All events WiML Social @ ICLR 2024 Vienna, Austria May 8, 2024 12:45PM Date: May 08th, 2024 (Wed.) Time: 12:45 PM- 2:15 PM Place: Hall B, Messe Wien Exhibition Congress Center@Vienna, Austria The topic of the panel will be AI Unplugged: Navigating Everyday Life & Professional Paths. During the panel, we aim to facilitate discussions on various topics, such as mentorship advice and how AI t echnologies are impacting personal and professional domains. Program: 12:45 – 12:50 PM Opening Remarks - Tatjana Chavdarova (WiML board) 12:50 – 1:25 PM Networking & Lunch 12:50 – 1:00 PM Icebreaker games 1:00 – 1:25 PM Networking themed roundtables 1:25 – 2:15 PM Panel discussion: “AI Unplugged: Navigating Everyday Life & Professional Paths” PANELISTS Bahare Fatemi Bahare Fatemi is a Research Scientist at Google Research in Montreal, specializing in graph representation learning and natural language processing. She received her Ph.D. From the University of British Columbia. Her work has been featured in top AI conferences and journals including NeurIPS, ICLR, AAAI, and JMLR. She co-organized the Mining and Learning with Graphs workshop at KDD, Women in Machine Learning (WiML) workshop, and the Montreal AI Symposium. Devi Parikh Devi Parikh, an Associate Professor at Georgia Tech's School of Interactive Computing, previously served as Senior Director of Generative AI at Meta until March 2024. Her diverse career includes roles as Director at Meta's FAIR lab, Assistant Professor at Virginia Tech, and Research Assistant Professor at TTIC. She has held visiting positions at esteemed institutions such as Cornell, UT Austin, Microsoft Research, MIT, Carnegie Mellon, and Facebook AI Research. Her research focuses on generative AI, AI for creativity, multimodal AI, and human-AI collaboration. She boasts numerous awards, including NSF CAREER, Sloan Research Fellowship, and IJCAI Computers and Thought award, among others. Priya Donti Priya Donti is an Assistant Professor and the Silverman (1968) Family Career Development Professor at MIT EECS and LIDS. Her research focuses on machine learning for forecasting, optimization, and control in high-renewables power grids. Priya is also the co-founder and Chair of Climate Change AI, a global nonprofit initiative to catalyze impactful work at the intersection of climate change and machine learning. Priya received her Ph.D. in Computer Science and Public Policy from Carnegie Mellon University. She hold several awards and fellowships including the MIT Technology Review’s 2021 “35 Innovators Under 35” award and the ACM SIGEnergy Doctoral Dissertation Award. MODERATOR Aya Abdelsalam Ismail Aya Abdelsalam Ismail is a research scientist at Prescient Design in the frontier group. Prior to Prescient, she received her Ph.D. from the University of Maryland where she was advised by Soheil Feizi and Héctor Corrada Bravo. During her Ph.D. her research focused on the interpretability of neural models for sequential data. WiML SOCIAL ORGANIZERS Yutong Zhou Yutong Zhou is a Postdoc Researcher at the Leibniz Centre for Agricultural Landscape Research (ZALF), Germany. Her research interests focus on computer vision and deep learning, particularly in Generative Models, Multi-modal Vision and Language. She is concentrating on Artificial Intelligence × Biodiversity × Smart agriculture, surrounding the goals of ‘Global Sustainability for Better AI’ and ‘AI for Best Global Sustainability’. Lisa Weijler Lisa Weijler is a PreDoc researcher at the Computer Vision Lab (CVL), TU Wien, Austria. Her research interests are computer vision and machine learning for 3D and unstructured data, especially point clouds. Additionally, she is passionate about combining her research with medical, social or political science in interdisciplinary projects. She has applied her research for cancer cell detection in pediatric leukemia patients as well as for methodological advancements like SE(3) equivariant convolutions or OOD 3D scene understanding. Her main research focus currently is open vocabulary 3D scene understanding. WiML BOARD ORGANIZERS Hewitt Tusiime – WiML ICLR liaison Erin Grant – D&I chair Tatjana Chavdarova – VP Events WiML Thanks to our sponsors! Previous Next

All events WiML Luncheon @ ICML 2016 New York, New York June 21, 2016 12:00 pm — 02:00 pm WiML is hosting a luncheon at ICML 2016 in New York, New York. This event gives female faculty, research scientists, data scientist, and graduate students in the machine learning community an opportunity to meet, exchange ideas and learn from each other. Date: Tuesday, June 21, 2016, 12pm-2pm Venue: Microsoft building (5th floor), 11 Times Square, New York Registration: https://www.eventbrite.com/e/wiml-icml-luncheon-2016-tickets-25415537557# If you see any errors or omissions or have any information to contribute to this page, please contact us at info@wimlworkshop.org SPONSORS -Silver- -Bronze- Previous Next

17th Women in Machine Learning Workshop (WiML 2022) 17th Women in Machine Learning Workshop (WiML 2022) The Workshop is co-located with NeurIPS on Monday, November 28th, 2022 at the New Orleans Convention Center in Louisiana, USA. Speakers Logistics Program Call for Participation Committee FAQ 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 Un-Workshop is the flagship event in un-conference style of Women in Machine Learning , primarily intended to foster active participant engagement in the program. 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. Now in its 4th year, the 2023 un-workshop is co-located with IC ML . Besides this annual un-workshop, Women in Machine Learning also organizes annual workshop at NeurIPS, events such as lunch or social at the AISTATS or AAAI conferences, 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. All participants are required to abide by the WiML Code of Conduct . I'm a paragraph. Click here to add your own text and edit me. It's easy. Invited Speakers Location Type of registration required to attend PROGRAM PANELISTS BREAKOUT SESSIONS COFFEE MEET & MINGLE SOCIAL Program Monday, November 28, 2022 [ in-person ] ( Time in CT) Morning Session 7:30 am - 8:30 am Registration & Breakfast 8:30 am - 8:45 am Opening Remarks - Konstantina Palla (Senior Program Chair) 8:45 am - 9:00 am D&I Chair remarks - Danielle Belgrave 9:00 am - 9:10 am Contributed talk ( Tejaswi Kasarla ) - "Maximum Class Separation as Inductive Bias in One Matrix" 9:10 am - 9:20 am Contributed talk ( Taiwo Kolajo ) - "Pre-processing of Social Media Feeds based on Integrated Local Knowledge Base" 9:20 am - 9:55 am Invited talk - Alice Oh - " The importance of multiple languages and multiple cultures in NLP research " 9:55 am - 10:10 am Coffee break 10:10 am - 10:25 am WiML Board Remarks - Jessica Schrouff 10:25 am - 11:00 am Invited talk - Raesetje Sefala - " Constructing visual datasets to answer research questions " 11:00 am - 11:10 am Contributed talk ( Pascale Gourdeau ) - "When are Local Queries Useful for Robust Learning?" 11:10 am - 11:20 am Contributed talk ( Annie S Chen ) - "You Only Live Once: Single-Life Reinforcement Learning" 11:20 am - 1:20 pm Mentorship roundtables & Lunch - Mentors: Adam Roberts, Stephanie Hyland, Bianca Zadrozny, Sima Behpour, Mercy Asiedu, Franziska Boenisch, Eleni Triantafillou, Isabela Albuquerque, Yisong Yue, Amy Zhang, Zelda Mariet, Tristan Naumann, Danielle Belgrave, Shakir Mohamed, Tong Sun, Gintare Karolina Dziugaite, Samy Bengio, Rianne van den Berg, Maja Rudolph, Luisa Cutillo, Ioana Bica, Clara Hu, Rosanne Liu, Jennifer Wei, Alice Oh, SueYeon Chung, Erin Grant, Sasha Luccioni, Michela Paganini, Mounia Lalmas-Roelke, Claire Vernade, Alekh Agarwal, Neema Mduma, Vinod Prabhakaran, Savannah Thais, Jonathan Frankle, Ce Zhang, Rose Yu, Jessica Schrouff, Bo Li, Katherine Heller, Ben Poole, Setareh Ariafar, Christina Pavlopoulou, Isabel Morlidge, Kavya Srinet, Cheng Zhang, Elise van der Pol, Diana Montanes, Lise Diagne, Le Yu, Megan Forrester. Afternoon Session 1:20 pm - 1:55 pm Invited talk - Bianca Zadrozny - " Machine Learning for Climate Risk " 1:55 pm - 2:05 pm Contributed talk ( Elizabeth Bondi-Kelly ) - "Human-AI Interaction in Selective Prediction Systems" 2:05 pm - 2:15 pm Contributed talk ( Gowthami Somepalli ) - "Investigating Reproducibility from the Decision Boundary Perspective." 2:15 pm - 2:35 pm Coffee break 2:35 pm - 3:10 pm Invited talk - Hima Lakkaraju - " A Brief History of Explainable AI: From Simple Rules to Large Pretrained Models " 3:10 pm - 4:10 pm Panel discussion 4:10 pm - 4:20 pm Closing Remarks 4:20 pm - 4:30 pm Poster setup 4:30 pm - 6:00 pm Joint Affinity Groups Poster Session Mentorship Roundtables AI and Creativity: Adam Roberts (Google Brain) Choosing between Academia and Industry: Stephanie Hyland (Microsoft Research) and Bianca Zadrozny (IBM Research) Continual Learning & Open-World Learning: Sima Behpour (Bosch) Founding and Funding Startups: Mercy Asiedu (Google) Gender-related challenges: Franziska Boenisch (Vector Institute) Generalization & Robustness: Eleni Triantafillou (Google Brain) and Isabela Albuquerque (DeepMind) Getting a job (academia): Yisong Yue (Caltech) and Amy Zhang (UT Austin) Getting a job (industry): Zelda Mariet (Google) Healthcare/clinical applications: Danielle Belgrave (DeepMind) and Tristan Naumann (Microsoft Research) Leadership: Shakir Mohamed (DeepMind) and Tong Sun (Adobe) Learning theory: Karolina Dziguaite (Google Brain) Life in industry research: Samy Bengio (Apple) and Rianne van den Berg (Microsoft Research) Life with kids: Maja Rudolph (BCAI) and Luisa Cutillo (University of Leeds) Mental health & surviving in grad school: Ioana Bica (DeepMind), Clara Hu (Google Brain), and Rosanne Liu (Google Brain) ML for Science: Jennifer Wei (Google) Natural language processing: Alice Oh (KAIST) Negotations in ML: Nicole Bannon (81cents) Neuroscience & cognitive science: Erin Grant (UCL), SueYeon Chung (NYU/Flatiron Institute), and Noga Zaslavsky Non-traditional paths in machine learning: Sasha Luccioni (HuggingFace) and Michela Paganini (DeepMind) Recommender systems: Mounia Lalmas-Roelke (Spotify) Reinforcement learning: Claire Vernade (DeepMind), Alekh Agarwal (Google), and Elise van der Pol (Microsoft Research) Seeking funding in academia: Neema Mduma (The Nelson Mandela African Institution of Science and Technology) Social science applications: Vinod Prabhakaran (Google Research), Savannah Thais (Columbia University), and Sarah Brown (University of Rhode Island) Systems and machine learning: Jonathan Frankle (Harvard University/MosaicML) and Ce Zhang (ETH Zurich) Time Series: Rose Yu (UCSD) Trustworthy machine learning: Jessica Schrouff (DeepMind), Bo Li (UIUC), and Katherine Heller (Google Research) Monday, December 5, 2022 [virtual](Time in ET) 9:30 am - 9:40 am Opening Remarks 9:40 am - 9:55 am Contributed talk ( Okechinyere J Achilonu ) - "Natural language processing for automated information extraction of cancer parameters from free-text pathology reports" 9:55 am - 10:10 am Contributed talk ( Paula Harder ) - "Physics-Constrained Deep Learning for Climate Downscaling" 10:10 am - 10:25 am Contributed talk ( Silvia Tulli ) - "Explanation-Guided Learning for Human-AI collaboration" 10:25 am - 10:40 am Contributed talk ( Mina Ghadimi Atigh ) - "Hyperbolic Image Segmentation" 10:40 am - 10:50 am Set up (for mentorship session) 10:50 am - 11:50 am Mentorship Panel (Discussion + Q&A) withJenn Wortman Vaughan (Microsoft Research),Colin Raffel (University of North Carolina)Kristen Grauman (University of Texas at Austin) 11:50 am - 12:00 pm Break 12:00 pm - 12:35 pm Sponsor Talks 2:00 pm - 4:00 pm Joint Affinity Groups Poster Session Call for Participation PLATINUM SPONSORS PLATINUM SPONSORS PLATINUM SPONSORS Committee ORGANIZERS WiML RECEPTION ORGANIZER ADVISORY SUPER VOLUNTEERS FAQs

< Back Kate Niehaus, PhD WiML Director (2018-2020)

< Back Tamara Broderick, PhD WiML Director (2013-2019) Visit my Profile

All events WiML Symposium @ ICML 2024 Vienna July 24, 2024 Symposium The WiML Symposium at ICML will occur on Wednesday, July 24th, 2024 at the Messe Wien Exhibition Congress Center, Vienna, Austria. For more information or to register, please go here. Previous Next

< Back Jane Wang, PhD WiML Director (2020-2022)

All events 4th WiML Mentorship Program for Job Seekers: Panel on Applying to Jobs in Machine Learning Virtual November 18, 2024 9:00 am - 10:00 am This event, part of the WiML’s 2024-2025 Mentorship Program on the theme of Industry Jobs Applications, takes place 9-10am PT in Zoom. Mentors and mentees of the 2024-2025 Mentorship Program are invited to attend. Panelists: Dr. Kaoutar El Maghraoui (IBM Research), Jaya Shankar (Nvidia), Catherine Breslin (Kingfisher Labs) Moderator: Anoush Najarian (MathWorks) We will cover: Overview on career pathways in Machine Learning and AI Key tips and advice to apply to jobs in the industry sector, including improving your CV and writing a cover letter Building your skills and tips on the emerging trends in Machine Learning Building your personal network Q&A session to answer participant questions Previous Next

< Back Amy Zhang, PhD WiML Director (2020-2022)

< Back Claire Vernade WiML Director