Live-Stream


How to Stand Out in a Virtual World: Reflections on Job Searches by Former IEEE Students

3 December, 1:00 pm EDT

Speaker: Panel of IEEE Young Professionals

Mike Mournighan will be one of several young professionals, all past IEEE Student Branch Chairs at their universities, who will share their recent and ongoing experience navigating their careers in a virtual world. Mike graduated from Columbia University in '13 (BS) and '15 (MS) in EE. In 2015 he left NYC for Austin, Texas to work for Silicon Labs, who he hosted several times as IEEE student chair. In early 2020, after leading firmware development efforts in IEEE802.bt Power over Ethernet controllers (Si3474/Si3471), he transitioned into a Systems Engineering role at Apple. Despite being at Apple in-person for only 2 weeks before lockdown, he was able to ramp up and play a crucial role in shipping the iPad8 on time in Sept. He misses travel (but not traffic); performing live comedy; and gathering in-person, but has found new joy in recording and streaming his video game sessions. Mike will be joined by a panel of several other former IEEE Students who will share their stories with the membership.

Speaker Bios

Natalia Baklitskaya
Nat is an Engineering Manager at Better.com, one of the fastest growing home ownership startups in the country. Prior to Better, she worked as a hardware and software engineer at both very large companies and small startups. Nat originally comes from the hardware world, having graduated from Columbia University as an Electrical Engineering major. Nat has been involved in the IEEE community from her college days and throughout her professional life. She has served as Chair of the Columbia University IEEE Student Branch and later as Chair of the Santa Clara Valley Women in Engineering (SCV WIE) board. Nat stays engaged with the IEEE community by giving talks and facilitating workshops at various IEEE conferences and events, such as Rising Stars, Future Leaders Forum, and local events.

Likhitha Patha
Likhitha comes from a Technical Program/Product Management background. She's currently leading the Technical Program Management team for Twitter's centralized Machine Learning organization called Twitter Cortex. For the past year, she served as a White House Presidential Innovation Fellow to help build digital tools and services for the American public. Prior to that, she worked as a Senior Technical Program Manager at Amazon's Alexa AI on Natural Language Understanding stack and as a Product Manager at Microsoft's Intune for Education and Visual Studio products. She was the IEEE Student Branch Chair at Virginia Tech, where she earned her bachelor’s degree in Electrical Engineering. She is currently working part-time toward her MS in Computer Science at Georgia Tech.

Mike Mournighan
Mike Mournighan graduated from Columbia University in '13 (BS) and '15 (MS) in EE. In 2015 he left NYC for Austin, Texas to work for Silicon Labs, who he hosted several times as IEEE student chair. In early 2020, after leading firmware development efforts in IEEE802.bt Power over Ethernet controllers (Si3474/Si3471), he transitioned into a Systems Engineering role at Apple. Despite being at Apple in-person for only 2 weeks before lockdown, he was able to ramp up and play a crucial role in shipping the iPad8 on time in Sept. He misses travel (but not traffic); performing live comedy; and gathering in-person, but has found new joy in recording and streaming his video game sessions.

Christopher R. Ellis
Christopher R. Ellis has a bachelors in electrical engineering with a focus in power electronics from University of California, San Diego. While an undergrad he created an IEEE Student Branch at his community college, before transferring and serving as an IEEE officer at UC San Diego, including serving as the Chair in his final year. Chris also received the IEEE PES scholarship for 2 years, including being named a Schweitzer Meritorious Scholar his senior year. Post graduation, he has worked as a power systems engineer at Lockheed Martin and is currently the CTO of a startup company called SparkCharge. At SparkCharge he leads the design of their portable electric vehicle charging solutions including a compact 20kW DC fast charger and patented modular battery technology.

Abstract:

GPU/accelerator architectures have greatly improved the training and inferencing speed for neural-network-based machine learning models. As major industry players race to develop ambitious applications such as self-driving vehicles, unstructured data analytics, human-level interactive systems, and human intelligence augmentation, major challenges remain in computational methods as well as hardware/software infrastructures required for these applications to be effective, robust, responsive, accountable and cost-effective. These applications impose much higher levels of data storage capacity, access latency, energy efficiency, and throughput. In this talk, I will present a vision for building a new generation of computing components and systems for these applications.

Speaker’s Bio:

Wen-mei W. Hwu is a Professor and holds the Sanders-AMD Endowed Chair in the Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign. He is the director of the IMPACT research group (www.crhc.uiuc.edu/Impact). He co-directs the IBM-Illinois Center for Cognitive Computing Systems Research (C3SR) and serves as one of the principal investigators of the NSF Blue Waters Petascale supercomputer. For his contributions, he received the ACM SigArch Maurice Wilkes Award, the ACM Grace Murray Hopper Award, the IEEE Computer Society Charles Babbage Award, the ISCA Influential Paper Award, the IEEE Computer Society B. R. Rau Award and the Distinguished Alumni Award in Computer Science of the University of California, Berkeley. He is a fellow of IEEE and ACM. Dr. Hwu received his Ph.D. degree in Computer Science from the University of California, Berkeley.

Description

The Low Power Image Recognition Challenge (LPIRC) 2019 is a one-day workshop that will extend the successes of LPIRC from the past four years, identifying the best computer vision solutions that can simultaneously achieve high accuracy and energy efficiency. Since the first competition, held in 2015, the winners’ solutions have improved 24x in the ratio of accuracy divided by energy.

The live-stream of LPIRC will feature presentations from researchers and last year's winner (all times PDT):

09:30-09:40 - Welcome by Organizers and Summary of Online Challenge

09:40-10:30 - 2018 competition winners will give a talk on their winning solutions — Amazon's Tao Sheng, and Expasoft's Alexander Goncharenko and Sergey Alyamkin

10:30-11:10 - Invited Talk: Rethinking the Computations in Computer Vision (and the Hardware that Computes Them) - UC Berkeley's Kurt Keutzer

11:10-13:40 - Live-stream will shut down temporarily

13:40-14:00 - Invited Talk: Visual Wake Words Challenge - Google's Aakanksha Chowdhery and Pete Warden

Additional Supporting Details

  • Additional Speaker

    Title, Company

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  • Additional Speaker

    Title, Company

    Brownie sesame snaps candy canes. Wafer muffin powder chocolate bear claw bonbon pastry. Topping caramels carrot cake marshmallow soufflé icing.

  • Additional Speaker

    Title, Company

    Brownie sesame snaps candy canes. Wafer muffin powder chocolate bear claw bonbon pastry. Topping caramels carrot cake marshmallow soufflé icing.

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  • Brownie sesame snaps candy canes. Wafer muffin powder chocolate bear claw bonbon pastry. Topping caramels carrot cake marshmallow soufflé icing.

    > Read More

  • Brownie sesame snaps candy canes. Wafer muffin powder chocolate bear claw bonbon pastry. Topping caramels carrot cake marshmallow soufflé icing.

    > Read More

  • Brownie sesame snaps candy canes. Wafer muffin powder chocolate bear claw bonbon pastry. Topping caramels carrot cake marshmallow soufflé icing.

    > Read More

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