ACM BALTIMORE CHAPTER 3RD SEMINAR
Thursday, August 11, 2022
CALL FOR PARTICIPATION
ACM BALTIMORE CHAPTER SEMINAR 2022
REMOTE AND IN-PERSON
JOHNS HOPKINS UNIVERSITY APPLIED PHYSICS LAB, USA
5:30 PM – 8:00 PM (EST), THURSDAY, AUGUST 11, 2022
ACM, the Association for Computing Machinery, is the world’s largest educational and scientific computing society, uniting educators, researchers and professionals to inspire dialogue, share resources and address the field’s challenges. The Baltimore ACM Professional Chapter was recently formed to help organize monthly seminar, professional meetings and networking events, professional development workshops, and provide collaboration opportunities with computing organizations and research labs in the DC, Maryland and Virginia area. ACM Baltimore Chapter is scheduled to organize the third seminar on Thursday, August 11, 2022.
JOIN FREE: The registration is FREE!
AGENDA
(Talks will be Streamed Live/All Times are US Eastern Time)
| 5:30 PM – 5:50 PM EST | Networking and Refreshment |
| 5:50 PM – 6:00 PM EST | Welcome Address and ACM Baltimore Chapter Update |
| 6:00 PM – 6:50 PM EST | Invited Talk: Common Issues and Challenges in AI for Cybersecurity (Prof. Raj Jain, Barbara J. and Jerome R. Cox, Jr. Professor of Computer Science and Engineering, Washington University in Saint Louis) |
| 6:50 PM – 7:00 PM EST | BREAK |
| 7:00 PM – 7:50 PM EST | Invited Talk: A Study in Real World Data Races in Go Lang (Albert Greenberg, Vice President of Platform Engineering at Uber) |
| 7:50 PM – 8:00 PM EST | Future plans and Vote of Thanks |
JOIN FREE: The registration is FREE!
Johns Hopkins University Applied Physics Laboratory
(JHU/APL), 201-117, 11091 Johns Hopkins Road,
Laurel, MD 20723 Visitor’s Information
FREE REGISTRATION
Free registration (in-person and remote) is open
click here to register
https://edas.info/registerPerson.php?c=29426
Register through Eventbrite: bit.ly/ACM-Baltimore-11Aug-Register
On behalf of ACM Baltimore Chapter
Ashutosh Dutta, Chair, ACM Baltimore Chapter
Contact: Ashutosh.Dutta@jhuapl.edu or +1 908-642-8593
REMOTE/ ONLINE AVAILABILITY
Remote attendees can join the seminar via online using the Zoom link given below
TINY URL: bit.ly/ACM-Baltimore-11Aug
ID: 161 570 4794 PASSWORD: 918613
More details about Baltimore ACM Chapter can
be found: https://baltimore.acm.org
Common Issues and Challenges in AI for Cybersecurity
AI is everywhere. It is being applied to security as well. In our research on the security of medical and industrial IoT over the last 5 years, we have noticed several common mistakes, challenges, and issues in applying AI and securing IoT. In this talk, we will discuss nine such common issues and mistakes.
Raj Jain is currently the Barbara J. and Jerome R. Cox, Jr., Professor of Computer Science and Engineering at Washington University in St. Louis. Dr. Jain is a Life Fellow of IEEE, a Fellow of ACM, a Fellow of AAAS, and a recipient of the 2017 ACM SIGCOMM Life-Time Achievement Award. Previously, he was one of the Co-founders of Nayna Networks, Inc., a Senior Consulting Engineer at Digital Equipment Corporation in Littleton, Mass, and then a professor of Computer and Information Sciences at Ohio State University in Columbus, Ohio. With 38,000+ citations, according to Google Scholar, he is one of the highly cited authors in computer science. Further information is at http://www.cse.wustl.edu/~jain/
A Study in Real World Data Races in Go Lang
The concurrent programming literature is rich with tools and techniques for data race detection. Less, however, has been known about real-world, industry-scale deployment, experience, and insights about data races. Golang (Go for short) is a modern programming language that makes concurrency a first-class citizen. Go offers both message passing and shared memory for communicating among concurrent threads. Gois gaining popularity in modern microservice-based systems. Data races in Go stand in the face of its emerging popularity. In this paper, using our industrial code base as an example, we demonstrate that Go developers embrace concurrency and show how the abundance of concurrency alongside language idioms and nuances make Go programs highly susceptible to data races. Google’s Go distribution ships with a built-in dynamic data race detector based on ThreadSanitizer. Dynamic race detectors pose scalability and flakiness challenges; we discuss various software engineering tradeoffs to scale this detector to work effectively at scale. We have deployed this detector in our 50-million lines of Go codebase hosting 2100 distinct microservices, found over2000 data races, fixed over 1000 data races, spanning 790 distinct code patches submitted by 210 unique developers over a six-month period. Based on a detailed investigation of these data race patterns in Go, we make seven high-level observations relating to the complex interplay between the Go language paradigm and data races.
Albert Greenberg is Vice President of Platform Engineering at Uber, leading the engineering and program management teams responsible for data center, compute, networking, storage, data, search, monitoring, developer productivity, engineering DEI, tooling and corporate IT infrastructure. In this role, Albert is the executive sponsor for the company’s community of senior engineers who drive the evolution of Uber’s Engineering architecture, culture, and standards to be considerably more effective, reliable, and sustainable. Uber’s Platform Engineering has offices in the Bay Area, Seattle, New York; Aarhus, Denmark; Vilnius, Lithuania; Hyderabad and Bangalore, India.
In addition to sitting on the company’s executive leadership team, Albert also serves as a member of Uber’s Artificial Intelligence Law & Ethics Council. Prior to Uber, Albert spent 15 years at Microsoft, as Technical Fellow and Corporate Vice President for Microsoft Azure Networking, leading software and hardware development and engineering across Microsoft Azure, spanning all physical and virtual networking and services, from each virtual or physical connection, on down to the global fiber. Within Azure, Albert founded and led the network virtualization, datapath and physical data center network teams in Azure, as well as other teams in networking and monitoring. Prior to joining Azure, he worked at Microsoft Research to invent and incubate the data center networking technologies now widely deployed in Microsoft services and products, such as Virtual Layer-2 (VL2), Virtual Networks (VNets), Clos datacenter networks (Monsoon), Load Balancing (Ananta), Data Center TCP (DCTCP). Albert joined Microsoft from Bell Labs and AT&T Labs Research, where he was an AT&T Fellow and Executive Director, and where he helped build the systems and tools for engineering and managing AT&T’s networks. He is the winner of the IEEE Kobayashi Award, the ACM Sigcomm Award, a winner of multiple ACM Test of Time Paper awards, and distinguished alumni of Unive
More details about Baltimore ACM Chapter can be found: https://baltimore.acm.org