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Upcoming events (3)
-by Pedro Domingos, professor of computer science at the University of Washington
--your questions in advance, on tractable deep learning, machine reading, knowledge bases, more ...
About this event
Have a question on Machine Learning and related areas that has been unanswered for long? Here’s your opportunity to get insights into cutting edge research that is driving innovation. Professor, book author, and SIGKDD Innovation Award winner, Pedro Domingos will be hosting an AMA (Ask Me Anything) session with the audience of this event. Questions can be submitted
• via Twitter by using the hashtag, #DomingosAMA and tagging @vishnupendyala
• replying to this post or direct messaging
• emailing vspendyala(at)hotmail.com with #DomingosAMA in the subject
Select questions will be answered by Prof. Domingos during the session. Audience may be able to ask follow-up questions during the session.
About the Speaker
Pedro Domingos, PhD is a professor of computer science and engineering at the University of Washington and the author of The Master Algorithm. He is a winner of the SIGKDD Innovation Award and the IJCAI John McCarthy Award, two of the highest honors in data science and AI. More about him at https://homes.cs.washington.edu/~pedrod/
Vishnu Pendyala, PhD is an ACM Distinguished Speaker, Book Author, and has over two decades of experience in the software industry. He teaches Machine Learning and other Applied Data Science related courses at San Jose State University.
SCHEDULE (times in PST, in the San Francisco bay area):
6:50 connect to streaming, preregister here:
[zoom link will go here]
7:00 SFbayACM intro, upcoming events, introduce the speaker
7:10 presentation starts (~90 min with Q&A)
8:10 - 8:30 wrap up
One picture is worth a thousand words, so what have been told with videos? What about 100 simultaneous videos to reconstruct every frame of life in a[masked] sq. ft dome? Is it enough to reconstruct and digitize us realistically? Similar to other industries, the entertainment industry is also being reshaped by AI, especially towards AR/VR consumption. Before the democratization of AI and data, such immersive experiences were lacking an essential element: photorealism. As the amount of data increased, our models got deeper, and the reality became decipherable.
This talk will introduce recent deep learning advancements in 3D vision, reconstruction, and shape understanding techniques with a focus on generative models to digitize performances and scenes. Then we will shift gears with an overview of such models in 3D, and their progression on voxels, point clouds, meshes, graphs, and other 3D representations. Back to our studio, in addition to a discussion about how to process such large visual data, the challenges of scaling 10x over current capture platforms, and over 200x over state-of-the-art datasets will be presented. The talk will conclude with a sneak peek of upcoming VR/AR productions from the worlds largest volumetric capture stage at Intel Studios, as an example of real-world use cases of such AI approaches.
SPEAKER BIO: (ACM Distinguished Speaker)
Dr. Ilke Demir is based in Hermosa Beach, CA. In the overlap of computer vision and machine learning, Dr. Ilke Demir's research focuses on generative models for digitizing the real world, deep fake detection and generation techniques, analysis and synthesis approaches in geospatial machine learning, and computational geometry for synthesis and fabrication. Currently, she is a Senior Staff Research Scientist at Intel Corporation.
Dr. Demir earned her Ph.D. and M.S. in Computer Science from Purdue University advised by Prof. Daniel Aliaga, and her B.S. in Computer Engineering from Middle East Technical University with a minor in Electrical Engineering. Her Ph.D. dissertation conceives geometric and topological shape processing approaches for reconstruction, modeling, and synthesis; which pioneered the area of proceduralization. Afterwards, Dr. Demir joined Facebook as a Postdoctoral Research Scientist working with Prof. Ramesh Raskar from MIT, where their team developed the breakthrough innovation on generative street addresses. Her research further included deep learning approaches for human behavior understanding in next generation virtual reality headsets, geospatial machine learning for map creation, and 3D reconstruction at scale.
At the intersection of art and science, Dr. Demir contributed to several animated feature and VR/AR short films in Pixar Animation Studios and Intel Studios, respectively. She established the research foundations of the worldÕs largest volumetric capture studio at Intel, bridging the gap between the creative process and AI approaches.
Dr. Demir has been actively involved in women in science organisms, always being an advocate for women and underrepresented minorities.
The Association of Computing Machinery http://www.acm.org/about-acm/about-the-acm-organization is the world’s largest computing society, handling Computer Science conferences and publications. The San Francisco Bay Area ACM is a local professional chapter, a non-profit 501c(3), founded in 1957. We hold two meetups a month on (1) General Computing on the 3rd Wednesday of the month, and (2) Data Science SIG, on data mining, deep learning or big data on the 4th Monday of the month. Among these Meetups, we recently emphasis Security & Social Modeling discussions, and We generally have[masked] people attending our talks.
See also our YouTube channel (https://www.youtube.com/user/sfbayacm) with OVER 140 past talks. And you can find our Security & Social Modeling talks on YouTube playlist: https://www.youtube.com/playlist?list=PL87GtQd0bfJyVsBgkL-TyNzZhsNOYK2v_ .
In general, we are seeking speakers to book in advance. Talks could be like something you would see at a computing conference, an educational subject for experienced computing professionals. It is fine to err on the side of more technical, algorithmic or mathematical.
If you would like to submit a talk proposal, please provide the following:
* 3 available dates (DS on 4th Monday of the month) or (General Computing on 3rd Wed of the month). We skip December for talks.
* speaker name, phone, email, LinkedIn (or picture)
* talk title
* talk description (include any desired links, related reading)
* speaker bio (include any desired links)
CALL FOR PRESENTATIONS IN SECURITY & SOCIAL MODELING
1. Efficiency Gap function, insufficiency and complementariness Reference: https://www.theatlantic.com/science/archive/2018/01/efficiency-gap-gerrymandering/551492/
2. Code of Ethics in Machine Learning
3. Ethic in financial product design
4. Ethic in social data collection
5. Ethic in Patent design
6. Deep learning from Chatbots
7. Dimension reduction in social science domains
Available dates for speakers in 2021:
General Computing talks on 3rd Wed: 10/20/, 11/17/2012;
Data Science SIG talks on 4th Monday in general: 10/25/, 11/22/2021.
On the left side of the Meetup page, in the "Organizers:" box, there is a "Contact" button you can use for the submission, use "general computing", "S&S" or "DS SIG" talk at the beginning to propose your talk.
You can also contact me (Greg Makowski) about sponsorship opportunities for our non-profit organization. We are run by unpaid volunteers. If you provide financial sponsorship, sponsor food or the video recording for a night or talk series, we can offer either
a) a "thank you for the donation letter with our 501c(3) non-profit tax ID" for your tax deduction
b) "thank the sponsor" time to address the event audience during the "upcoming events" period of one of our events (7:00 - 7:10)
c) opt-in registration information of the attendees
d) "thank the sponsor" branding on the video, posted on our YouTube video channel of our talks
e) a banner in our monthly email newsletter to 6,000 opt-in bay area computing professionals or a section of our print newsletter to members only
f) make a suggestion and we can see what we can do, constrained by our volunteer effort and non-profit status.
Liana Ye, Program Chair, and Greg Makowski, Business Development Lead and Data Science SIG Chair