Affinity Workshop
Women in Machine Learning (WiML) Un-Workshop
Wenshuo Guo · Beliz Gokkaya · Arushi G K Majha · Vaidheeswaran Archana · Berivan Isik · Olivia Choudhury · Liyue Shen · Hadia Samil · Tatjana Chavdarova
The Women in Machine Learning (WiML) workshop was founded in 2006 to forge connections within the relatively small community of women working in machine learning, to encourage mentorship, exchange of ideas, and promote communication. The program features 4 invited talks, 4 breakout sessions each having 2-8 parallel webinars, a panel with discussions on “industry/academic research, how to choose your path” and “post-pandemic adjustment and tips”, a mentoring social and 4 sponsor expo talks. Please refer to https://wimlworkshop.org/icml2021/program/ for more information.
The workshop attracts representatives from both academia and industry, whose contributed talks showcase some of the cutting-edge research done by women. In addition to technical presentations and discussion, the workshop aims to incite debate on promising research avenues and career choices for machine learning professionals. Details about WiML’s history and past events can be found at www.wimlworkshop.org. WiML workshops are overseen by the WiML Board of Directors, who select and oversee the organizing committee for each year’s workshop.
Schedule
Wed 6:40 a.m. - 6:50 a.m.
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Introduction & Opening Remarks
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Intro
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SlidesLive Video |
Wenshuo Guo 🔗 |
Wed 6:50 a.m. - 7:00 a.m.
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Diversity & Inclusion talk by D&I chair
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Talk
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SlidesLive Video |
Danielle Belgrave 🔗 |
Wed 7:00 a.m. - 7:25 a.m.
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Invited Talk #1 - Evaluating approximate inference for BNNs
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Talk
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SlidesLive Video |
Yingzhen Li 🔗 |
Wed 7:00 a.m. - 7:15 a.m.
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QuantumBlack Booth ( Sponsor Booth ) > link | 🔗 |
Wed 7:25 a.m. - 8:30 a.m.
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Breakout Session 1.8: Neural Machine Translation for Low-Resource Languages ( Breakout Session ) > link | 🔗 |
Wed 7:25 a.m. - 8:30 a.m.
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Breakout Session 1.4: Unsupervised Learning in Computer Vision ( Breakout Session ) > link | 🔗 |
Wed 7:25 a.m. - 8:30 a.m.
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Breakout Session 1.3: Data Integration and Predictive Modeling for Precision Medicine in Oncology ( Breakout Session ) > link | 🔗 |
Wed 7:25 a.m. - 8:30 a.m.
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Breakout Session 1.2: School mapping using computer vision technology ( Breakout Session ) > link | 🔗 |
Wed 7:25 a.m. - 8:30 a.m.
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Breakout Session 1.1: Catching Out-of-Context Misinformation with Self-supervised Learning ( Breakout Session ) > link | 🔗 |
Wed 7:25 a.m. - 8:30 a.m.
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Breakout Session 1.6: Fundamentals of Contrastive Learning in Vision ( Breakout Session ) > link | 🔗 |
Wed 7:25 a.m. - 8:30 a.m.
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Breakout Session 1.7: Exploring probabilistic sparse inferencing through the triangulation of neuroscience, computing and philosophy ( Breakout Session ) > link | 🔗 |
Wed 7:25 a.m. - 8:30 a.m.
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Breakout Session 1.5: Machine Learning for Privacy: An Information Theoretic Perspective ( Breakout Session ) > link | 🔗 |
Wed 7:30 a.m. - 9:00 a.m.
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Salesforce Booth ( Sponsor Booth ) > link | 🔗 |
Wed 8:30 a.m. - 9:00 a.m.
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Coffee Break and Posters AM ( Poster Session ) > link | 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Machine Learning Applications in Animal Sciences ( Poster Session ) > link | Ambreen Hamadani 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Emulating Aerosol Microphysics with Machine Learning ( Poster Session ) > link | Paula Harder 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Network Experiment Design for estimating Direct Treatment Effects ( Poster Session ) > link | Zahra Fatemi 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Adversarial Robust Model Compression using In-Train Pruning ( Poster Session ) > link | Sreetama Sarkar 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Iterative symbolic regression for learning transport equations
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Poster Session
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Heta Gandhi 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Cost Aware Asynchronous Multi-Agent Active Search ( Poster Session ) > link | ARUNDHATI BANERJEE 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Exploration and preference satisfaction trade-off in reward-free learning ( Poster Session ) > link | Noor Sajid 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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HYBRIDNET: A NETWORK THAT LEVERAGES ON CLASSICAL AND NON-CLASSICAL COMPUTER VISION TECHNIQUES FOR FEW SHOT LEARNING ON INFRARED IMAGERY ( Poster Session ) > link | Maliha Arif 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Clustering With Financial Fundamentals ( Poster Session ) > link | Jennifer Glenski 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Application of Knowledge Graph in Industry ( Poster Session ) > link | Samira Korani 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Contrastive Domain Adaptation ( Poster Session ) > link | Mamatha Thota 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Risk Analytics for Renewal of Purchase Orders ( Poster Session ) > link | Shubhi Asthana 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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On the (Un-)Avoidability of Adversarial Examples ( Poster Session ) > link | Sadia Chowdhury 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Extraction of Adverse Drug Reactions from Tweets using Aspect Based Sentiment Analysis ( Poster Session ) > link | Sukannya Purkayastha 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Interpretation and transparency in acoustic emotion recognition ( Poster Session ) > link | Sneha Das 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Seasonal forecasts of New Zealand's local climate conditions with limited GCM inputs using Convolutional Neural Networks ( Poster Session ) > link | Fareeda Begum 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Assessing the Carbon Intensity of Models Across Different Languages ( Poster Session ) > link | Krithika Ramesh 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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A Low-rank Support Tensor Network ( Poster Session ) > link | Kirandeep Kour 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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CricNet : Segment and Classify Cricket Events ( Poster Session ) > link | Shambhavi Mishra 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Episodically optimized dynamical networks for robust motor control ( Poster Session ) > link | Sruti Mallik 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Open Set Detection via Similarity Learning ( Poster Session ) > link | Sepideh Esmaeilpour 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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A modified limited memory Nesterov’s accelerated quasi-Newton ( Poster Session ) > link | Indrapriyadarsini Sendilkkumaar 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Time-series Forecasting of Ionospheric Space Weather using Ensemble Machine Learning ( Poster Session ) > link | Randa Natras 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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SocialBERT : An Effective Few Shot Learning Framework Applied to a Social TV Setting ( Poster Session ) > link | Debarati Das 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Explainable Prediction of Text Complexity: The Missing Preliminaries for Text Simplification ( Poster Session ) > link | Cristina Garbacea 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Alignment of Language Agents in Video games ( Poster Session ) > link | Gema Parreno 🔗 |
Wed 8:30 a.m. - 6:00 p.m.
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Using Weak Supervision to Identify Drug Mentions from Class Imbalanced Twitter Data ( Poster Session ) > link | Ramya Tekumalla 🔗 |
Wed 8:30 a.m. - 9:00 a.m.
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DeepMind Booth ( Sponsor Booth ) > link | 🔗 |
Wed 9:00 a.m. - 9:25 a.m.
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Invited Talk #2 - Towards fairness & robustness in machine learning for dermatology
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Talk
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SlidesLive Video |
Celia Cintas 🔗 |
Wed 9:25 a.m. - 10:30 a.m.
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Breakout Session 2.3: Challenges and Opportunities in ML for Health Care: How to address interpretability in clinical decision making? ( Breakout Session ) > link | 🔗 |
Wed 9:25 a.m. - 10:30 a.m.
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Breakout Session 2.7: Explainable machine learning: do we have the right tools? ( Breakout Session ) > link | 🔗 |
Wed 9:25 a.m. - 10:30 a.m.
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Breakout Session 2.1: Geometry and Machine Learning ( Breakout Session ) > link | 🔗 |
Wed 9:25 a.m. - 10:30 a.m.
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Breakout Session 2.8: Decision-Making in Social Settings: Addressing Strategic Feedback Effects ( Breakout Session ) > link | 🔗 |
Wed 9:25 a.m. - 10:30 a.m.
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Breakout Session 2.2: Leveraging Open-Source Tools for Natural Language Processing ( Breakout Session ) > link | 🔗 |
Wed 9:25 a.m. - 10:30 a.m.
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Breakout Session 2.4: Leading the Way for the Next Generation of Black Women in STEM ( Breakout Session ) > link | 🔗 |
Wed 9:25 a.m. - 10:30 a.m.
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Breakout Session 2.5: Un-bookclub Algorithms of Oppression ( Breakout Session ) > link | 🔗 |
Wed 9:25 a.m. - 10:30 a.m.
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Breakout Session 2.6: Research within community: how to cultivate a nurturing environment for your research ( Breakout Session ) > link | 🔗 |
Wed 9:30 a.m. - 10:30 a.m.
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Salesforce Booth ( Sponsor Booth ) > link | 🔗 |
Wed 10:30 a.m. - 10:45 a.m.
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Microsoft: Improving productivity with Graph ML over content-interaction networks
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Expo Talk
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SlidesLive Video |
Jennifer Neville 🔗 |
Wed 10:45 a.m. - 11:00 a.m.
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QuantumBlack: Algorithmic Fairness (Machine Learning with a Human Face)
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Expo Talk
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SlidesLive Video |
Viktoriia Oliinyk 🔗 |
Wed 10:45 a.m. - 11:45 a.m.
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Facebook Booth ( Sponsor Booth ) > link | 🔗 |
Wed 10:45 a.m. - 11:00 a.m.
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QuantumBlack Booth ( Sponsor Booth ) > link | 🔗 |
Wed 11:00 a.m. - 11:15 a.m.
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Apple: Machine Learning at Apple
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Expo Talk
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SlidesLive Video |
Lizi Ottens 🔗 |
Wed 11:15 a.m. - 11:30 a.m.
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Facebook: Future of AI-Powered Shopping
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Expo Talk
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SlidesLive Video |
Ning Zhang 🔗 |
Wed 11:30 a.m. - 12:30 p.m.
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Mentoring Room with Anna Goldenberg, University of Toronto - Two body problem in academia, raising a family, grant strategies, looking for a job, and deploying ML in a hospital setting ( Mentoring ) > link | 🔗 |
Wed 11:30 a.m. - 12:30 p.m.
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Mentoring Room with Lalana Kagal from MIT ( Mentoring ) > link | 🔗 |
Wed 11:30 a.m. - 12:30 p.m.
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Mentoring Room with Dina Obeid from Harvard - A non-linear career path in machine learning ( Mentoring ) > link | 🔗 |
Wed 11:30 a.m. - 12:30 p.m.
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Mentoring Room with Been Kim from Google Brain - Industry research and managing up ( Mentoring ) > link | 🔗 |
Wed 11:30 a.m. - 12:30 p.m.
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Mentoring Room with Shakir Mohamed from DeepMind - Socio-Technical AI Research ( Mentoring ) > link | 🔗 |
Wed 11:30 a.m. - 12:30 p.m.
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Mentoring Room with Angelique Taylor from UC San Diego - Transitioning from PhD to Assistant Professor ( Mentoring ) > link | 🔗 |
Wed 12:30 p.m. - 1:30 p.m.
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Facebook Booth ( Sponsor Booth ) > link | 🔗 |
Wed 2:00 p.m. - 2:30 p.m.
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Microsoft Booth ( Sponsor Booth ) > link | 🔗 |
Wed 3:45 p.m. - 4:25 p.m.
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Invited Talk #3 - Characterizing the Generalization Trade-offs Incurred By Compression
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Talk
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SlidesLive Video |
Sara Hooker 🔗 |
Wed 4:25 p.m. - 5:30 p.m.
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Breakout Session 3.1: Does your model know what it doesn’t know? Uncertainty estimation and out-of-distribution (OOD) detection in deep learning ( Breakout Session ) > link | 🔗 |
Wed 4:25 p.m. - 5:30 p.m.
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Breakout Session 3.5: Variational Inference for Neural Networks ( Breakout Session ) > link | 🔗 |
Wed 4:25 p.m. - 5:30 p.m.
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Breakout Session 3.2: ML Applications in Big Code ( Breakout Session ) > link | 🔗 |
Wed 4:25 p.m. - 5:30 p.m.
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Breakout Session 3.3: Connecting Novel Perspectives on GNNs: A Cross-Domain Overview ( Breakout Session ) > link | 🔗 |
Wed 4:25 p.m. - 5:30 p.m.
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Breakout Session 3.4: Bridging the gap between academia and industry ( Breakout Session ) > link | 🔗 |
Wed 4:25 p.m. - 5:30 p.m.
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Breakout Session 3.6: Responsible AI in production: Technical and Ethical considerations ( Breakout Session ) > link | 🔗 |
Wed 4:30 p.m. - 5:30 p.m.
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Salesforce Booth ( Sponsor Booth ) > link | 🔗 |
Wed 5:30 p.m. - 6:00 p.m.
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Coffee Break and Posters PM ( Poster Session ) > link | 🔗 |
Wed 6:00 p.m. - 6:25 p.m.
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Invited Talk #4 - Errors are a crucial part of dialogue
(
Talk
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SlidesLive Video |
🔗 |
Wed 6:25 p.m. - 7:30 p.m.
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Breakout Session 4.1: AI and Creativity: Approaches to Generative Art ( Breakout Session ) > link | 🔗 |
Wed 6:25 p.m. - 7:30 p.m.
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Breakout Session 4.2: Attrition of women and minoritized individuals in AI ( Breakout Session ) > link | 🔗 |
Wed 6:25 p.m. - 7:30 p.m.
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Breakout Session 4.3: Safely navigating scalability-reliability trade-offs in ML methods ( Breakout Session ) > link | 🔗 |
Wed 7:30 p.m. - 8:30 p.m.
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Panel Discussion
(
Panel Discussion
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SlidesLive Video |
🔗 |
Wed 8:30 p.m. - 8:45 p.m.
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Closing Remarks
(
Closing
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SlidesLive Video |
Sarah Osentoski 🔗 |