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Speakers and Presentation Topics

LIDAR in Drone Applications: Lessons and Insights for Automotive System Makers
Tom Brady
Co-Founder and CTO

For decades, LIDAR sensing has been at the core of robotics and automation. LIDAR allows for extremely high sensing rates when compared to sound-based methods, while offering drastically reduced computational complexity when compared to vision-based approaches. These two benefits -- high throughput and low computational complexity -- are key advantages for LIDAR in the highly dynamic environments experienced by autonomous vehicles and autonomous drones. We use LIDAR-equipped drones to do autonomous inspections of wind turbines. With our approach, we fuse LIDAR information with GPS, inertial, and other sensory data to construct three-dimensional maps of wind turbines in real time. Our drones use this 3D map to intelligently plan their mission and movement throughout the world. In this talk, we will walk through key learnings when dealing with LIDAR in commercial drone applications, as well as share some insights and suggestions for designing LIDAR sensors into autonomous vehicles. We will also share our perspective on the emerging LIDAR technologies and applications.

Biography: Tom Brady is the CTO and co-founder of SkySpecs, an Ann Arbor-based startup with the mission to completely automate diagnostics and maintenance of renewable energy infrastructure. The company currently serves the wind industry with an autonomous blade inspection solution. With the push of a single button, SkySpecs’ drones are deployed to collect pictures that wind turbine owners can use to assess the health of their blades. Since launching their commercial product in 2016, SkySpecs has inspected nearly 15,000 blades across 6 countries and is playing an integral role in the maintenance cycle for some of the world’s top renewable energy companies. Tom has led SkySpecs’ engineering team since 2014, guiding product development and strategy for the company’s autonomous inspection system and web-based analytics platform. Tom holds two degrees in aerospace engineering from the University of Michigan, is an Endeavor Entrepreneur, and was named one of Forbes "30 Under 30" in 2016.

Edge, Centralized, and Fluid Real-Time Processing Techniques of LIDAR Data
Raul Bravo

When using a centralized architecture, the raw data from the LIDAR sensor is sent to the machine learning "brain" (AI), located in a central processing unit, often a high-end computing platform or GPU. In this scenario, the AI software can fuse data at a low level, but has to sift through high volumes of data, which can take up valuable network bandwidth and have significant costs in terms of time and energy consumption. Smart sensors refer to sensor modules with local processing (i.e. edge computing), where the output is typically a high-level description of detected objects. This approach optimizes the network use and can lower overall costs, but the AI cannot obtain rich-enough information, especially for multi-sensor fusion purposes. The presentation will explain these approaches with specific uses cases and will also introduce a third option, where the edge processing is delivering a “fluid” stream of data: low-level enough to be fused with other LIDARs or radars/cameras, but "smart enough" to decrease network and central processing requirements.

Biography: Raul Bravo is CEO and co-founder of Dibotics, and creator of the Augmented LIDAR technology. He is a serial entrepreneur in mobile robotics and a startup coach, with an extensive 15-year background in both bootstrapped and VC-backed startup creation and growth. He is an engineer from UPC (Barcelona, Spain) with an MBA from College des Ingénieurs (Paris, France). He has filed 10 patents and obtained 27 various awards for his engineering and entrepreneur career, among them the MIT Technology Review’s Top 10 Innovators Under 35 recognition.

Solid-State LIDAR Sensors: the Future of Self-Driving Vehicles
Patrick Brunett
Director, Business Development
Quanergy Systems

In this presentation, we will explain the differences between solid-state and mechanical LIDAR sensors, and why we ultimately see solid-state LIDAR as the key to mass-production of autonomous vehicles. Unlike mechanical sensors, which rely on a tightly coordinated choreography of tiny moving parts, solid-state LIDAR can be contained on a single chip, providing the MTBF necessary to support the sensor’s sustained use. The solid-state technology also allows the sensor to be more compact – fitting into the palm of your hand, the sensors can easily be integrated into the body of a vehicle without compromising aesthetics or airflow. Additionally, solid-state LIDAR sensors can be manufactured and sold at a lower cost, enabling the use of multiple sensors on vehicles for a fraction of the price. Finally, we will walk the audience through Quanergy’s product roadmap, the specific approach that the company has taken to developing both solid-state and mechanical LIDAR sensors, and how this fits into the timeline we envision for further sensor development. We will also discuss how self-driving technologies will be integrated into commercial and privately-owned vehicles over time, and what this means for key industry stakeholders.

Biography: Patrick Brunett is Director, Business Development at Quanergy Systems, maker of mechanical and solid-state LIDAR sensors and perception software. Brunett manages the company's Detroit office with a focus on the transportation and industrial markets. He has over 20 years of experience in the automotive market with a focus on infotainment systems, power electronics for electric vehicles, and connected and automated vehicle technologies. Prior to joining Quanergy, he held senior and executive level sales, business development, and business unit leadership positions at companies such as Sony Electronics, Sirius Satellite Radio, Intelligent Mechatronics Systems, Panasonic, Cohda Wireless, and Brunett Consulting.

The Role of LIDAR in Multi-Modal, High-Reliability Sensing
Ed Olson, PhD
Co-Founder and CEO
May Mobility

Developing autonomous vehicles that can operate at very high reliabilities (e.g., one failure per billion miles) requires sensor performance that cannot generally be obtained from a single sensor. In this talk, we describe approaches to developing integrated sensing systems by combining LIDAR with other sensor modalities (e.g. radar), and the usefulness of using multiple types of LIDAR sensors within a single system. Fundamentally, the sensing system must be able to detect, identify, and track objects at long ranges. Ultimately, better systems allow better predictions of a target’s future behavior, enabling a self-driving vehicle to produce better plans. We will describe some of the strengths and weaknesses of currently-available sensor systems and show how careful system design can achieve high performance in real-world conditions at price points that allow autonomous vehicles to be not only safe but also economically viable.

Biography: Edwin Olson is an Associate Professor of Computer Science and Electrical Engineering at the University of Michigan, and co-founder/CEO of May Mobility, Inc., which develops self-driving shuttles. He earned his PhD from MIT in 2008 for work in robot mapping. He has worked on autonomous vehicles for over a decade, including work on the 2007 DARPA Urban Challenge, vehicles for Ford and Toyota Research Institute, and now May Mobility. His academic research includes work on perception, planning, and mapping. He was awarded a DARPA Young Faculty Award, named one of Popular Science's "Brilliant 10", and was winner of the 2010 MAGIC robotics competition. He is perhaps best known for his work on AprilTags, SLAM using MaxMixtures and SGD, and Multi-Policy Decision Making.

An Overview and Comparison of LIDAR Receiver Solutions
Marc Schillgalies, PhD
Vice President of Development
First Sensor

A key component to ensure automotive LIDAR reliability and functionality is the light receiver/detector element. With the significant increase of LIDAR developments, various detector technologies are now used. Laser wavelengths vary from 850nm to 1550nm and require different types of detectors, each with their specific advantages and disadvantages. Different signal amplification concepts also lead to distinct detector technologies. In terms of specifications, signal-to-noise figures are not the only parameters to be considered. Cost, reliability, as well as system capability and availability need to be factored in too. This talk will provided a comprehensive comparison of silicon photodiodes, silicon avalanche photodiodes, silicon SiPMs/SPADs, and InGaAs avalanche photodiodes with respect to SNR, performance under different ambient conditions, bandwidth, differences in signal path architecture, and cost. Furthermore, multi-channel and single-channel detector designs will be compared. The talk will also discuss the next steps in detector development for automotive LIDAR scanners, including robust designs of semiconductor and packaging for harsher environmental conditions and higher integration density.

Biography: Dr. Marc Schillgalies is currently Vice President of Development at the German detector company First Sensor in Berlin. At First Sensor he has worked in different development and product management roles since 2010. Prior to First Sensor he was developing semiconductor laser diodes at Osram Opto Semiconductors in Regensburg, Germany. He received a Doctorate degree and M. Sc. degree in physics from the University of Leipzig, Germany and a M. Sc. degree in Optical Sciences from the University of Arizona in Tucson. In Tucson and Leipzig, his academic work focused on the field of optical semiconductor devices. F urthermore, he received a M.B.A. degree in General Management from Steinbeis University in Berlin with attention to innovation management.

Lasers and Detectors: Requirements, Considerations, and Emerging Trends for Automotive LIDAR
Rajeev Thakur, P.E
Product Marketing Manager, Infrared Business Unit
OSRAM Opto Semiconductors

Being a leading provider of lasers for LIDAR, we are often besieged with requests for new laser designs. This presentation will share some of our insights on the market, the challenges faced in evaluating various LIDAR concepts, and the resulting requirements for lasers. We will discuss the range, resolution, field of view, eye safety, beam qualities, and collimation along with laser packages, laser drivers, detector considerations, and various related topics. Also, we will share a weighted quality function deployment matrix of application requirements and LIDAR design properties along with a few selected LIDAR architectures. We will also discuss sensor fusion gaps, as well as data throughput and regulations. The presentation will also include an overview of some of the interesting and recently funded LIDAR startups, as well as notable technologies that are coming out of universities and R&D labs. Finally, we will present a “crystal ball” outlook for LIDAR technology growth for ADAS and self-driving cars.

Biography: Rajeev Thakur is currently a Product Marketing Manager at OSRAM Opto Semiconductors, where he is responsible for infrared product management and business development in the NAFTA automotive market. His current focus is on LIDAR, driver monitoring, night vision, blind spot detection, and other ADAS applications. Rajeev joined OSRAM Opto Semiconductor in 2014. His experience in the Detroit automotive industry spans over 28 years -- working for companies such as Bosch, Johnson Controls, and Chrysler. He has concept-to-launch experience in occupant sensing, seating, and power train sensors. He holds a Master’s Degree in Manufacturing Engineering from the University of Massachusetts, Amherst and a Bachelor’s Degree in Mechanical Engineering from Guindy Engineering College in Chennai, India. He is a licensed professional engineer and holds a number of patents on occupant sensing. He is also a member of the SAE Active Safety Standards development committee.

Technology Showcase Presenters

(listed alphabetically, by company name)

Rajeev Thakur
Product Marketing Manager
OSRAM Opto Semiconductors

Wade Appelman
Vice President Sales and Marketing

Jane Zhang
Surestar Technology

Brian Wong

Georg Ockenfuss
Director WW FAE
VIAVI Solutions

Startup Showcase Presenters

(listed alphabetically, by company name)

Mohammad Musa
CEO and Co-Founder

Bill Colleran, PhD
CEO and Founder
Holosense Technologies

Call for Speakers

If you’d like to participate as a speaker, please call Jessica Ingram at 360-929-0114 or send a brief email with your proposed presentation topic to All speakers will receive a complimentary pass to the conference.

Workshop and conference scope includes topics related to LIDAR in automotive applications, such as:

  • Expert reviews and analyses of state-of-the-art LIDAR technologies
  • Business trends, market projections, M&A developments, and startup activity
  • LIDAR data fusion with other types of sensors such as radar and camera
  • Impacts of enabling technologies such as artificial intelligence
  • Notable academic research related to LIDAR for automotive applications
  • LIDAR data processing techniques and algorithms
  • Supply chain trends and challenges, government regulations, and mandates
  • Fabrication, packaging, and system assembly techniques
  • Reliability testing methodologies and techniques
  • Technology transfer, ecosystems and research hubs, company formation