Erica Aduh, a research scientist, is seen standing outside with office buildings in the background
Erica Aduh, a research scientist at Amazon Robotics, was drawn to robotics after taking an Intro to Robotics course during her sophomore year at the University of Pennsylvania.
Courtesy of Erica Aduh

How Erica Aduh learned to love robots

Today she’s a research scientist working on significant challenges for Amazon Robotics, but it was a college class that proved fateful.

Ask any roboticist — they’ll tell you that, when it comes to robots, manipulating items can be technically challenging. In simply lifting a package, these end effectors or end-of-arm tools sometimes need to be able to compensate for varying weights, as well as detecting small differences in pressure and texture. Erica Aduh, a research scientist at Amazon Robotics, is tackling that very type of problem.

Aduh has had a long-standing interest in engineering — one that started in her childhood. Her first home was in Nigeria, but then she moved with her family to skyscraper heavy Dubai. “There is a huge variety of intricately constructed buildings,” she says. “I found myself being fascinated by not only their magnificence but also the calculations required to design and construct them.” 

That fascination (and her love of math and physics), led Aduh to the US in 2010 to pursue mechanical engineering at the University of Pennsylvania. The Penn engineering department had two areas of interest for Aduh: product design and robotics. “I found myself incredibly interested in mechanical design,” says Aduh. There she built her portfolio and even started a product innovation club — one which several people in the engineering department ended up joining.

Learning to love robotics

She got bit by the robotics bug after taking Intro to Robotics her sophomore year. The class focused on item manipulation, similar to the work she’s doing now. She found the subject absorbing. When she later took a class on mechatronics, she was drawn to robotics once again. “I poured so much time into that class because I was just so fascinated by it,” she says.

I knew there was something in robotics that I really wanted to get my hands and feet into.
Erica Aduh

After working on a series of smaller projects building different types of robots and having fun combining electrical, mechanical, and software, “I knew there was something in robotics that I really wanted to get my hands and feet into.” Her final project: Create a robot that could autonomously play hockey. “I just remember spending hours and hours and hours with my teammates in the lab — it was a blast,” she recalls. 

Those late-night sessions pushed her towards robotics, which she then pursued as a master’s student, also at Penn. Her passion for research meant she faced the question of whether to continue on for a PhD. She was unsure, so when she landed a post-graduate internship at Amazon Robotics, she took it — and loved it. She worked with other interns on an exploratory project that allowed them to use what they had learned. “By the end of that internship, I was pretty sure I wanted to stay in the industry, instead of return to academia,” Aduh says. She joined Amazon as a mechanical engineer in early 2016.

Returning to research

After a couple of years, Aduh realized that her passion for research still burned: “While I really enjoyed my team and learned a lot, I realized I wanted to get back into research.”

So she started the transition, dropping into research team meetings, and taking on small tasks. “When I joined the manipulation research organization, I reported to Beth Marcus, who is fantastic and inspiring. She gave me the opportunity to explore a range of research topics and develop a focus within research. That was great because it was exactly what I needed to break into science research and grow as a scientist,” says Aduh.

Her other mentor, Andrew Marchese, taught her about modeling and simulation. “Andy is brilliant and skillful in just about every domain of robotics manipulation,” she said. “Having the opportunity to learn from him has been key and he is a major reason behind my transition into the science world.”  

That transition has proved fruitful for Amazon. “Erica has a profound ability to advance understanding through methodical experimentation and careful analysis. She's continually breaking down ambiguous problems into testable hypotheses — a true embodiment of the scientific process,” says Marchese.

Aduh’s team is currently focused on advancing how robots transport and move packages.  She’s developing the analytical models for robotic item manipulation — that includes both physics and robotics system modeling. “That could be anywhere from physics calculations that describe a component of a robotic work-cell to programmed simulations that model the full robotic system,” she explains.

Working with her team, she develops those models within a simulation platform. She also works with a high-fidelity physics simulator, developing models there, too. “I also create simulations of my own to be able to answer high level business questions and communicate my findings to leaders and coworkers using white papers,” Aduh says.

That can take her out of the workcell systems and into the floor-level simulations, which can be used to examine how throughput is affected by one approach versus another. The ultimate goal is to reliably and safely get packages where they need to go.

Aduh writes her scripts in Python or MATLAB, since she’s just creating the models to describe systems, but she also sometimes applies her ideas to a real robot (both to develop intuition and validate her models). Though the COVID-19 pandemic precluded her from going into the office and working on real robots for much of 2020, she found an alternate approach. Her workaround: watching videos of the robots performing the specific movements she was working on to build intuition, and then to later use robots for the validation tests.

“The ability to go from a simulation to the real world is critical,” noted Parris Wellman, vice president of engineering and robotics at Amazon Robotics. “It has a significant impact both on our organization and its ability to put out really cool stuff. It allows us to take smart software engineers and scientists and let them learn how to do robotics without a lot of risk.”

Career advice

For anyone interested in following in Aduh’s footsteps, she says finding good mentors has been “incredibly critical” to her success. “Through them, I was able to learn and get their feedback and thoughts on the correct approaches to use in ambiguous problems — they were just incredibly helpful,” she says.

Aduh’s creative way of attacking problems has also made her an asset to Amazon.

“Since I've known her, Erica has been drawn to really murky problems — areas the business wants to head, but where our technologies and/or solutions are unproven,” says Marchese. He says her ability to ask and answer hard questions “influences where our manipulation technology goes next. She's rigorous in her scientific exploration, but timely in her delivery of results.”

In addition to mentors, Aduh says it’s also important to be comfortable working outside what you already know. “Much of the time I feel as though I'm working on things that are outside of my comfort zone,” says Aduh. “And that's how I've been able to grow.”

Seeking proposals in five research areas, including human-robot interaction, autonomous navigation/mobility, and manipulation.

Research areas

US, WA, Seattle
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US, WA, Seattle
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US, WA, Seattle
Job summaryWW Installments is one of the fastest growing businesses within Amazon and we are looking for a Data Scientist to join the team. This group has been entrusted with a massive charter that will impact every customer that visits Amazon.com. We are building the next generation of features and payment products that maximize customer enablement in a simple, transparent, and customer obsessed way. Through these products, we will deliver value directly to Amazon customers improving the shopping experience for hundreds of millions of customers worldwide. Our mission is to delight our customers by building payment experiences and financial services that are trusted, valued, and easy to use from anywhere in any way.As a Data Scientist within WW Installments, you will be responsible for building machine learning models and pipelines with direct customer impact. These models represent a core capability for WW Installments and businesses across Amazon. Your work will directly impact customers by influencing how they interact with financing options to make purchases. You will work across functions including data engineering, software development, and business to induce data driven decisions at every level of the organization.Key job responsibilitiesThis role will be responsible for:• Developing machine learning models and pipelines for the WW Installments Competitive Pricing team.• Apply expertise in machine learning to develop large-scale systems that are deployed across Amazon businesses.• Identify business opportunities, define and execute modeling approach, then deliver outcomes to various Amazon businesses with an Amazon-wide perspective for solutions.• Lead the project plan from a scientific perspective on product launches including identifying potential risks, key milestones, and paths to mitigate risks.• Own key inputs to reports consumed by VPs and Directors across Amazon.• Identifying new opportunities to influence business strategy and product vision using data science and machine learning.• Continually improve the WW Installments ML roadmap automating and simplifying whenever possible.• Coordinate support across engineers, scientists, and stakeholders to deliver ML pipelines, analytics projects, and build proof of concept applications.• Work through significant business and technical ambiguity delivering on analytics roadmap across the team with autonomy.
US, CA, San Diego
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US, VA, Arlington
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US, CA, Sunnyvale
Job summaryAmong the goals of the Alexa Devices AI team, is to make Alexa the most knowledgeable and trusted ally for notifications, annoucements, pickup services and voice assistance while on the go.Key job responsibilities1. As an Applied Scientist on our team you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art NLU (Natural language understanding) developments.2. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to traing Machine Learning models for their application in NLU.3. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations.4. The ideal candidate will have experience with machine learning models and their application in AI systems. We are particularly interested in experience applying natural language processing, deep learning at scale. Additionally, we are seeking candidates with strong interest in data/research sciences and engineering, creativity, curiosity, and great judgment.5. You will interact with various stake holders: product leaders, program managers, other domain managers and developers on regular basis for requirement collections, deliveries, and other related communication6. You will help attract and recruit technical talentA day in the lifeApplied Scientist will help develop novel algorithms and apply modeling techniques to advance the state of the art in spoken language understanding (SLU) and to improve the customer experience in engaging with Alexa.About the teamThe Alexa Devices AI science team's work directly impacts the experience and engagement of customers who rely on Alexa while in-the-car, on-the-go and at-home.
US, VA, Arlington
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US, CA, Palo Alto
Job summaryAmazon is the 4th most popular site in the US (http://www.alexa.com/topsites/countries/US). Our product search engine is one of the most heavily used services in the world, indexes billions of products, and serves hundreds of millions of customers world-wide. We are working on a new AI-first initiative to re-architect and reinvent the way we do search through the use of extremely large scale next-generation deep learning techniques. Our goal is to make step function improvements in the use of advanced Machine Learning (ML) on very large scale datasets, specifically through the use of aggressive systems engineering and hardware accelerators. This is a rare opportunity to develop cutting edge ML solutions and apply them to a problem of this magnitude. Some exciting questions that we expect to answer over the next few years include:· Can a focus on compilers and custom hardware help us accelerate model training and reduce hardware costs?· Can combining supervised multi-task training with unsupervised training help us to improve model accuracy?· Can we transfer our knowledge of the customer to every language and every locale ? The Search Science team is looking for a Senior Applied Science Manager to drive roadmap on making large business impact through application of Deep Learning models via close collaboration with partner teams. The team also has a focus on technology solution for deep-learning based embedding generation, sensitive data ingestion and applications, data quality measurement, improvement, data bias identification and reduction to achieve model fairness.Success in this role will require the courage to chart a new course. You will manage your own team to understand all aspects of the customer journey. You and your team will inform other scientists and engineers by providing insights and building models to help improving training data quality and reducing bias. The research focus includes but not limited to Natural Language Processing, recommendation, applications relevant to Amazon buyers, sellers and more. You will be working with cutting edge technologies that enable big data and parallelizable algorithms. You will play an active role in translating business and functional requirements into concrete deliverables and working closely with software development teams to put solutions into production.
US, WA, Seattle
Job summaryAmazon EC2 provides cloud computing which forms the foundation for the majority of AWS services, as well as a large portion of compute use cases for businesses and individuals around the world. A critical factor in the continued success of EC2 is the ability to provide reliable and cost effective computing. The EC2 Fleet Health and Lifecycle (EC2 FHL) organization is responsible for ensuring that the global EC2 server fleet continues to raise the bar for reliability, security, and efficiency. We are looking for seasoned engineering leaders with passion for technology and an entrepreneurial mindset. At Amazon, it is all about working hard, having fun and making history. If you are ready to make history, we want to hear from you!Come join a brand new team, EC2 Health Analytics, under EC2 Foundational Technology, to solve complex cutting-edge problems to power a faster, more robust and performant EC2 of tomorrow. The charter of our team is to improve customer experience on the EC2 fleet by analyzing hundreds of signals and driving next-generation detection and remediation tools. We apply Machine Learning to predict outcomes and optimize decisions that improve customer experience and operational efficiency. As an Applied Scientist in the EC2 Health Analytics team, you will join an industry-leading engineering team solving challenging problems at massive scale.· Build a world-class forecasting platform that scales to handling billions of time series data in real time.· Drive fleet utilization improvement where each 1% means tens of millions of additional free cash flow.· Automate tactical and strategic capacity planning tools to optimize for service availability and infrastructure cost.· Build recommendation algorithms for improving the AWS customer experience.· · Reduce dependence on manual troubleshooting for deep-dives.What you will learn:· State-of-the-art analytics and forecasting methodologies.· Application of machine learning to large-scale data sets.· · Product recommendation algorithms.· Resource management and admission control for the Cloud.· The internals of all AWS services.Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, CA, Palo Alto
Job summaryThe Amazon Search team creates powerful, customer-focused search and advertising solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, the Amazon Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. Our team works to maximize the quality and effectiveness of the search experience for visitors to Amazon websites worldwide.