November 2022 - Ececourtesy-list

Guest Speaker Seminar: "Computational imaging/photography research at Snap Research", Jian Wang (Snap Research), Tuesday, November 22 at 12PM, Virtual
by Hodges, Kendra Renee 17 Nov '22

17 Nov '22

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Zoom Info: https://purdue-edu.zoom.us/j/96390812481?pwd=NVRZekErTVdDTUk2Nk90cGVuRkpYZz… [cid:image001.png@01D8FA77.80520220] Kendra Hodges | Administrative Assistant Elmore Family School of Electrical and Computer Engineering Purdue University Materials and Electrical Engineering Building 501 Northwestern Avenue, Suite 150 West Lafayette, Indiana 47907 Phone: 765-494-3540 Email: khodges(a)purdue.edu [download]

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Physical Chemistry Seminar Speaker: Professor Kieron Burke
by Hodges, Kendra Renee 15 Nov '22

15 Nov '22

Please see below seminar dates for Professor Kieron Burke. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ PLEASE NOTE: These are two separate seminars for Professor Kieron Burke. Please join us Wednesday, November 16th, 2022 for the Physical Chemistry Seminar. When: Wednesday Where: BRWN 4102 and Zoom https://purdue-edu.zoom.us/j/93195456102<https://www.google.com/url?q=https://purdue-edu.zoom.us/j/93195456102&sa=D&…> Meeting ID: 931 9545 6102 Time: 12:30 PM Speaker: Professor Kieron Burke (University of California Irvine) Title: "Density Functional Theory and its Semiclassical Origins" Abstract attached. _____________________________________________________________ Department of Mathematics Colloquium, Kieron Burke, UC Irvine, LWSN B151 Tuesday, Nov 15th 3:30 - 4:30pm Title: Important mathematical questions in density functional theory Abstract: I will discuss density functional theory, the theory behind most modern electronic structure calculations in science today. Improvements in the approximations in current use can have enormous impact in many technological applications. I will discuss functional analysis, algorithmic development, and even optimal transport. But then I will focus on asymptotic analysis of density functionals, which is becoming increasingly important in the development of approximations. I will outline some formidable mathematical challenges, where any progress would be extremely useful. Libby Zupancic Administrative Assistant Physical and Biochemistry Research Areas Department of Chemistry WTHR 265 Purdue University 560 Oval Drive West Lafayette, IN 47907-2084 lzupanci(a)purdue.edu<mailto:lzupanci@purdue.edu> 765-494-9264

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Happening Now: ECE Distinguished Seminar Series: Dr. Ming Zhang, Synopsys
by Jurss, Karen L 11 Nov '22

11 Nov '22

MSEE 289 (Chiminski Family Collaborative Research Space) ________________________________ From: Amelia Katherine Bragg <bragg14(a)purdue.edu<mailto:bragg14@purdue.edu>> Sent: Monday, November 7, 2022 8:09:42 AM To: ecefaculty(a)ecn.purdue.edu<mailto:ecefaculty@ecn.purdue.edu> <ecefaculty(a)ecn.purdue.edu<mailto:ecefaculty@ecn.purdue.edu>> Subject: ECE Distinguished Seminar Series: Dr. Ming Zhang When: Friday, November 11, 2022 9:00 AM-10:00 AM. Where: MSEE 289 C [cid:image001.jpg@01D8F5AC.5CFFFD10]Dear ECE Colleagues, Next week on Friday, November 11th we will be welcoming Dr. Ming Zhang from Synopsis as a part of the "ECE Distinguished Seminar Series." The talk will be held in the Chiminski Demonstration Space, MSEE 289C from 9:00 a.m. - 10:00 a.m. Please note that although a Zoom link is provided for those who cannot make it to the talk, but in-person attendance is strongly encouraged. Zoom Link: https://purdue-edu.zoom.us/j/98599683019 Best, Amelia Bragg

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CompE Seminar Series: Dr. Tarek Abdelzaher, UIUC: Real-time Intelligent Edge Services for Internet of Things Applications
by Satterfield, Mary Ann 09 Nov '22

09 Nov '22

https://purdue-edu.zoom.us/j/93166268645?pwd=UlpSYWtqbTh3WFdHNEdQL29ELy9ldz… Meeting ID: 931 6626 8645 ~ Passcode: 800947 [cid:image001.png@01D8F46E.E9149610]

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TODAY: CompE Seminar Series: Azam Ikram: Root Cause Analysis of Failures in Microservices through Causal Discovery; BHEE 317 / Zoom, 12:00 Noon
by Satterfield, Mary Ann 08 Nov '22

08 Nov '22

Root Cause Analysis of Failures in Microservices through Causal Discovery Azam Ikram Advised by Prof. Saurabh Bagchi https://purdue-edu.zoom.us/j/93166268645?pwd=UlpSYWtqbTh3WFdHNEdQL29ELy9ldz… Meeting ID: 931 6626 8645 Passcode: 800947 Abstract: Most cloud applications use a large number of smaller sub-components (called microservices) that interact with each other in the form of a complex graph to provide the overall functionality to the user. While the modularity of the microservice architecture is beneficial for rapid software development, maintaining and debugging such a system quickly in cases of failure is challenging. We propose a scalable algorithm for rapidly detecting the root cause of failures in complex microservice architectures. The key ideas behind our novel hierarchical and localized learning approach are: (1) to treat the failure as an intervention on the root cause to quickly detect it, (2) only learn the portion of the causal graph related to the root cause, thus avoiding a large number of costly conditional independence tests, and (3) hierarchically explore the graph. The proposed technique is highly scalable and produces useful insights about the root cause, while the use of traditional techniques becomes infeasible due to high computation time. Our solution is application agnostic and relies only on the data collected for diagnosis. For the evaluation, we compare the proposed solution with a modified version of the PC algorithm and the state-of-the-art for root cause analysis. The results show a significant improvement in top-k recall while significantly reducing the execution time. Bio: I am a second-year Ph.D. student at ECE Purdue University working with Prof. Saurabh Bagchi. I'm broadly interested in large-scale distributed systems, cloud computing, computer networks, and applied machine learning in systems. My current research work focuses on providing fault diagnosability for cloud applications through causal inference. Another part of my work concentrates on making the serverless framework more applicable to the end user by reducing the latency and cost of serverless DAGs. Before joining Purdue, I was at LUMS where I worked with Prof. Zafar Ayyub Qazi to improve the latency of cellular control plane messages of 4G/LTE. Mary Ann Satterfield Sr. Administrative Assistant Elmore Family School of Electrical and Computer Engineering Electrical Engineering Building 465 Northwestern Ave., BHEE 326B West Lafayette, IN 47907 o: 765-494-6389 m: 765-490-6392 f: 765-494-2706 [BB871DD1]<https://www.purdue.edu/?utm_source=signature&utm_medium=email&utm_campaign=…>

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CompE Seminar Series: Azam Ikran: Root Cause Analysis of Failures in Microservices through Causal Discovery
by Satterfield, Mary Ann 07 Nov '22

07 Nov '22

Root Cause Analysis of Failures in Microservices through Causal Discovery Azam Ikram Advised by Prof. Saurabh Bagchi Abstract: Most cloud applications use a large number of smaller sub-components (called microservices) that interact with each other in the form of a complex graph to provide the overall functionality to the user. While the modularity of the microservice architecture is beneficial for rapid software development, maintaining and debugging such a system quickly in cases of failure is challenging. We propose a scalable algorithm for rapidly detecting the root cause of failures in complex microservice architectures. The key ideas behind our novel hierarchical and localized learning approach are: (1) to treat the failure as an intervention on the root cause to quickly detect it, (2) only learn the portion of the causal graph related to the root cause, thus avoiding a large number of costly conditional independence tests, and (3) hierarchically explore the graph. The proposed technique is highly scalable and produces useful insights about the root cause, while the use of traditional techniques becomes infeasible due to high computation time. Our solution is application agnostic and relies only on the data collected for diagnosis. For the evaluation, we compare the proposed solution with a modified version of the PC algorithm and the state-of-the-art for root cause analysis. The results show a significant improvement in top-k recall while significantly reducing the execution time. Bio: I am a second-year Ph.D. student at ECE Purdue University working with Prof. Saurabh Bagchi. I'm broadly interested in large-scale distributed systems, cloud computing, computer networks, and applied machine learning in systems. My current research work focuses on providing fault diagnosability for cloud applications through causal inference. Another part of my work concentrates on making the serverless framework more applicable to the end user by reducing the latency and cost of serverless DAGs. Before joining Purdue, I was at LUMS where I worked with Prof. Zafar Ayyub Qazi to improve the latency of cellular control plane messages of 4G/LTE.

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