Alla Sheffer horizontal
Alla Sheffer is a computer science professor at the University of British Columbia in Vancouver, Canada, and an Amazon Scholar. Her work contributed to the recent launch of the Made for You service, which allows customers to create a custom T-shirt to their exact measurements and style preferences.
Courtesy Alla Sheffer

Amazon Scholar Alla Sheffer uses computer graphics to drive improvements in garment sizing and fitting

Complex algorithms promise to fundamentally change a craft that still relies almost entirely on handwork.

Alla Sheffer is a computer science professor at the University of British Columbia (UBC) in Vancouver, Canada, where she has built a powerhouse research center around her specialty: computer graphics. Her research applies insights about human perception and communication of shapes to algorithmic shape processing, yielding novel modeling methods targeted at a broad user base. The algorithms she has developed accelerate and simplify the creation of virtual and real shapes across multiple domains, including fashion and product design.

Royal Society of Canada video when Alla Sheffer named a Fellow

Sheffer is a Fellow of the Royal Society of Canada and an IEEE Fellow. Her other recent honors include the Canadian Human Computer Communications Society 2018 Achievement Award, and a UBC Killam Research Award (2019). In addition, last year she was inducted into the ACM SIGGRAPH Academy, an honorary group of individuals who have made significant contributions to the field of computer graphics. Sheffer was recognized for her contributions in geometry processing and interactive geometric modeling.

Sheffer is also an Amazon Scholar, an expanding group of academics who work on large-scale technical challenges for Amazon while continuing to teach and conduct research at their universities. Sheffer has an affinity for meshed cows and dragon stuffies, as both are excellent examples of applications of computer graphics algorithms.

We recently spoke with Professor Sheffer about the field of computer graphics, her career, and her work with Amazon Fashion on its recently announced “Made for You” Custom T-shirt.

Alla Sheffer with cows
Alla Sheffer admits to an affinity for meshed cows and dragon stuffies, as both are excellent examples of applications of computer graphics algorithms.
Courtesy Alla Sheffer

What drew you to computer graphics?

I took a computer graphics course during my undergrad studies and was enamored by the ability that graphics algorithms provide for folks with no art skills to create beautiful content. I then drifted into doing more engineering-oriented research, such as computer aided design and finite element mesh generation, but came back to graphics, as I just find it more visually appealing and exciting. 

One of the things I find exciting about graphics is that many technical problems that arise when creating virtual content directly correlate to real-world fabrication challenges. For instance, algorithms for computing texture atlases for graphics applications are directly applicable to fabrication of stuffed toys. In both settings, one needs to compute 2D charts, or patterns, that can be stitched together in three dimensions to form the desired virtual shape or real stuffed toy.

How does your work impact Amazon?

I am helping Amazon Fashion solve shopping challenges, such as size and fit. Most recently we launched Made for You, which is a new way for customers to shop in “Size You” using virtual fit technology that allows customers to create a custom T-shirt to their exact measurements and style preferences.

Traditionally, creating made-to-measure garments requires an expert pattern maker to take individual customer body measurements, modify the original garment patterns with these measurements in mind, and have a single custom garment manufactured. The pattern maker would then test how well the resulting garment fits a mannequin with your dimensions and iteratively adjust the patterns until they are satisfied with the fit. The time and expertise required to generate well-fitted, made-to-measure garments means that very few customers can afford to purchase such clothing.

With Made for You we are using technology to make it easier and more affordable for all customers to order made-to-measure, customizable garments. Providing the algorithmic support to achieve this goal requires solving two hard research problems. First, what does it even mean for a garment to look, or fit, the same on two different people? To answer this question, we need to understand how customers perceive fit. Once we know what the customer expects, how do we create the garment that the customer wants? Or specifically, how do we generate the patterns for this desired garment? These are two separate problems, and we are looking at both.

Made for You Customer T-shirt
Alla Sheffer is helping Amazon Fashion solve shopping challenges, such as size and fit, including her work on the recently announced Made for You service. Providing the algorithmic support to help create Made for You requires solving two hard research problems, Sheffer says.
Credit: Glynis Condon

How did you become interested in garments?

I find clothes fascinating – they are ubiquitous yet ridiculously hard to design to fit well even for just traditional sizes. While I have no formal garment design or pattern-making background, I learned a little bit about pattern making and sewing from my mom. She was a semi-professional tailor and I grew up in a house where tailoring magazines, patterns, and sewing tools were all around. I never expected this knowledge to be useful in my professional life, but here I am.

What led you to become an Amazon Scholar?

I love my university position; it gives me the opportunity to train undergraduate and graduate students and enables me to research fundamental open problems in computer graphics and related fields. But it lacks the immediate satisfaction of seeing your inventions being used by the general public. I found the opportunity to work on practical problems that Amazon provides exciting. The opportunity to impact how millions of people purchase clothing is tremendously exciting. I am also personally looking forward to the day where I can purchase clothing that perfectly fits me without first having to try on dozens of ill-fitting garments. 

The opportunity to impact how millions of people purchase clothing is tremendously exciting.
Alla Sheffer

Does working at Amazon benefit your academic research?

Yes, it does. I learn a lot from the amazing researchers, developers, and garment design professionals I am working with. I am also inspired by the workflow processes that Amazon uses. Adopting some of them for the academic environment would be very useful.

What advice would you give to someone interested in computer graphics as a career?

Do it! Computer graphics is cool and a computer graphics background provides you with a lot of work opportunities both inside and outside the traditional movie or video game industries. To be successful as a graphics researcher or developer you need to have a strong background in computer science theory and mathematics, and to be a very, very good programmer. In graphics, being able to code complex algorithms and to make them run as fast as possible is critical. Most universities have courses dedicated to computer graphics. Take them. Graphics has many different sub-areas – such as geometric modeling, which is what I do. See which ones attract you and try to take specialized courses in those.

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Are you seeking an environment where you can drive innovation? Do you want to apply machine learning techniques and advanced statistical modeling to solve real world problems to help Amazon reach and delight millions of customers around the world? Do you want to play a crucial role in the future of Amazon?Every time an Amazon customer makes an order they leverage the most advanced and sophisticated supply chain the world has ever seen, Amazon, and its global network comprising of cutting edge software, fulfillment centers, sort centers, delivery stations, airports, customer service centers, physical stores, robots, airplanes, trucks, vans, trucks, world class employees, trusted partners, and more. Conducting a symphony of this scale comes with significant costs.Here in WW Consumer Finance, our quantitative researchers raise the bar on our ability to fulfill promises to customers at greater convenience, speed, and value through:· Developing models to support the identification of investment opportunities consistent with Amazon strategic priorities· Developing models identifying synergy opportunities and risks in potential transactions· Serving as a subject matter expert on investment lead pipeline and valuation methodologies· Establish the ongoing processes, skill sets, and strategy that will enable Amazon to continue to build out our financial engineering competency, in the face of extremely fast growth and a rapidly changing industry· Working with technical and non-technical customers across every step of data science project life cycle.· Collaborating with our dedicated product, data engineering, and software development teams to create production implementations for large-scale data analysis.· Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business.· Presenting research results to our internal research community.· Leading training and informational sessions on our science and capabilities.Your contributions will be seen and recognized broadly within Amazon, potentially contributing to the Amazon research corpus and patent portfolio.
US, VA, Arlington
Are you seeking an environment where you can drive innovation? Do you want to apply machine learning techniques and advanced statistical modeling to solve real world problems to help Amazon reach and delight millions of customers around the world? Do you want to play a crucial role in the future of Amazon?Every time an Amazon customer makes an order they leverage the most advanced and sophisticated supply chain the world has ever seen, Amazon, and its global network comprising of cutting edge software, fulfillment centers, sort centers, delivery stations, airports, customer service centers, physical stores, robots, airplanes, trucks, vans, trucks, world class employees, trusted partners, and more. Conducting a symphony of this scale comes with significant costs.Here in WW Consumer Finance, our applied scientists raise the bar on our ability to fulfill promises to customers at greater convenience, speed, and value through:· Developing production ready solutions which help Amazonians search, find, compare, and buy goods / services critical to Amazon's operations· Developing production-ready machine learning solutions to improve Amazon's corporate procurement catalog· Working with technical and non-technical customers across every step of data science project life cycle.· Collaborating with our dedicated product, data engineering, and software development teams to create production implementations for large-scale data analysis.· Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business.· Presenting research results to our internal research community.· Leading training and informational sessions on our science and capabilities.Your contributions will be seen and recognized broadly within Amazon, potentially contributing to the Amazon research corpus and patent portfolio.
US, VA, Arlington
Are you seeking an environment where you can drive innovation? Do you want to apply machine learning techniques and advanced statistical modeling to solve real world problems to help Amazon reach and delight millions of customers around the world? Do you want to play a crucial role in the future of Amazon?Every time an Amazon customer makes an order they leverage the most advanced and sophisticated supply chain the world has ever seen, Amazon, and its global network comprising of cutting edge software, fulfillment centers, sort centers, delivery stations, airports, customer service centers, physical stores, robots, airplanes, trucks, vans, trucks, world class employees, trusted partners, and more. Conducting a symphony of this scale comes with significant costs.Here in WW Consumer Finance our applied scientists raise the bar on our ability to fulfill promises to customers at greater convenience, speed, and value through:· Developing production ready solutions which help Amazonians search, find, compare, and buy goods / services critical to Amazon's operations· Developing production-ready machine learning solutions to improve Amazon's corporate procurement catalog· Working with technical and non-technical customers across every step of data science project life cycle.· Collaborating with our dedicated product, data engineering, and software development teams to create production implementations for large-scale data analysis.· Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business.· Presenting research results to our internal research community.· Leading training and informational sessions on our science and capabilities.Your contributions will be seen and recognized broadly within Amazon, potentially contributing to the Amazon research corpus and patent portfolio.
US, WA, Seattle
We are constantly making Alexa the best voice assistant in the world. Amazon’s Alexa cloud service and Echo devices are used every day, by people you know, in and about their homes. The Alexa Monetization team is hiring talented and experienced Sr. Applied Scientists to help building the next generation products for Alexa across multiple channels and domains. We are seeking an experienced, entrepreneurial, big thinker for a confidential new initiative within Alexa. You will be joining a team doing innovative work, making a direct impact to customers, showing measurable success, and building with the latest natural language processing systems. If you are holding out for an opportunity to:Make a huge impact as an individual· Be part of a team of smart and passionate professionals who will challenge you to grow every day· Solve difficult challenges using your expertise in coding elegant and practical solutions· Create applications at a massive scale used by millions of people· Work with machine learning systems to deliver real experiences, not just researchAnd you are experienced with…· Drive applied science (machine learning) projects end-to-end ~ from ideation, analysis, prototyping, development, metrics, and monitoring· Conduct deep analyses on massive user and contextual data sets· Propose viable modeling ideas to advance optimization or efficiency, with supporting argument, data, or, preferably, preliminary results· Design, develop, and maintain scalable, Machine Learning models with automated training, validation, monitoring and reporting· Stay familiar with the field and apply state-of-the-art Machine Learning techniques to NLP and related optimization problems· Produce peer-reviewed scientific paper in top journals and conferencesAnd you constantly look for opportunities to…· Innovate, simplify, reduce waste, and increase efficiencies· Use data to make decisions and validate assumptions· Automate processes otherwise performed by humans· Learn from others and help grow those around you...then we would love to chat!In 2021, we have the opportunity to build new products and features from the ground up and we are looking for strong, bias for action engineering leaders who are not afraid of taking bold bets and trying new things to improve customer experience for Alexa.As part of a new and growing team, you will be iterating on new features and products to help drive innovation and expansion. You will work on cross-functional and cross-domain opportunities; tackle challenging projects aim to accelerate experimentations in Alexa; and build out operating mechanisms and technology to enable novel customer experiences. You will be instrumental in setting the team culture, quality bar, engineering best practices, and norms. Mentoring and growing the team around you will be one of the primary ways you measure your own success. You will have the opportunity to contribute and develop deep expertise in the areas of distributed systems, machine learning, conversational technologies, user interfaces (including voice and natural user interfaces), data storage and data pipelines.This role is exciting for scientists who love to apply startup mindset to their day-to-day, enjoy working cross-functionally to master both business and technology knowledge, and are passionate about building engineering best practices. If you are looking for opportunity to learn, grow and lead, this is the position for you.