Salomey Osei · Bonaventure F. P. Dossou

A social with keynote speakers, and a panel discussion. The main objective would be to learn more about African Languages, related ongoing research, and initiatives.

Hunar Batra · Kelsey Doerksen · Nele Quast

"Our session aims to highlight the distinguished work of several Wom*n Researchers in machine learning. From ML for Space, ML for healthcare, interpretability, climate change, and more, we’ll have you covered with this exciting research and discuss about further possibilities along with established researchers in the field."

Nicole Bannon · Brian Liou · Crystal Lee

"Webinar and Q&A on How to Negotiate Industry Offers in AI. Some of the topics we discuss are: * What the standard recruiting process looks like * How to choose the best job offer for career growth * When/how you should negotiate * When should you walk away from a job offer * When can an offer be rescinded from negotiating"

Jayeeta Putatunda

"Did you read about LaMDA, what do you think about the claims that it has become sentient! Will the transformer models save the world just that Transformer Optimus Prime did? What are your opinions about the BLOOM model? Seems like the era of NLP is here with these super successful large language models breaking all benchmark scores that the big tech companies are producing, some even in association with other big techs! Long live this collaboration! In this social, we will aim to look at the rapid rise, the progress of NLP models, the tasks Transformers had made the greatest impact, and the road ahead! This will be an informal session where I will try to walk through a few examples from different industries like adtech/fintech and use-cases and would appreciate an open discussion on other use-cases from the participants!"

Yi Wan · Alex Ayoub

An artificial general intelligence (AGI) agent is capable of achieving general goals. An agent that reasons about generality is complicated. The world the AGI is interacting with, however, is much more complicated than the agent itself. Further, the agent only observes a part of the world at a time and thus needs to construct its own summary of the past and the summary is the agent’s subjective state. All components that the agent has, except the one that generates the agent’s state, take the agent’s state as input and generate desired outputs. What components the agent should maintain and how the specific components interact with each other are two fundamental questions. Specific questions arise from these two fundamental questions. For example, what are good agent states and what are bad ones? What should the world model take and produce? Are sub-tasks necessary? What sub-tasks are good and what are bad? These questions are about designing architecture and identifying the purposes of each component in the architecture, rather than specific ways to implement each component. Our social welcomes everyone who is interested in brainstorming such an architecture design.

Adam Cobb

An opportunity to meet others in the community who work on quantum machine learning and/or quantum-inspired machine learning. It will be very informal, with a few pointers placed on the tables to help start discussions.

Louvere Walker-Hannon

Maternal mortality continues to be a global issue however, studies over the past 5 years identify a growing alarming trend in the United States with respect to maternal mortality. According to several studies from the Centers for Disease Control, “Black women are three times more likely to die from a pregnancy-related cause than White women”. Many of these same studies have also acknowledged that most pregnancy-related deaths are preventable and that this alarming trend continues to grow. This session will entail providing an overview of both past and current recommendations that are being used to address this issue which did not entail the usage of technology. Recent studies will also be identified that have indicated that Artificial Intelligence (AI) could be used to reduce Black maternal mortality. An exploration of how AI can be used to reduce Black maternal mortality and to advocate for further study of this topic will also be highlighted as a part of this session. During this session through conversation, dedicated reflection time, and creation of action plans we as a community will have an opportunity to explore what are ways that AI in conjunction with other resources can be used to address this ongoing and …

Hongming Zhang · Yiyuan Li

This social event will discuss current progress on commonsense knowledge acquisition and application with large models. Specifically, two invited speakers will be introducing their recent work on finding the knowledge bottleneck in pre-trained language models and commonsense knowledge discovery. After that, we will have a casual panel discussion to discuss some open questions regarding commonsense knowledge.

Haohan Wang · Sarah Tan · Chirag Agarwal · Chhavi Yadav · Jaydeep J Borkar

A social to build a community for friends who are interested in trustworthy machine learning topics defined to the broadest scopes. Join us to meet the peers who might have read your papers or the peers you have read papers from, to know new friends who are interested in exploring topic in this dimension, and to build new collaboration opportunities

Sindhuja Parimalarangan · Rachna Tatachar · Pavithra Ashok Kumar · Anoush Najarian

We’d love to come together for an un-bookclub at ICML. We’ve been learning a lot in the cross-continental book club out of the book Haben: The Deafblind Woman Who Conquered Harvard Law.

We’d love to give you the gift of connection, conversation, and reflection Haben gave us. We’ll invite Haben to stop by if she can (things are uncertain in the pandemic). We ask you to watch Haben's powerful talk at the National Book Festival in preparation:

Haben Girma, the author of the book, defines disability as an opportunity for innovation. She learned non-visual techniques for everything from dancing salsa to handling an electric saw. She developed a text-to-braille communication system that created an exciting new way to connect with people. Haben pioneered her way through obstacles, graduated from Harvard Law, and now uses her talents to advocate for disabled people.

Join us for a discussion on accessibility and intersectionality in the tech industry, and the roles and responsibilities of the machine learning community in building a culture where disabled people thrive."

Victor Silva · Huan Zhang · Nathaniel Rose · Arjun Subramonian · Krunoslav Lehman Pavasovic · Ana Da Hora

A joint social with researching affinity groups Black in AI and Queer in AI celebrating the work of queer and black scientists. These events seek to fostercollaborations and mentorship among people from both communities, and discuss initiatives to increase the presence of black and queer people in the field of Artificial Intelligence.

Mah Parsa · sepid parsa

Artificial intelligence (AI) has strengthened its progress, and AI positions are the top emerging jobs worldwide; however, the talented women, who could help AI organizations achieve their ambitions, have been underrepresented in the field. The 2020 World Economic Forum report has shown that women account for only 26% of data and AI positions in the workforce. On the other hand, About two percent of the world's population suffers from various types of mental health disorders. Psychological health problems, e.g., depression, are among the ten principal causes of disability in all countries. Due to the large scale of the problem, tackling it falls under one of the 17 sustainable development goals of the United Nations. Thus, it is critical to foster research partnerships that result in the development of AI-driven solutions to measure, diagnose, and treat mental and neurodegenerative disorders.

To promote women's roles in AI for mental health application, we aim to organize a virtual social event for international women in AI and ML and a physical, social event for women in AI and ML in Montreal: Establish informal science relationships with women researchers in AI research centers around the world. Facilitate formal technology partnerships with women CEOs and women …

Patrick R Perrine

In this in-person, 2-hour Social, we pair participants together based on differing types of experience in related subdisciplines of ML. These pairings would be determined by a confidential online form that participants would fill out upon entering the Social. For example, suppose Researcher A identifies as being highly experienced in Reinforcement Learning but has little to no experience in Optimization. Researcher A could then be paired with Researcher B, who has a great background in studying Optimization but has had no exposure to Reinforcement Learning. This cycle could repeat every 15 minutes so that every participant can meet a diverse set of researchers across a multitude of subdisciplines. The Social would end with a round table discussion talking about the various topics that they learned about and how it could influence their research moving forward.

Paula Gradu · Cyril Zhang

A roundtable participant-led discussion on how to ensure the mental wellbeing of our community: from preventing and dealing with burnout and maintaining a healthy work-life balance to brainstorming ways in which we could better support peers struggling with their mental health or advising situations. While we will be discussing possibly heavy topics, the focus will be on the positive actions we can all take to foster a mentally healthy ML academic community.

Olga Isupova · Yunpeng Li · Ivan Kiskin

Enjoy an evening full of fun and wisdom with 8 leading AI/ML scientists and engineers to debate whether progress towards achieving AI will be mostly driven by engineering or science. You will be joined by Pulkit Agrawal (MIT), François Charton (Meta), Kyunghyun Cho (NYU), Sujoy Ganguly (Unity Technologies), Maya Gupta (Didero), Been Kim (MIT), Ida Momennejad (Microsoft), and Sella Nevo (Google) who will debate the topic following the British Parliament Style. We will also host live votes right before and after the debate to see whether you are convinced by our debaters!

Nicole Bannon · Brian Liou · Crystal Lee

"Webinar and Q&A on How to Negotiate Industry Offers in AI. Some of the topics we discuss are: * What the standard recruiting process looks like * How to choose the best job offer for career growth * When/how you should negotiate * When should you walk away from a job offer * When can an offer be rescinded from negotiating"

Abhishek Singh · Mohammad Mohammadi Amiri · Ayush Chopra

Do you have a crazy idea about Machine Learning? Have you figured out AGI? Or an algorithm to generate personalized memes? Pitch your crazy idea in this ICML social. We invite attendees to pitch their fun, crazy or wild ideas relevant to the ICML audience. Every speaker would give a 2-minute presentation/pitch to the audience.

Mementor Beta

The Mementor portal should help us scheduling spontaneous virtual mentor sessions during ICML and beyond. Our goal is to enable mentorship opportunities for researchers in machine learning, both as mentors and mentees, with a special focus on under-represented minorities.

Our initial goal is to provide a platform to support conversations between mentors and mentees. The mode of operation initially will be a “lighter” version, where a mentor, at a time of their convenience, has a video call, which everybody willing as a mentee can join. No person-to-person commitment.

The mentorship session serves as a platform to share experiences. These could be technical and research related (e.g., research topics and technical discussions), or could be about scientific communication (e.g., paper writing, presentation, networking), or could also be mental health, burnouts, work ethics, PhD life etc. The goal is to facilitate sharing of experiences between members of the community which would not happen otherwise.

Note: The mentorship sessions are not a platform for self-promotion or promotion of products.