• Efficiently Protecting Software Innovations on a Global Scale

    -by Steve Bachmann, Bachmann Law Group Agenda 6:45 Zoom Networking stars, preregister here: https://us02web.zoom.us/webinar/register/WN_UWNmkblCRsK0IynEZZ957Q 7:00 Presentation, Streaming to SFBayACM YouTube Channel: https://www.youtube.com/watch?v=dtmk3NG40KQ Event Details To be competitive, software companies often employ designers and developers in different locations and countries to implement and update different versions of software. With this increasing workforce in other countries, software company competition can also stem from other countries, and can provide different flavors of a software product to different markets. To adapt to this developing global stage of software development, competition, and implementation, software companies should use diverse and efficient strategies to protect their innovations both where and when the protection is appropriate and makes business sense. This presentation coves strategies for efficiently protecting software innovations, both individual and families or related innovations, in the US and foreign countries. Efficient methods for protecting an innovation in different countries, from different perspectives, and utilizing trade secret and patent protection will be discussed. Real life examples will be discussed to demonstrate how to implement decisions to maximize innovation protection in a manner that aligns with the goals and budget of a company. Speaker Bio Steve Bachmann, a Bay Area native, is the founder of Bachmann Law Group PC and specializes in patent and intellectual property matters. For over 18 years, Steve has counseled clients on prosecution of U.S. and foreign patent and trademark applications, implementing trade secret programs, intellectual property (IP) portfolio development and strategy, licensing and technology transfer negotiation and drafting, open source, competitor IP analysis and investigations, and IP related due diligence. Steve has substantial experience in obtaining patent protection in numerous areas of software and hardware.‎ Steve has a worked with start-up and Fortune 500 companies and tailors IP services to each client. http://bachmann-law.com

  • Panel Discussion with Senior Data Science Recruiters (to hire or be hired)

    DESCRIPTION Join a Q&A panel discussion with three experienced recruiters focused on hiring Data Scientists. Submit questions via Zoom Q&A. This panel can help both Data Scientist job seekers as well as hiring managers. Example questions may include: For DS candidates: * What are best practices I could follow to improve my search? * What are "hot topics" (technologies or verticals) that companies are having a hard time finding? * How is the job hunt changing in COVID? For DS hiring managers: * From talking to people leaving a company, what are common reasons? * What could a hiring manager do to help retain DS staff (culture, teamwork, engagement, division of labor to deploy, benefits, career path, training, mentoring)? . . AGENDA 11:45 AM PST Zoom Networking stars, preregister here: https://us02web.zoom.us/webinar/register/WN_n7Qti6F5Si69OGLmClLYwQ 12:00 noon Panel discussion, Streaming to SFBayACM YouTube Channel . . PANELIST BIOs (in alpha order by name) Howard Fishman, Analytic Recruiting. He has been an integral part of Analytic Recruiting since joining the firm in 2004 after a long career working in senior-level roles at a number of well-known advertising agencies as a marketing executive within online/technology startups. He is a Managing Director placing professionals at all levels (junior to senior executives) in functions that span marketing analytics, database marketing, digital analytics, credit risk management, data science and more. See also: https://www.analyticrecruiting.com https://www.linkedin.com/in/howardfishmanrecruiter/ . Linda Burtch, Founder & Managing Director of Burtch Works, She is an industry leader in quantitative recruiting and began her career on the corporate side at Pepsi and Whirlpool before transitioning into recruiting and becoming a subject matter expert on the analytics and data science hiring market. Linda is a frequent speaker on quantitative career topics, and has been an active member of the Chicago Chapter of the American Statistical Association and INFORMS for years. She has maintained a popular blog on the quantitative hiring market for over 10 years. Over the past several years, Linda and Burtch Works have been repeatedly mentioned in the press, including The New York Times, The Wall Street Journal, The Economist, CNBC, The Chicago Tribune, InformationWeek, Analytics Magazine. Burtch Works is a targeted recruiting firm whose quantitative specializations range from data science and predictive analytics to marketing research and data engineering, among many others. We produce annual salary reports for DS. See also: https://www.burtchworks.com https://www.linkedin.com/in/lindaburtch/ https://www.burtchworks.com/big-data-analyst-salary/big-data-career-tips/the-burtch-works-study/ . Scott Brosnan, Executive Director of Motion Recruitment, manages the Silicon Valley branch of the specialized recruitment agency that matches top IT professionals with organizations of all sizes that hire full-time and contract candidates. Unlike typical IT staffing agencies, Motion Recruitment’s unique tech-specific team approach creates a deep understanding of the most promising technologies being used in today’s world to fit seamlessly in the local markets of the 15 major North American cities they operate in. Scott oversees all Motion Recruitment activities in Silicon Valley, after spending the better part of a decade in Boston, Chicago and San Francisco working hands-on with industry clients and candidates. Scott also manages a team focused exclusively on working with Data Scientists in the Silicon Valley market. See also: https://www.linkedin.com/in/scottbrosnan https://www.motionrecruitment.com . MODERATOR Greg Makowski, FogHorn Systems FogHorn is an IoT software startup. Greg has been deploying data science since 1992 and building DS teams since 2010 at 7 startups. https://www.linkedin.com/in/GregMakowski https://www.foghorn.io/career/data-scientist (Hiring 2 in Pune, India)

  • Silicon Valley ACM SIGGRAPH: AI-Driven Photorealistic Human Digitization

    PLEASE ALSO RSVP ON SILICON VALLEY ACM SIGGRAPH. https://www.meetup.com/SV-SIGGRAPH/events/275574816 Zoom Details To Be Announced Koki Nagano, Senior Research Scientist, NVIDIA Abstract: It is unquestionable that photorealistic digital humans will become ubiquitous in society, whether in the form of AI assistants or as fictional characters on viral media or as our own virtual self for social interactions. While currently creating a convincing digital human involves an expensive and lengthy procedure from a team of VFX experts, in the near future, anyone will be able to create photorealistic human content at their fingertips. In this talk, I present techniques to create photorealistic digital humans using 3D computer graphics and deep learning. Using the Light Stage high-fidelity capture systems, I describe how we can achieve realistic rendering of an animated face in real-time that is accurate to the level of microns. By combining cutting edge 3D graphics and deep generative models, I present methods to model, animate, and render photorealistic 3D humans from minimal inputs to bring avatar digitization to everyone. I will also showcase the applications of deep generative models for lifelike digital humans for VFX, gaming and an autonomous virtual agent. While these are key technologies for the creation of consumer accessible virtual beings, they can also be misused for malicious purposes such as the spread of disinformation. To that end, I will discuss a method to detect advanced media forgeries such as deepfakes and our efforts to fight against them. Bio: Koki Nagano is a Senior Research Scientist at NVIDIA Research. He works at the intersection of Graphics and AI with focus on achieving realistic digital humans. He has worked on a 3D display that allows an interactive conversation with a holographic projection of Holocaust survivors to preserve visual archives of the testimonies for future classrooms. His work on skin microgeometry synthesis has helped create digital characters in blockbuster movies such as "Ready Player One" and "Blade Runner 2049" as well as the open source ones such as "Digital Mike" and "Digital Emily 2.0". His work on photorealistic human digitization has been shown in places including World Economic Forum, EmTech, TEDxCharlottesville, and SIGGRAPH Real-time Live!. His work has also led to the development of the state of the art Deepfake detection technology in collaboration with top media forensics experts. He was named a Google PhD Fellow 2016 and his research has won the DC Expo 2015 Special Prize. He previously worked for Pinscreen as Principal Scientist. He obtained his PhD from the University of Southern California advised by Dr. Paul Debevec at USC ICT and his Bachelor of Engineering from the Tokyo Institute of Technology. https://luminohope.org/ Video will be posted later on YouTube

  • Panel: Practical Realities of Consulting

    Online event

    Moderated by Chris Hansen, PATCA President and founder of Covariant Corporation Agenda 6:45 Zoom Networking stars Click the link below to preregister: https://us02web.zoom.us/webinar/register/WN_dKkQh1sJSYSJ96J3CuSZZQ 7:00 Presentation, Streaming to SFBayACM YouTube Channel: Event Details Looking for new opportunities? An interactive session designed to offer insights into what it takes to launch a consulting practice and persevere. This is intended for engineers and managers who are considering a change to consulting. The panel will share their personal experience and their view on the current conditions for engineering teams in Silicon Valley. Key Take-aways • Low cost ways to get start on consulting, assessment of your experiences and certifications • How to explore where to focus your practice • Learning how to market and sell your services PATCA Panel: The Professional and Technical Consultants Association (PATCA) is Silicon Valley’s most prestigious consulting organization dedicated to serving independent consultants and the client companies that use them. • Chris Hansen, PATCA President and founder of Covariant Corporation. 20 years of experience in analysis and design of wireless communication systems, signal processing, integrated circuits, and international standards. Named inventor on over 100 issued patents. https://covariantcorp.com/ • Omar Fahmi Khalid, Consultant at Vortex Innovation Labs LLC. 20 years of experience in software development. He is a full-stack consultant fluent in Golang, Python, C++, and Javascript. https://vortexinnovationlabs.com/ • Perry West Consultant at Automated Vision Systems, Inc. Machine vision specialist working with system architecture, lighting and optics design, imaging design, and software design. https://www.autovis.com/ • Jerry Rice Consultant at FabNexus. Software development consultant for motor, thermal, fluids, optics, and signal control. Sensors and wireless networks. https://fabnexus.com/ • Rafa Baca, Esq., at https://adelanteiplaw.com/, a data scientist and lawyer who has written extensively on CS & Data Consulting in the legal field. Rafa is currently leading the charge for legal consulting credentials for Software Professionals in the State of California.

  • Deep Networks Are Kernel Machines

    Online event

    -by Pedro Domingos, professor of computer science at the University of Washington Agenda 6:45 Zoom Networking stars, preregister here: https://us02web.zoom.us/webinar/register/WN_jrX_1f0iTF6djRiNpXNgSQ 7:00 Presentation, Streaming to SFBayACM YouTube Channel: ABSTRACT: Deep learning's successes are often attributed to its ability to automatically discover new representations of the data, rather than relying on handcrafted features like other learning methods. In this talk, however, Pedro Domingos will show that deep networks learned by the standard gradient descent algorithm are in fact mathematically approximately equivalent to kernel machines, a learning method that simply memorizes the data and uses it directly for prediction via a similarity function (the kernel). This greatly enhances the interpretability of deep network weights, by elucidating that they are effectively a superposition of the training examples. The network architecture incorporates knowledge of the target function into the kernel. The talk will include a discussion of both the main ideas behind this result and some of its more startling consequences for deep learning, kernel machines, and machine learning at large. For his 2020 paper behind this talk, see: "Every Model Learned by Gradient Descent Is Approximately a Kernel Machine" at https://arxiv.org/abs/2012.00152 BIO: Pedro Domingos is a professor of computer science at the University of Washington and the author of "The Master Algorithm", the worldwide bestseller introducing machine learning to a broad audience. 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, and a Fellow of the AAAS and AAAI. His research spans a wide variety of topics in machine learning, artificial intelligence, and data science. He helped start the fields of statistical relational AI, data stream mining, adversarial learning, machine learning for information integration, and influence maximization in social networks. https://homes.cs.washington.edu/~pedrod/ https://www.amazon.com/Master-Algorithm-Ultimate-Learning-Machine-ebook/dp/B012271YB2

  • AI Trust: Adversarial Attacks on AI ML models and defenses against attacks

    By Bhairav Mehta, Principal Manager at Microsoft in Azure Core Operating System and Security Agenda 6:45 Zoom Networking stars Click the link below to preregister: 7:00 Presentation, Streaming to SFBayACM YouTube Channel: Machine learning (ML) is making incredible transformations in critical areas such as finance, healthcare, and defense, impacting nearly every aspect of our lives. Many businesses, eager to capitalize on advancements in ML, have not scrutinized the security of their ML systems. Cyber-attacks can penetrate and fool AI systems. Trusted AI systems provide ability to detect and provide protection against adversarial attacks while understanding how issues with data quality impact system performance. With the rapid developments of artificial intelligence (AI) and deep learning (DL) techniques, it is critical to ensure the security and robustness of the deployed algorithms. Recently, the security vulnerability of DL (Deep Learning) algorithms to adversarial samples has been widely recognized. The fabricated samples can lead to various misbehaviors of the DL models while being perceived as benign by humans. Successful implementations of adversarial attacks in real physical-world scenarios further demonstrate their practicality. Hence, adversarial attack and defense techniques have attracted increasing attention from both machine learning and security communities and have become a hot topic in recent years. We will present the attack and defense method. We will also demonstrate these attacks on real life business models published on Public cloud and explain remediations one should consider. Speaker Bio Bhairav Mehta is a Principal Manager at Microsoft working on projects and products related to this topic in Microsoft Core Operating System and Intelligent Edge team. He has pending patents on this topic. https://www.linkedin.com/in/mehtabhairav/

  • Lessons and Opportunities in Large Scale Networks and Smart Health Application

    By Dr. Chen-Nee Chuah, Electrical and Computer Engineering, U.C. Davis Agenda 6:45 Zoom networking starts, preregistration to be specified later: https://us02web.zoom.us/ 7:00 streaming to YouTube SFBay ACM channel to be specified later: Abstract: Data science and statistical/machine learning techniques can be leveraged to tackle various predictive and decision control problems in a wide range of application domains. This talk will focus on two domains: (1) large-scale networked systems such as IP backbone or wireless cellular networks, and (2) smart health applications. The first part of the talk will discuss lessons learned and opportunities in Internet measurement area. We will demonstrate how flexibility of software-defined networking (SDN) can be leveraged to adapt measurement rules based on optimal online strategies to augment traditional network inference techniques to obtain better estimates of network characteristics, such as traffic matrix or per-hop delay/loss rates. We will discuss the importance of data pre-processing, featurization, and choice of models by case studies from our prior work on detecting malicious activities in wireless networks and modeling user activity graphs on massive online social platforms. The second part of the talk focuses on opportunities and challenges that arise in applying IoTs, big data, AI, and machine learning (ML) techniques to smart health domain such as AI-assisted critical patient care or medical imaging. Specifically, we will draw examples from our on-going collaborative projects with UC Davis Medical Center, the Alzheimer Disease Center, and the MIND Institute in Sacramento. Biography: Chen-Nee Chuah is currently the Child Family Professor in Engineering at the Department of Electrical and Computer Engineering at the University of California, Davis. She received her B.S. in Electrical Engineering from Rutgers University, and her M. S. and Ph.D. in Electrical Engineering and Computer Sciences from the University of California, Berkeley. Her research interests include Internet measurements, network management, and cybersecurity. Her more recent projects focus on applying data science and intelligent learning techniques to tackle predictive and decision control problems in societal-scale networked systems, such as massive online social platforms, intelligent transportation systems, and smart health applications. Chuah has experience leading numerous funded projects as lead-PI or Co-PI from NIH, NSF, DoD, and industry, including multi-institution grants. She was a recipient of the NSF CAREER Award and was named a Chancellor’s Fellow of UC Davis in 2008. She has served as an Associate Editor for IEEE/ACM Transactions on Networking and IEEE Transactions on Mobile Computing. Chuah is a Fellow of the IEEE and an ACM Distinguished Scientist.

  • [CALL FOR SPEAKERS for: Security, Social Modeling, Data Science]

    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_ . SEEKING SPEAKERS 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 Sample titles: 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: 5/19/, 6/16/2021, Data Science SIG talks on 4th Monday in general: 5/24/, 6/28/2021. CONTACT US: 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. SPONSORSHIP OPPORTUNITIES 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. Thanks, Liana Ye, Program Chair, and Greg Makowski, Business Development Lead and Data Science SIG Chair