Loading Events

« All Events

  • This event has passed.

GRASP/ PRECISE Industry Symposium 2018

May 21 @ 3:50 am

The GRASP Lab and the PRECISE Center will host a 1-1/2 day symposium of leading executives and engineering involved in cutting-edge robotics, cyber-physical systems and Internet of Things. Prominent speakers from industry and academia will be featured, along with ample networking opportunities with GRASP and PRECISE students, alumni and industry representatives.

The GRASP/PRECISE Industry Symposium will be held on February 2nd-3rd, 2018 in the Wu & Chen Auditorium and Pennovation. Additional event details and the agenda are below.



Hotel Information

The Study at University City
20 S. 33rd St, Philadelphia, PA 19104
Please call the reservations coordinator, Sakiyna Muhammad, at 215-398-1869 and ask for the “GRASP/PRECISE Industry Day” Penn rate. 

Valet parking is available at $39.00 per overnight with in and out privileges. Event parking is $18.00 per car and can be posted to a master account. 

Walking directions from The Study at University City to Levine Hall are below. Click on “more options” to see the complete Google map.


Thursday, February 1st

18:30 Invited Speakers’ Dinner with GRASP/PRECISE Faculty (*Invitation Only)
20:30 – 21:30 Special Seminar by Justin Gottschlich (Intel) in Levine 307
“The Future of Anomaly Detection”

Friday, February 2nd – Wu & Chen Auditorium  Levine Hall

8:15 – 9:00 Breakfast & Registration  (Levine Hall First Floor Lobby)
9:00 – 9:05 Welcome Message – Kathleen Stebe
Deputy Dean for Research and Innovation, SEAS
9:05 – 10:00 GRASP Lab Research Presentations
10:00 – 10:50 PRECISE Center Research Presentations
10:50 – 11:50 Morning Keynote Speaker: Parris Wellman (Amazon Robotics)
“The Future is Humans and Robots Working Together”
(Talk Information Below)
11:50 – 12:00 SEAS Outreach Programs – Daniel Miller-Uueda 
Associate Director Education and Outreach, SEAS
12:00 – 13:30 Lunch / Student Poster Session & Demos (Levine Hall First Floor Lobby)
13:30 – 14:20

Industry Presentations (Theme: Transportation)
Session Chair: Rahul Mangharam

BaekGyu Kim (Toyota)
“Design Challenge of Open Software Platform for Connected Vehicles”
Andrew King (Zoox)
“Autonomous Mobility for the Future”
Robert Bourg (Wabtec Freight)
“Positive Train Control”
Ashish Kapoor (Microsoft Research)
“What’s new in AirSim?”
Justin Gottschlich (Intel)
“Deep Learning for Autonomous Driving”

14:20 – 14:30  Break
14:30 – 15:20 Afternoon Keynote Speaker: Ben Firner (NVIDIA)
“Accelerating Autonomous Vehicles with Deep Learning”
(Talk Information Below)
15:20 – 15:30  Break 
15:30 – 16:20

Industry Presentations (Theme: AI / IOT / CPS)
Session Chair: Joe Devietti

Gian Luca (Draper)
“Autonomous Perception and Localization at Draper”
Bongho Kim (Nokia)
“Wireless Communications for IoT”
Yoonsoo Lee (National Grid)
“Modeling Our Future: The Energy Path Forward”
Shwetha Shetty (SAP)
“Getting Enterprises to the Cutting ‘Edge’”

16:20 – 16:30 Break
16:30 – 17:20

Industry Presentations (Theme: Robotics)
Session Chair: Daniel Koditschek

Pulkit Kapur (Mathworks)
“Advanced Robotics with MATLAB and Simulink”
Brad Neuman (Anki)
“Creating Robots with Character”
Alex Kushleyev (Qualcomm)
“Robotics @ Qualcomm Research Philadelphia”
Edward Tunstel (UTRC)
“Robotics at UTRC”UTRC”

17:20 – 17:30 Closing Remarks – Daniel Lee & Insup Lee
Directors, GRASP Lab & PRECISE Center (respectively)
17:30 – 18:30 Reception & Industry Networking

Saturday, February 3rd – Pennovation & PERCH

8:30 – 10:00  Breakfast
9:00 – 11:30 Rapid Interview Session (Invite Only)
9:30 – 10:30 Tour of PERCH (Sign-up Required)


Morning Keynote Speaker

Dr. Parris S. Wellman
Director, Hardware Engineering and Advanced Robotics at Amazon Robotics

“The Future is Humans and Robots Working Together”

Abstract: Amazon Robotics systems are transforming fulfillment at the core of many of Amazon’s fulfillment centers.  The unprecedented scale and efficiency that have been achieved in these facilities are the result of some key system design decisions that were made during development.  In this talk, we will address how these choices influenced the development of the massively parallel human-robot collaborative system and its components.  We will show how these choices allow the associates perform their tasks safely, quickly and efficiently in order to deliver smiles to Amazon customers worldwide.   

Biography: Parris has been at Amazon Robotics since September 2013. He first started building robots more than 20 years ago in the GRASP laboratory at the University of Pennsylvania and earned his doctorate at the Harvard Robotics Laboratory. He has delivered robotics and automated instrumentation solutions world-wide in the material handling, medical device, life sciences and in-vitro diagnostics sectors. He enjoys the challenge of solving customer needs by commercializing products that are built at the intersection of many disciplines. He is excited to be at Amazon Robotics where he gets to work with robots every day and where he leads Hardware Engineering and Advanced Robotics. His teams design and engineer the robots, firmware and other equipment used in the Amazon robotic fulfillment solution to support the rapidly scaling business.

Afternoon Keynote Speaker

Dr. Ben Firner
Research Scientist, NVIDIA

Accelerating Autonomous Vehicles with Deep Learning

Abstract: At NVIDIA’s lab in Holmdel, New Jersey we are training deep convolutional neural networks to emulate human drivers. Using only annotated recordings of human drivers we can train these networks learn important driving maneuvers, including lane keeping, changing lanes, and turning. Furthermore, we can show that these networks have learned to react strongly to consistent and reasonable features, such as lane markers and other vehicles, without any explicitly human intervention or labeling.

As part of NVIDIA’s efforts to create hardware and software platforms for autonomous vehicles we have also developed testing and simulation tools to validate our trained models. Integrating this approach to autonomous driving with more traditional approaches creates the opportunity to create redundancy and improve safety for future autonomous vehicles.

Biography: In 2015 Ben Firner joined a new research group at NVIDIA whose goal was to explore novel solutions for autonomous vehicles, starting with end-to-end deep learning. In the past few years this small group has demonstrated the viability of their approach on real roads and in variable weather conditions across the United States and in live demonstrations, such as at the annual consumer electronics show in Las Vegas.

Ben earned a PhD from Rutgers University where he worked on small wireless sensors with many-year lifetimes. Before joining NVIDIA, Ben applied his thesis work at a startup creating and deploying next generation wireless monitoring systems for the laboratory animal care market. Ben also taught several undergraduate and graduate courses in the Rutgers ECE and CS departments.



May 21, 2024
3:50 am
Event Category: