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2nd Women in Machine Learning Un-Workshop

The 2nd WiML virtual Un-Workshop is co-located with virtual ICML on Wednesday July 21st, 2021.

Machine learning is one of the fastest growing areas of computer science research. Search engines, text mining, social media analytics, face recognition, DNA sequence analysis, speech and handwriting recognition, healthcare analytics are just some of the applications in which machine learning is routinely used. In spite of the wide reach of machine learning and the variety of theory and applications, it covers, the percentage of female researchers is lower than in many other areas of computer science. Most women working in machine learning rarely get the chance to interact with other female researchers, making it easy to feel isolated and hard to find role models.

The annual Women in Machine Learning Workshop is the flagship event of Women in Machine Learning. This technical workshop gives female faculty, research scientists, and graduate students in the machine learning community an opportunity to meet, network and exchange ideas, participate in career-focused panel discussions with senior women in industry and academia and learn from each other. Underrepresented minorities and undergraduates interested in machine learning research are encouraged to attend. We welcome all genders; however, any formal presentations, i.e. talks and posters, are given by women. We strive to create an atmosphere in which participants feel comfortable to engage in technical and career-related conversations. The workshop started at the 2006 Grace Hopper Celebration and moved to NeurIPS in 2008. A History of WiML poster was created in 2015 to celebrate the 10th workshop.

This is the 2nd WiML Un-Workshop and is co-located with ICML. This event along with ICML are virtual events due to COVID-19.

The term “un-workshop” is based on the concept of an “un-conference”, a form of discussion on a pre-selected topic that is primarily driven by participants. The overall goal of the un-workshop is to advance research through collaboration and increased interaction among participants from diverse backgrounds. Different from the workshop, the un-workshop’s main focus is topical breakout sessions, with short invited talks and casual, informal poster presentations.

Besides this un-workshop and annual workshop which is co-located with NeurIPS, Women in Machine Learning also organizes events such as lunch at AAAI conference, maintains a public directory of women active in ML, profiles the research of women in ML, and maintains a list of resources for women working in ML.

Invited Speakers

This un-workshop takes place virtually due to COVID-19. Please check the program book for a complete overview of the program. info desk and tech support

If you have general questions or technical difficulties on the day of the event, drop by the window on the workshop page on

Best Practices for virtual events

Virtual conferences can be tricky, and there are a lot of unintuitive ways to make your experience (and the experience of others) a little better. You can read some of our tips here.

Information on Talks, Panel and Breakout Sessions

We will be hosting the talks, panel as a Zoom webinar. We will also host breakout sessions on Zoom. You can join these sessions by clicking the links on the ICML Un-Workshop webpage. As an attendee, you will not be able to unmute yourself. If you have questions about the content of the talk, please submit the questions using the Zoom Q&A feature. Time permitting, and depending on the volume of questions, the moderator will either ask your question for you or confirm with you to ask the question yourself and unmute you at a suitable time. Note that Q&A will be moderated by us so you will only be able to see some of the questions of the other attendees. If you want to send messages to the moderators during the seminar, please use the Zoom chat feature.

If you have not used Zoom before, we highly recommend downloading and installing the Zoom client before the meeting. Additional instructions on how to use Zoom during a webinar can be found here.

Information on Poster Session and Mentorship Social

The WIML Un-Workshop poster session, mentorship social and The Joint Affinity Groups Poster Session takes place in Gather.Town. You can join these sessions by clicking the links on the ICML Un-Workshop webpage. See Gather.Town guidelines to troubleshoot common access issues. If you face any issues, check these common video/audio issues or Gather.Town FAQ.

An Important Note on ICML Registration

Please note that the application form does not constitute registration for the WiML Un-Workshop. To attend the un-workshop, you need to register for ICML at There is no separate registration for the un-workshop.

The 2021 WiML Un-Workshop at ICML will be held virtually on Wednesday, July 21th, 2021. WiML will also participate in the ICML Affinity Groups Joint Poster Session with Queer in AI on Monday, July 19th.


All participants are required to abide by the WiML Code of Conduct.

Please use this link to access the Un-Workshop on ICML.
Wednesday, July 21th, 2021

Time (ET/New York) - Event

09:40 – 09:50: Introduction and Opening Remarks

09:50 – 10:00: WiML D&I Chairs Remarks

10:00 – 10:25: Invited talk – Yingzhen Li

10:25 – 11:30: Breakout sessions #1

11:30 – 12:00: Virtual Coffee Break and Poster Session #1

12:00 – 12:25: Invited Talk – Celia Cintas

12:25 – 13:30: Breakout Sessions #2

13:30 – 14:30: Sponsor Expo: Presentations by Microsoft, QuantumBlack, Apple, and Facebook

14:30 – 15:30: Mentoring Social

15:30 – 18:45: Break + Informal Social

18:45 – 19:25: Invited Talk – Sara Hooker

19:25 – 20:30: Breakout Sessions #3

20:30 – 21:00: Virtual Coffee Break and Poster Session #2

21:00 – 21:25: Invited Talk – Luciana Benotti

21:25 – 22:30: Breakout Sessions #4

22:30 – 23:30: Panel Discussion – Sarah Dean, Sarah Aerni, Sylvia Herbert, Kalesha Bullard, Amy Zhang (moderator)

23:30 – 23:45: Closing Remarks


Our sponsor booths are open during the Un-Workshop. Please find information on their schedules and events here.

For more details about the breakout sessions (e.g. affiliations), please use this link.

You can submit your questions to the panelists through this link.

Breakout session #1, 10:25 AM – 11:30 AM ET

ID - Session title - Leaders - Facilitators

1.1 Catching Out-of-Context Misinformation with Self-supervised LearningShivangi AnejaMamatha Thota, Vishwali Mhasawade

1.2 School mapping using computer vision technologySafa SulimanMaryam Daniali

1.3 Data Integration and Predictive Modeling for Precision Medicine in OncologyMehreen Ali
Esther Oduntan

1.4 Unsupervised Learning in Computer VisionAyca Takmaz, Clara Fernandez Labrador
Naina Dhingra

1.5 Machine Learning for Privacy: An Information Theoretic PerspectiveEcenaz Erdemir, Fatemehsadat Mireshghallah
Cemre Cadir

1.6 Fundamentals of Contrastive Learning in VisionSamrudhdhi Rangrej, Ibtihel Amara, Zahra Vaseqi
Farzaneh Askari

1.7 Exploring probabilistic sparse inferencing through the triangulation of neuroscience, computing and philosophyGagana B, Stuti Gupta

Akash Smaran

1.8 Neural Machine Translation for Low-Resource LanguagesEn-Shiun Annie Lee, Surangika Ranathunga, Rishemjit Kaur, Marjana Prifti SkenduliNiti M KC, Jivat Neet Kaur


Breakout session #2, 12:25 PM – 1:30 PM ET

ID - Session title - Leaders - Facilitators

2.1 Geometry and Machine LearningMelanie WeberAnkita Shukla

2.2 Leveraging Open-Source Tools for Natural Language ProcessingJennifer Glenskii RanaAneri Rana, Niti M KC

2.3 Challenges and Opportunities in ML for Health Care: How to address interpretability in clinical decision making?Annika Marie Schoene, En-Shiun Annie Lee, Peiyuan Zhou

Malinda Vania

2.4 Leading the Way for the Next Generation of Black Women in STEMLouvere Walker-Hannon, Dr. Tracee Gilbert
Mozhgan Saeidi

2.5 Un-bookclub Algorithms of OppressionRajasi Desai, Esther Oduntan, Anoush Najarian
Sindhuja Parimalarangan

2.6 Research within community: how to cultivate a nurturing environment for your researchRosanne LiuMehreen Ali

2.7 Explainable machine learning: do we have the right tools?Michal Moshkovitz, Chhavi Yadav
Shreya Ghosh

2.8 Decision-Making in Social Settings: Addressing Strategic Feedback EffectsMeena Jagadeesan, Celestine Mendler-Dünner
Frances Ding


Breakout session #3, 7:25 PM – 8:30 PM ET

ID - Session title - Leaders - Facilitators

3.1 Does your model know what it doesn’t know? Uncertainty estimation and out-of-distribution (OOD) detection in deep learningJie Ren, Polina Kirichenko, Sharon Yixuan Li, Sergul Aydore, Haleh Akrami
Liyan Chen

3.2 ML Applications in Big CodeSonia Kim, Mozhgan Saeidi
Shima Shahfar

3.3 Connecting Novel Perspectives on GNNs: A Cross-Domain OverviewIlke Demir, Nesreen Ahmed, Vasuki Narasimha Swamy, Subarna Tripathi
Ancy Tom

3.4 Bridging the gap between academia and industryChip Huyen, Sharon Zhou
Sasha Luccioni

3.5 Variational Inference for Neural NetworksSahar Karimi, Audrey Flower
Gargi Balasubramaniam

3.6 Responsible AI in production: Technical and Ethical considerationsParul Pandey, Himani Agrawal
Wanda Wang


Breakout session #4, 9:25 PM – 10:30 PM ET

ID - Session title - Leaders - Facilitators

4.1 AI and Creativity: Approaches to Generative ArtAneta NeumannAncy Tom

4.2 Attrition of women and minoritized individuals in AIJeff Brown, Christine Custis, Madu Srikumar, Himani AgrawalJeff Brown, Christine Custis, Madu Srikumar

4.3 Safely navigating scalability-reliability trade-offs in ML methodsRuqi Zhang, A. Feder CooperMonica Munnangi


Sponsor Expo Presentations, 1:30 PM – 2:30 PM ET

Time (ET/New York) - Sponsor - Speaker - Title

13:30 – 13:45 Microsoft Jennifer Neville Improving Productivity with Graph ML over Content-Interaction Networks

13:45 – 14:00 Quantum Black Viktoriia Oliinyk Algorithmic Fairness: Machine Learning with a Human Face


14:00 – 14:15 Apple Lizi Ottens Machine Learning at Apple

14:15 – 14:30 Facebook Ning Zhang  Future of AI-Powered Shopping


Mentorship Social, 2:30 PM – 3:30 PM ET

ID - Mentor - Topic

1 Dina Obeid (Harvard) A non-linear career path in Machine Learning

2 Shakir Mohamed (DeepMind) Socio-Technical AI Research

3 Been Kim (Google Brain) Industry Research and Managing Up

4 Anna Goldenberg (U Toronto) Two body problem in academia, Raising a family, Grant strategies, Looking for a job to deploying ML in a hospital setting

5 Lalana Kagal (MIT) Maintaining work-life balance


6 Angelique Taylor (Cornell University) Transitioning from PhD to Assistant Professor

Invited talk: Celia Cintas

Towards fairness & robustness in machine learning for dermatology

Abstract: Recent years have seen an overwhelming body of work on fairness and robustness in Machine Learning (ML) models. This is not unexpected, as it is an increasingly important concern as ML models are used to support decision-making in high-stakes applications such as mortgage lending, hiring, and diagnosis in healthcare. Currently, most ML models assume ideal conditions and rely on the assumption that test/clinical data comes from the same distribution of the training samples. However, this assumption is not satisfied in most real-world applications; in a clinical setting, we can find different hardware devices, diverse patient populations, or samples from unknown medical conditions. On the other hand, we need to assess potential disparities in outcomes that can be translated and deepen in our ML solutions. In this presentation, we will discuss how to evaluate skin-tone representation in ML solutions for dermatology and how we can enhance the existing models’ robustness by detecting out-out-distribution test samples (e.g., new clinical protocols or unknown disease types) over off-the-shelf ML models.



Invited talk: Yingzhen Li

Evaluating approximate inference for BNNs

Abstract:Bayesian Neural Network is one of the major approaches for obtaining uncertainty estimates for deep learning models. Key to the success is the selection of the approximate inference algorithms used to compute the approximate posterior, with mean-field variational inference (MFVI) and MC-dropout being the most popular variants. But is the good downstream uncertainty estimation performance of BNNs attributed to good approximate inference? In this talk I will discuss some of our recent results towards answer this question. I will also discuss briefly the computational reasons of the preference of MFVI/MC-dropout and describe our latest work to make BNNs more memory efficient.



Invited talk: Sara Hooker

Characterizing the Generalization Trade-offs Incurred By Compression

Abstract: To-date, a discussion around the relative merits of different compression methods has centered on the trade-off between level of compression and top-line metrics such as top-1 and top-5 accuracy. Along this dimension, compression techniques such as pruning and quantization are remarkably successful. It is possible to prune or heavily quantize with negligible decreases to test-set accuracy. However, top-line metrics obscure critical differences in generalization between compressed and non-compressed networks. In this talk, we will go beyond test-set accuracy and discuss some of my recent work measuring the trade-offs between compression, robustness and algorithmic bias. Characterizing these trade-offs provide insight into how capacity is used in deep neural networks — the majority of parameters are used to represent a small fraction of the training set. Formal auditing tools like Compression Identified Exemplars (CIE) also catalyze progress in training models that mitigate some of the trade-offs incurred by compression.



Invited talk: Luciana Benotti

Errors are a crucial part of dialogue

Abstract: Collaborative grounding is a fundamental aspect of human-human dialogue which allows people to negotiate meaning; in this talk, I argue that current deep learning approaches to dialogue systems don’t deal with it adequately. Making errors, and being able to  recover from them collaboratively, is a key ingredient in grounding meaning, but current dialogue systems can’t do this. I will illustrate the pitfalls of being unable to ground collaboratively, discuss what can be learned from the language acquisition and dialog systems literature, and reflect on how to move forward. I will urge the community to proceed by addressing a research gap: how clarification mechanisms can be learned from data. Novel research methodologies which highlight the importance of the role of clarification mechanisms are needed for this. I will present an annotation methodology, based on a theoretical analysis of clarification requests, which unifies a number of previous accounts. Dialogue clarification mechanisms are an understudied research problem and a key missing piece in the giant jigsaw puzzle of natural language understanding. I will conclude this talk with an open call for collaborators that share the vision presented.

Call for Participation

The 2nd WiML Un-Workshop is co-located with ICML on Wednesday, July 21st, 2021.

The Women in Machine Learning will be organizing the second “un-workshop” at ICML 2021. This is an event format to encourage more participant interaction, especially with ICML going virtual this year. The un-workshop is based on the concept of an “un-conference”, a form of discussion on a pre-selected topic that is primarily driven by participants. Different from the workshop, the un-workshop’s main focus is topical breakout sessions, with short invited talks and casual, informal poster presentations.

The overall goal of the un-workshop is to advance research through collaboration and increased interaction among participants from diverse backgrounds. Students, postdocs and researchers in all areas of Machine Learning who primarily identify as a woman and/or nonbinary are encouraged to submit one-page proposal to lead a breakout session on a certain research topic.

While all presenters will identify primarily as a woman and/or nonbinary, all genders are invited to attend.


Important dates​

  • June 14th, 2021 – Application form opens

  • July 4th, 2021 – Deadline (anywhere on Earth) to apply for a breakout session, poster, registration fee funding, facilitating or volunteering

  • July 10th, 2021 – Notification of acceptance of breakout session’s proposals

  • July 10th, 2021 – Notification of acceptance of posters, registration fee funding, facilitators, volunteers

  • July 21st, 2021 – WiML Un-Workshop Day

Various ways of participating in WiML un-workshop

  • Lead a breakout session: submit a proposal to lead a breakout session on a certain research topic.

  • Facilitate a breakout session: assist breakout session leaders by taking notes and encouraging participant interactions and taking attendance.

  • Present a poster: present a poster in a casual, informal setting.

  • Volunteer: help with technical setup and in-event needs.

  • Attend: participate in breakout session discussions.

Breakout session proposals

A breakout session is a 1-hour free-form discussion overseen by 1-3 leaders and with assistance from 1-2 facilitators to take notes and encourage participant interactions. We strongly encourage students, postdocs, and researchers who primarily identify as women and/or nonbinary in all areas of machine learning to submit a proposal to lead a topical breakout session.

A complete proposal consists of a 1 page blind PDF (example here) and the names and bios of leaders submitted separately in the application form. We strongly recommend having at least 2 leaders, with a diverse set of leaders preferred (see selection criteria below). The names of facilitators can also be provided if known at submission time. Otherwise, the organizers will match facilitators to breakout sessions.

Breakout session leaders must identify primarily as women and/or nonbinary; facilitators can be of any gender. Only one proposal submission per leader is allowed. If there are multiple leaders, only one leader needs to submit the proposal. There are no proceedings.

WiML registration fee funding is prioritized for accepted breakout session leaders who fulfill certain eligibility criteria (see details below) and do not have any other sources of funding.

Breakout session guidelines:

  • Role of leaders:

    • Point-out key characteristics of your topic and make connections with other topics.

    • Describe the key challenges in this research area on a high-level.

    • Describe the key approaches on a high-level to provide intuition.

    • Highlight possible points of discussion/goals to achieve during the session.

    • Use graphics/imagery and materials e.g. slides as needed

    • Encourage inclusive (rather than unilateral) discussions

  • Role of facilitators: take notes and encourage participant interactions.

  • Leaders and facilitators should anticipate a small additional time commitment before the un-workshop to receive briefing/training and a possible dry run.

  • While the exact technology is still being determined, we anticipate using video-conferencing software (e.g. Zoom).

Submission instructions for breakout sessions:

  • Proposals must be no more than 1 page (including any references, tables, and figures) submitted as a PDF.

  • Main body text must be minimum 11 point font size and page margins must be minimum 0.75 inches (all sides).

  • Your proposal should stand alone, without linking to a longer paper or supplement.

  • You should provide a brief description of the topics you’d like to discuss, any relevant references, a plan for how you’d organize the time (1 hour) allocated for a session, as well as some ideas on how you’d encourage discussion and participant interaction during the session.

  • The PDF must not include identifying information, as it will be reviewed blind.

  • In particular, the PDF should not contain information of the leaders or facilitators. Instead, submit their information in the application form.

Selection criteria for breakout sessions:

  • The degree to which it is expected that participants will find the topic interesting and valuable.  

  • Diversity of leaders and facilitators, including diversity of experience/seniority, affiliation, race, viewpoint and thinking regarding the topic, etc. 

  • Plans for encouraging discussion and participant interaction during the session.


If you are interested in facilitating a breakout session but have not yet connected with anyone submitting a breakout session proposal, you can indicate your interest in the application form. Organizers will match selected facilitators to breakout sessions. Facilitators should anticipate a small additional time commitment before the un-workshop to receive briefing/training and a possible dry run.


If you wish to present a poster, submit EITHER a short abstract (max 1500 characters) OR a PDF of the poster (only if you have it already). The poster may describe new, previously, concurrently published, or work-in-progress research. Posters in theory, methods, and applications are welcome. 

The poster presenter must identify primarily as a woman and/or nonbinary; other authors can be of any gender. The poster presenter does not need to be the first author of the work. Only one poster submission per presenter is allowed.

Accepted posters will be presented in a casual, informal setting. This setting is very different from formal poster sessions, e.g. at WiML Workshop at NeurIPS. While the exact presentation format is still being determined, it may be as simple as a webpage with poster PDF and pre-recorded video. There are no oral or spotlight presentations. There are no proceedings.

Submission instructions for posters:

  • Submitted materials may contain identifying information, as posters for this un-workshop are not reviewed blind.

  • Your submission should stand alone, without linking to a longer paper or supplement.

  • You should convey motivation and give some technical details of the approach used.

  • While we acknowledge that space is limited, some experimental results are likely to improve reviewers’ opinions of your poster.

Registration fee funding

The virtual nature of ICML and this un-workshop allows individuals from all over the world to attend. By funding a number of ICML registrations, WiML hopes to further expand the range of participants at this un-workshop.

To apply for funding, you should:

  1. identify primarily as a woman and/or nonbinary;

  2.  be a student, postdoc, or have an equivalent position (equivalent positions include unemployed recent grads and early career researchers from underrepresented geographical regions).

Accepted breakout session leaders who fulfill the above eligibility criteria and do not have any other sources of funding will be prioritized for WiML funding. Other participants are also encouraged to apply. Priority will be given to individuals from underrepresented regions or groups, first-time attendees of ICML or similar conferences, and individuals who would benefit the most from this funding.

Funding recipients must participate in at least one breakout session as a leader, facilitator, or attendee.

Due to limited funding, we may not be able to support everyone eligible; however, we hope to support as many eligible applicants as possible.

We also encourage you to apply for ICML volunteer and funding opportunities, which are separate and independent of WiML funding. Check the ICML website directly for details.


We are seeking volunteers to help with technical setup and virtual technology testing before the event, as well as help during the event, e.g. letting people into Zoom rooms, etc. We may also need emergency reviewers for breakout session proposals. You can indicate if you can help in any way in the application form here.

Participation instructions

To participate in ANY of the above roles and/or apply for registration fee funding, please fill in this application form by **July 4, 2021**. Selected breakout session leaders, facilitators, poster presenters, volunteers, and funding recipients will be notified individually by the dates mentioned above.

If you only wish to attend, we still recommend you fill in this form to provide your timezone and topic preferences. All participants are required to abide by the WiML Code of Conduct.

Important note: This form does not constitute registration for the WiML Un-Workshop. To attend the un-workshop, you need to register for ICML at

Submission is now open!


  • Beliz Gokkaya, Facebook

  • Wenshuo Guo, University of California, Berkeley

  • Arushi Majha, University of Cambridge

  • Liyue Shen, Stanford

  • Olivia Choudhury, Amazon

  • Berivan Isik, Stanford

  • Hadia Mohmmed Osman Ahmed Samil, Mila

  • Vaidheeswaran Archana, Continental Automotive

Questions? Check out the FAQs or reach us at workshop[at]wimlworkshop[dot]org


Diversity and Inclusion Chair

Danielle Belgrave, Principal Research Manager at Microsoft Research


We would like to acknowledge and warmly thank our super-volunteers who worked tirelessly to ensure a high quality un-workshop.
Belen Saldias, MIT
Elre Oldewage, University of Cambridge
Mandana Samiei, McGill and Mila
Niveditha Kalavakonda, University of Washington Seattle
Weiwei Zong, Henry Ford Health System

How do I register for the un-workshop?

You need to register to ICML to attend to WiML and then please fill the application form provided. Please refer to call for participation for more details.

Is filling the application form enough for register to WiML?

No, you need to register to ICML.

What is an un-workshop?

The un-workshop is based on the concept of an “un-conference”, a form of discussion on a pre-selected topic that is primarily driven by participants.

The overall goal of the un-workshop is to advance research through collaboration and increased interaction among participants from diverse backgrounds. 

How is an un-workshop different from WiML workshop at NeurlPS?

WiML Workshop at NeurIPS is a one-day event with invited speakers, oral presentations, and posters. This year WiML is bringing a new event format to ICML to encourage more participant interaction, especially with ICML going virtual this year.

Different from the workshop, the un-workshop’s main focus is topical breakout sessions, with short invited talks and casual, informal poster presentations.

I'm a man. Can I attend WiML?

Yes. All genders are welcome to attend! To do so, please register for ICML and fill the application form. Note, however, that all speakers, breakout session leaders and poster presenters will primarily identify as a woman and/or nonbinary, as our goal is to promote them and their work within the machine learning community.

Where will the un-workshop take place?

This is a virtual event.

How much funding is available?

Funding is distributed based on geographic location. Support varies from year to year and this year due to COVID-19, it will be a virtual event and ICML registration fee funding is available for participants who fulfill eligibility criteria.

Is there a code of conduct?

Yes. WiML requires all participants and reviewers to abide by our code of conduct.

Is WiML an archival venue?

No, WiML is a non-archival venue. This means that, if your contribution is accepted, we will not be asking you to submit a camera-ready version of it, nor will we publish it anywhere (neither online nor in proceedings of any sort). We will only make the title and authors’ names available in the program book.


How can I get more information on un-workshop logistics?

Please check out the logistics page!


I want to support WiML by providing sponsorship / recruiting at the un-workshop. Who should I talk to?

Thank you for your support! Please contact us.

How can I join the WiML network?

Join our Google Group.

When and where do I submit my proposal?

You can find more information on call for participation. Submission to the 2021 WiML un-workshop is now closed.

How many breakout sessions will be on the day of the un-workshop?

There are 4-time slots for 1-hour breakout sessions (marked as Breakout Sessions #1 to #4). Each of these 4-time slots will have several parallel breakout sessions.

Why do breakout sessions involve Zoom and Slack?

Zoom rooms are mainly for the breakout sessions for the specific one hour period. However, leaders can use Slack a few days before and after to ask participants to read some papers, ask them specific questions and keep the discussions going. Also, participants can ask questions regarding the breakout session’s topic in the Slack channel before the actual session.

Can I make breakout rooms in the breakout session as a leader?

Yes, leaders can make smaller breakout rooms to engage participants in smaller group discussions.

How many attendees will be in each breakout session?

We can’t promise the exact number but we are hoping for smaller groups (max 20) to increase interaction between participants.

What is the whiteboard in Zoom rooms?

Whiteboard is like a digital board and leaders and participants can write on it and explain a specific topic. More instructions are available here.

Will we as leaders be given a chance to advertise our proposal topic before the un-workshop?

Sure, you can advertise your session’s topic on Twitter for example and tag us on @WiMLworkshop and we can retweet that. Also, attendees will have access to the breakout session topics at least a week before the un-workshop.

Can anyone who did not fill the WiML form still join the un-workshop?

Anyone who is registered to ICML can join the un-workshop.

I am new to the platform being used for the live poster session. How can I prepare for it?

Check out these guidelines.

I have a question that's not answered here. How do I reach you?

Contact us.

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