang Zhao. In addition, authors can provide an optional one page supplement at the end of their submitted paper (it needs to be in the same PDF file) focused on reproducibility. sup-port vector machine (SVM), decision tree, random forest, etc.) To adapt SSL frameworks to build effective human-centric deep learning solutions for human-centric data, a number of key challenges and opportunities need to be explored. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Event Prediction in the Big Data Era: A Systematic Survey. The official dates for submitting an application are detailed below, but see the exact deadline posted on the Description Page for the program of study. The desired LENGTH of the workshop: Full-day (~8 hours). Besides academia, many companies and institutions are researching on topics specific to their particular domains. Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. Ting Hua, Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. KDD is the premier Data Science conference. The eligibility criteria for attending the workshop will be registration in the conference/workshop as per AAAI norms. Ourprevious workshop at AAAI-21generated significant interest from the community. 1923-1935, 1 Oct. 2020, doi: 10.1109/TKDE.2019.2912187. Declarative languages and differentiable programming. Submissions will undergo double blind review. We will accept the extended abstracts of the relevant and recently published work too. AD Conference Deadlines Liang Zhao, Junxiang Wang, and Xiaojie Guo. Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI 2021), (acceptance rate: 21.0%), accepted. We hope this will help bring the communities of data mining and visualization more closely connected. This AAAI-22 workshop on AI for Decision Optimization (AI4DO) will explore how AI can be used to significantly simplify the creation of efficient production level optimization models, thereby enabling their much wider application and resulting business values.The desired outcome of this workshop is to drive forward research and seed collaborations in this area by bringing together machine learning and decision-making from the lens of both dynamic and static optimization models. GNES: Learning to Explain Graph Neural Networks. ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), accepted. The submissions need to be anonymized. 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. Oilers Outperform Division Rivals at 2023 Trade Deadline Use Compass, the interactive checklist designed exclusively for the Universit de Montral, to carefully prepare your application and to avoid common pitfalls along the way. The 9th International Conference on Learning Representations (ICLR 2021), (acceptance rate: 28.7%), accepted. Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu Aggarwal, and Chang-Tien Lu. This workshop wants to emphasize on the importance of integrative paradigms for solving the new wave of AI applications. The deadline for the submissions is July 31st, 2022 11.59 PM (Anywhere on Earth time). 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/.
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