Margarita Chli, vice director at the Institute of Robotics and Intelligent Systems at ETH Zurich, is seen standing in front of a room giving a talk.
Margarita Chli, an Amazon Research Award recipient, is vice director at the Institute of Robotics and Intelligent Systems at ETH Zurich, where she heads up the Vision for Robotics Lab.
Lukas Bigler/wavelighthouse

How Margarita Chli is using drones to go where people can’t

When it comes to assisting search-and-rescue missions, dogs are second to none, but an Amazon Research Award recipient says they might have some competition from drones.

Today, using drones in responding to natural or man-made disasters is limited by the fact that they need to be both individually piloted and have their observations interpreted by a human. But what if drones could “see” on their own? What if they could not only make decisions about navigation, but also where to look more closely — or even collaborate with other drones and robots to observe a specific location?

That suite of skills is exactly what Margarita Chli, an Amazon Research Award recipient and vice director at the Institute of Robotics and Intelligent Systems at ETH Zurich (the Swiss Federal Institute of Technology), is exploring. Chli heads up the Vision for Robotics Lab there (V4RL), and she’s been using her 2019 Amazon Research Award (she was awarded one in 2020 as well) to advance robotic vision for small aircraft, including drones.

Chli grew up in Greece and Cyprus with math teachers as parents, so while she was “heavily trained” in the language of mathematics, she didn’t always know robotics would be her professional focus.

Chli says it was really a series of lucky events that led to her introduction to “influential and brilliant scientists who planted the seed of intellectual curiosity in this area.”

After studying computer science and engineering at the University of Cambridge, where she earned her bachelor’s and master’s degrees, she considered her options.

“The coolest thing at the time seemed to be this PhD position at Imperial College in London, where my advisor, Andrew Davison, brought me into the area of robotic vision. That’s how it all started,” says Chli.

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Measuring the displacement between location estimates derived from different camera views can help enforce the local consistency vital to navigation.

Davison’s expertise was pioneering monocular SLAM (simultaneous localization and mapping), which is about “understanding how a camera moves in space,” says Chli. In pursuing her PhD, Chli did a lot of coding on her laptop, connecting that computer to a single camera and testing algorithms.

During her postdoc at ETH Zurich, which began in 2010, she applied her computer-vision algorithms to small drones. Chli says it was exciting to translate what she was doing on her laptop to a robot that was actually moving. That’s when she envisioned the potential impact for this technology.

“It's one thing to write some code and look at beautiful images, and another thing to get a robot moving – you get a feeling that you're creating something. And even going beyond that, to create something that can help people,” says Chli.

Drones in disaster zones

Her time at ETH Zurich also marked an era where drones, which had once been prohibitively expensive, were becoming more popular and accessible. “The technological hardware side of things was blooming, which meant we could run then-expensive image-processing algorithms onboard smaller and smaller platforms.” Those drones were more expensive, bulkier, less flexible, and lacked the processing power compared to today’s drones, “but nevertheless, the applications and imagination were there already,” she says.

As she wrote her research proposals, Chli expanded her thinking about the power of this technology. “What can we do with this? How we can use drones and robots and robotic vision to have robots in our everyday lives, that that can help us with tasks that we don't want to do?”

Those questions have propelled her research ever since.

Margarita Chli is seen speaking behind a lectern that says ETH Zürich on it, there are two large flower vases just behind her
One of the first projects for Margarita Chli at ETH Zurich: using drones for search-and-rescue missions.
Oliver Bartenschlager

One of the first projects Chli got to work on at ETH Zurich — where she was appointed as a deputy director of the lab she was working as a postdoc — was using drones for search-and-rescue missions. That work involved drones accessing areas that would be too dangerous or time-consuming for rescuers on foot, allowing rescuers to search for missing people with less risk.

Working backwards from the end-user, Chli spoke with rescuers at Club Alpino Italiano and learned that they didn’t want anything in the field that wasn’t directly useful — drones that worked independently made more sense than dedicating human resources to flying and monitoring drones.

These rescuers had lost colleagues to this very risky work, which takes place in harsh weather conditions, and so they were understandably demanding — and skeptical. “They had no time for delays or mistakes from fussy hardware or software,” she says.

The requirement for simplicity and a just-works solution has “been a great drive for my research ever since, to be honest: to develop plug-and-play, no-fuss systems, such that mission experts do not need to also be robotics experts or pilots.”

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While supporting the work of search-and-rescue teams is still an important component of her work, Chli and team have expanded the scope of their research.

Chli also envisions drones being used for inspecting hard-to-reach areas like wind-turbine blades, or power plants. “In 2012, there was a big explosion in the power plant on the island where I come from in Cyprus. We needed drones to be able to inspect the boilers for cracks to figure out how safe it was for humans to go closer,” she says.

Truly useful robots

This incident inspired Chli to focus on designing robots with real utility.

“I found it quite astonishing that we would see in the news robots that could do all sorts of gimmicky things, but we didn’t have reliable enough robots that could really help humans in a time of dire need.” She wanted to change that, and with her background in robotic vision and interest in drones, creating an unmanned aerial vehicle (UAV) that could “see” was the next challenge. In 2013, she was part of the team that ran the first vision-based autonomous flights of a small helicopter.

Margarita Chli is seen standing on a garden terrace, a drone is hovering over her shoulder in the background.
Margarita Chli is tackling drone challenges such as how a drone can maintain estimating its motion as accurately as possible.
Daniel Winkler

That same year, Chli took a post as a professor at the University of Edinburgh as a Chancellor's fellow. There, she started Vision for Robotics Lab (V4RL), which focuses on vision for robots, especially UAVs. In 2015, she returned to ETH Zurich, where she’s now professor and continues to lead V4RL.

Her research has been accelerated thanks to the resources made available to her as an Amazon Research Award recipient; resources that include access to AWS EC2 and S3.

“I think that what Amazon is doing is a great thing, because it's helping us actually see what researchers can do with its tools and it is democratizing where research is going,” she says.

She’s using those tools to tackle some of the most important problems in her work at ETH Zurich, like “how to figure out where a good spot to land is for our drones, and how we can keep a drone estimating its motion as accurately as possible, without being affected by water, trees, pedestrians, cars, and other dynamic, moving parts of the scene.” While flight-critical tasks must be processed on the drones themselves, transferring other processing tasks to the cloud, like semantic segmentation and high-level path planning, makes sense, says Chli.

Drones helping humanity

Chli thinks drones that can see and make decisions on their own will serve humanity outside search-and-rescue operations.

Researchers tracking wildlife migrations or large, dispersed herds could use drones to keep tabs on individual animals in ways humans on foot can’t, while at the same time understanding group movements.

Robots are going to help us in many ways that today we cannot really imagine, in ways we never thought possible.
Margarita Chli

“Archaeologists have come to us and said, ‘We have about 250 archaeological sites in Greece, we have a few tools around like a tripod, and I can put it in different places and take laser scans, but it's heavy, it's bulky. I don't want to find holes in my model, because I don't have time to go back to every one of these sites to capture new data.’ That’s where drones could be ideal, because they can map an area,” says Chli.

Chli says she’s become a bit of a drone evangelist because often when people hear her speak about autonomous drones, they think of military applications — whereas her focus is on what robots can do to improve the human condition.

Chli said she understands how that distrust emerged. “This technology has been growing very quickly, particularly comparing the progress today to a few years back,” she said. “And the less we know about how this technology works, the more scared we are of it.”

That’s why, she says, it’s important to raise questions and have open dialogues to address concerns because, as she sees it, robots are going to be part of our everyday lives.

“Robots are going to help us in many ways that today we cannot really imagine,” Chli says, “in ways we never thought possible.”

Research areas

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Re-imagining the realms of what’s possible in advertising. Amazon is re-imagining advertising. Amazon Ads operates at the intersection of eCommerce and advertising and offering a rich array of advertising solutions and audience insights so businesses and brands can create relevant campaigns that produce measurable results. At Amazon Ads, you can build models that impact millions every day. And we’re passionate about solving real-world problems while using cutting-edge machine learning and artificial intelligence to do this. For example, our applied science teams leverage a variety of advanced machine learning and cloud computing techniques to power Amazon's advertising offerings. This includes building algorithms and cloud services using clustering, deep neural networks, and other ML approaches to make ads more relevant while respecting privacy. They develop machine learning models to predict ad outcomes and select the optimal ad for each shopper, context, and advertiser objective, leveraging techniques like multi-task learning, bandit/reinforcement learning, counterfactual estimation, and low-latency extreme ML. The teams also utilize Spark, EMR, and Elasticsearch to extract insights from big data and deliver recommendations to advertisers at scale, continuously improving through offline analysis and impact evaluation. Additionally, they apply generative AI models for dynamic creative optimization and video experimentation and automation. Underpinning these efforts are unique technical challenges, such as operating at unprecedented scale (hundreds of thousands of requests per second with 40ms latency) while respecting privacy and customer trust guarantees, and solving a wide variety of complex computational advertising problems related to traffic quality, viewability, brand safety, and more. Help us take innovation in advertising to the next level. Our teams are based in our fast-growing tech hubs in London and Edinburgh. Learn more about Amazon Ads, employee stories and available opportunities here: https://www.amazon.jobs/content/en/teams/advertising/applied-science-machine-learning-research?ref_=a20m_us_car_lp_asml Key job responsibilities * Design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both analysis and business judgment. * Collaborate with software engineering teams to integrate successful experiments into large-scale, highly complex Amazon production systems. * Promote the culture of experimentation and applied science at Amazon. * Demonstrate ability to meet deadlines while managing multiple projects. * Excel communication and presentation skills working with multiple peer groups and different levels of management * Influence and continuously improve a sustainable team culture that exemplifies Amazon’s leadership principles * Develop a deep and wide understanding of large ad tech solutions to which you will contribute, and how they interact with components owned by other teams. * Anticipate obstacles and look around corners, effectively prioritising work, solving trade-offs and influencing the development of advertising products beyond the scope of your immediate team. We are open to hiring candidates to work out of one of the following locations: Edinburgh, MLN, GBR | London, GBR
US, VA, Arlington
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center at AWS is a new strategic team that helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. A key focus of this role is GenAI model customization using techniques such as fine-tuning and continued pre-training to help customers build differentiating solutions with their unique data. Key job responsibilities As a Data Scientist, you will: Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder Provide customer and market feedback to Product and Engineering teams to help define product direction About the team Sales, Marketing and Global Services (SMGS) AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest-growing small- and mid-market accounts to enterprise-level customers, including the public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. The Professional Services team is part of Global Services. About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Denver, CO, USA | Herndon, VA, USA | New York, NY, USA | Santa Clara, CA, USA | Seattle, WA, USA | Washington Dc, DC, USA