TheWebConf: Stable themes, new wrinkles

Amazon Scholar Eugene Agichtein on incorporating knowledge into natural-language-processing models, multimodal interactions, and more.

Famously, in 1998, the first research paper about Google’s ranking algorithm was turned down by more-established academic conferences on information retrieval before finding a home at the upstart World Wide Web Conference, which was only four years old at the time.

0022303-18AW
Eugene Agichtein, Amazon Scholar and Winship Professor of computer science at Emory University.
Credit: Ann Watson

“It was accepted to WWW because it was this new and emerging conference that was just taking cool ideas,” says Eugene Agichtein, an Amazon Scholar, the Winship Professor of computer science at Emory University, and a researcher whose 20-year involvement with the Web Conference included a stint as program committee co-chair in 2017. “It was accepting of new topics, and it moved faster and was more adaptable than traditional academic conferences. And it was more inclusive of industry work.”

This year, the formerly disruptive conference — now known as simply the Web Conference, nicknamed TheWebConf — receives another badge of mainstream acceptance, as it officially comes under the aegis of the Association for Computing Machinery.

“This year marks the historical transition of the conference series to ACM, the world’s largest scientific- and educational-computing society,” says Yoelle Maarek, the Amazon vice president for research and science at Alexa Shopping and a vice president of the conference’s new steering committee of the conference. “This definitely paints an even brighter future for the conference series.”

Related content
For Amazon’s Xin Luna Dong, the conference’s diversity mirrors that of her project: building the Amazon product knowledge graph.

“Five years ago” — the year in which Agichtein was program chair — “we had a record number of submissions to the conference,” Agichtein says. "Out of 966 submissions, 164 were accepted. This year, there were almost double the submissions from five years ago. There were 1,820 submissions, with, again, a 17% acceptance rate. The conference has just exploded, and it remains incredibly competitive.

“Because of the acceptance rate, a lot of potentially cool and exciting work doesn't get in. However, there are a lot of what they call alternate tracks for industry, for posters and demos, and for web development where a lot of these emerging topics get accepted. For example, e-sports and online gaming, which would be a struggle to evaluate in a regular academic conference — e-sports has a special track at the Web Conference this year.”

Shifts and trends

In just the five years since he served as program chair, Agichtein says, there have been some notable shifts in the distribution of research topics covered at the conference.

“One of the popular topics five years ago was crowdsourcing, investigating methodologies for large-scale human data collection for training and evaluating machine learning models,” he says. “But by now, it has become a mainstream method for creating training data for large models. Similarly, there is no longer a separate track for conversational systems, because conversational interfaces have become incorporated into the general search or recommendation system tracks.”

Related content
Scientists updated the system to accurately measure body fat percentage and create personalized 3D models even if there’s not enough room to take a full-body photo.

“In ’17, we introduced a new track to the Web Conference on computational health,” Agichtein adds, “and I was very happy to see that there are a lot of papers this year on health on the web, with different names, like web for good or web for society. Especially with the pandemic, the web has become central to health-related activities and research — tracking things like infection rates. It was interesting to see how much it took off.”

Glancing over the program of this year’s Web Conference, Agichtein notices a few pronounced trends.

“User modeling has been a central part of the web, and this year is no exception,” he says. “It's all about trying to personalize content, trying to model how people are interacting with the systems. I would say there are at least two dozen papers on representing users, building user models, and trying to personalize or present content to them. And security, privacy, and trust remain a critical issue.”

Knowledge and multimodality

One of the research trends that most intrigues Agichtein is the incorporation of both structured and unstructured knowledge and reasoning into natural-language-processing models for conversational information retrieval and recommendation systems.

“I can give you an example close to our work at Amazon,” he says. “In order to generate an informed response, a conversational agent needs to be able to detect when, how, and what knowledge to incorporate into a conversation in a coherent manner. For example, to recommend an item such as a movie, an agent needs to represent the conversation context and retrieve useful knowledge about the movie itself and, ideally, provide relevant information about what made this movie appropriate for the user.

Related content
Amazon’s George Karypis will give a keynote address on graph neural networks, a field in which “there is some fundamental theoretical stuff that we still need to understand.”

“There's been a wide variety of approaches to how to incorporate this knowledge, whether it's to incorporate it directly into the generative model by memorizing everything — storing it as part of the language model — or by retrieving knowledge from a variety of sources at runtime, which is the approach that we tend to favor.

“The new approaches will allow us to better select relevant knowledge or reason about which parts of the knowledge sources are helpful to include, because we have more capacity to capture the conversational context itself and more powerful models to pull in the knowledge needed to either generate a response or to select among possible responses or to understand what the user is trying to do.

“The other thing I have been studying is how users interact with information retrieval and conversational systems. Conversational interfaces have become ubiquitous, thanks to Alexa and others, but there's a completely open area on how those agents would interact with users in the real world, and in combination with other modalities such as screens and available sensors. So when we have responsive and potentially autonomous devices like Amazon’s Astro or other robots interacting with users in the real, physical environment, we need completely new models to represent the physical context of the interaction and to connect the content and the user’s gestures to what they refer to on the screen or in the real world.

“In this spirit, we have organized the Alexa Prize TaskBot Challenge, providing an opportunity for university teams to develop conversational-AI agents to assist users with cooking and home improvement tasks. The user modeling track at TheWebConf would be a perfect venue for that kind of work.

Related content
With a new machine learning system, Alexa can infer that an initial question implies a subsequent request.

“The research community has spent 20 years optimizing models to interpret user queries and result clicks on the web. Now we have much richer environments and interaction modalities. So you can imagine it'll take us another 20 years to really come up with accurate ways of interpreting user interactions with multimodal conversational systems embedded in the user’s space.”

For the most part, however, “the overall themes of TheWebConf have remained relatively stable for the last five years,” Agichtein says. “It's just that the diversity within each of the tracks has continued to increase. And it’s encouraging to continue to see strong representation of both academia and industry. That's the spirit in which the conference was founded.”

Related content

US, WA, Seattle
Amazon is seeking an experienced, self-directed data scientist to support the research and analytical needs of Amazon Web Services' Sales teams. This is a unique opportunity to invent new ways of leveraging our large, complex data streams to automate sales efforts and to accelerate our customers' journey to the cloud. This is a high-visibility role with significant impact potential. You, as the right candidate, are adept at executing every stage of the machine learning development life cycle in a business setting; from initial requirements gathering to through final model deployment, including adoption measurement and improvement. You will be working with large volumes of structured and unstructured data spread across multiple databases and can design and implement data pipelines to clean and merge these data for research and modeling. Beyond mathematical understanding, you have a deep intuition for machine learning algorithms that allows you to translate business problems into the right machine learning, data science, and/or statistical solutions. You’re able to pick up and grasp new research and identify applications or extensions within the team. You’re talented at communicating your results clearly to business owners in concise, non-technical language. Key job responsibilities • Work with a team of analytics & insights leads, data scientists and engineers to define business problems. • Research, develop, and deliver machine learning & statistical solutions in close partnership with end users, other science and engineering teams, and business stakeholders. • Use AWS services like SageMaker to deploy scalable ML models in the cloud. • Examples of projects include modeling usage of AWS services to optimize sales planning, recommending sales plays based on historical patterns, and building a sales-facing alert system using anomaly detection.
US, WA, Seattle
We are a team of doers working passionately to apply cutting-edge advances in deep learning in the life sciences to solve real-world problems. As a Senior Applied Science Manager you will participate in developing exciting products for customers. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the leading edge of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with others teams. Location is in Seattle, US Embrace Diversity Here at Amazon, 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. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust Balance Work and Life Our 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 Mentor & Grow Careers Our 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. Key job responsibilities • Manage high performing engineering and science teams • Hire and develop top-performing engineers, scientists, and other managers • Develop and execute on project plans and delivery commitments • Work with business, data science, software engineer, biological, and product leaders to help define product requirements and with managers, scientists, and engineers to execute on them • Build and maintain world-class customer experience and operational excellence for your deliverables
US, Virtual
The Amazon Economics Team is hiring Interns in Economics. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Some knowledge of econometrics, as well as basic familiarity with Stata, R, or Python is necessary. Experience with SQL, UNIX, Sawtooth, and Spark would be a plus. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. You will learn how to build data sets and perform applied econometric analysis at Internet speed collaborating with economists, data scientists and MBAʼs. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. Roughly 85% of interns from previous cohorts have converted to full time economics employment at Amazon. If you are interested, please send your CV to our mailing list at econ-internship@amazon.com.
US, WA, Seattle
Amazon internships are full-time (40 hours/week) for 12 consecutive weeks with start dates in May - July 2023. Our internship program provides hands-on learning and building experiences for students who are interested in a career in hardware engineering. This role will be based in Seattle, and candidates must be willing to work in-person. Corporate Projects (CPT) is a team that sits within the broader Corporate Development organization at Amazon. We seek to bring net-new, strategic projects to life by working together with customers and evolving projects from ZERO-to-ONE. To do so, we deploy our resources towards proofs-of-concept (POCs) and pilot programs and develop them from high-level ideas (the ZERO) to tangible short-term results that provide validating signal and a path to scale (the ONE). We work with our customers to develop and create net-new opportunities by relentlessly scouring all of Amazon and finding new and innovative ways to strengthen and/or accelerate the Amazon Flywheel. CPT seeks an Applied Science intern to work with a diverse, cross-functional team to build new, innovative customer experiences. Within CPT, you will apply both traditional and novel scientific approaches to solve and scale problems and solutions. We are a team where science meets application. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems.
US, WA, Seattle
Amazon internships are full-time (40 hours/week) for 12 consecutive weeks with start dates in May - July 2023. Our internship program provides hands-on learning and building experiences for students who are interested in a career in hardware engineering. This role will be based in Seattle, and candidates must be willing to work in-person. Corporate Projects (CPT) is a team that sits within the broader Corporate Development organization at Amazon. We seek to bring net-new, strategic projects to life by working together with customers and evolving projects from ZERO-to-ONE. To do so, we deploy our resources towards proofs-of-concept (POCs) and pilot programs and develop them from high-level ideas (the ZERO) to tangible short-term results that provide validating signal and a path to scale (the ONE). We work with our customers to develop and create net-new opportunities by relentlessly scouring all of Amazon and finding new and innovative ways to strengthen and/or accelerate the Amazon Flywheel. CPT seeks an Applied Science intern to work with a diverse, cross-functional team to build new, innovative customer experiences. Within CPT, you will apply both traditional and novel scientific approaches to solve and scale problems and solutions. We are a team where science meets application. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems.
US, CA, Palo Alto
The Amazon Search team creates powerful, customer-focused search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, 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. We’re seeking a Principal Scientist with a deep expertise in Search Science. Your responsibilities will include everything from developing and prototyping innovative machine learning, and deep learning algorithms to implementing, testing, and supporting full solutions in a production environment. We are looking for innovators who can contribute to advancing search technology on what’s scientifically possible while remaining committed to creating world-class products. Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.com (AMZN), Earth's most customer-centric company one of the world's leading internet companies. We provide a highly customer-centric, team-oriented environment in our offices located in Palo Alto, California. Key job responsibilities As a hands-on leader of this team, you’ll be responsible for defining key research questions, identifying relevant data, adopting or proposing innovative machine learning solutions conducting rigorous experiments, publishing results and working with the engineering team to deploy these solutions. As a strategic leader, you will identify investment opportunities, develop long term strategies, and propose, prioritize and deliver on goals. You’ll also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance). About the team Starting in 2009, the Visual Search & Augmented Reality team has thus far launched many visual search solutions on the Amazon App that use computer vision and machine learning/deep learning to help customers complete their shopping missions more easily; multiple internal teams at Amazon (devices, Kindle, Seller services, etc.) also use our libraries and APIs to deliver solutions to their own customers. We are a full stack shop, and our team capabilities cover the whole solution spectrum, ranging across applied science, large scale engineering services, product management, UX design, and mobile app development for iOS and Android.
LU, Luxembourg
&ltHire Relocation Requisition - not for posting> Provides insights to leadership on improving Supply Chain cost and Speed by using Data Science and Analytics techniques. Build Dashboards and models to industrialize these findings at scale.
US, VA, Arlington
The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for economists who are able to work with business partners to hone complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. We are looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work closely with business partners to develop science that solves the most important business challenges. They will work in a team setting with individuals from diverse disciplines and backgrounds. They will serve as an ambassador for science and a scientific resource for business teams, so that scientific processes permeate throughout the HR organization to the benefit of Amazonians and Amazon. Ideal candidates will own the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities Use causal inference methods to evaluate the impact of policies on employee outcomes. Examine how external labor market and economic conditions impact Amazon's ability to hire and retain talent. Use scientifically rigorous methods to develop and recommend career paths for employees. A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team We are a multidisciplinary team that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer.
US, WA, Seattle
The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for economists who are able to apply economic methods to address business problems. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. We are looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work in a team setting with individuals from diverse disciplines and backgrounds. They will work with teammates to develop scientific models and conduct the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities Use causal inference methods to evaluate the impact of policies on employee outcomes. Examine how external labor market and economic conditions impact Amazon's ability to hire and retain talent. Use scientifically rigorous methods to develop and recommend career paths for employees. A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team We are a multidisciplinary team that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer.
US, WA, Seattle
Amazon is looking for talented Postdoctoral Scientists to join our global Science teams for a one-year, full-time research position. Postdoctoral Scientists will innovate as members of Amazon’s key global Science teams, including: AWS, Alexa AI, Alexa Shopping, Amazon Style, CoreAI, Last Mile, and Supply Chain Optimization Technologies. Postdoctoral Scientists will join one of may central, global science teams focused on solving research-intense business problems by leveraging Machine Learning, Econometrics, Statistics, and Data Science. Postdoctoral Scientists will work at the intersection of ML and systems to solve practical data driven optimization problems at Amazon scale. Postdocs will raise the scientific bar across Amazon by diving deep into exploratory areas of research to enhance the customer experience and improve efficiencies. Please note: This posting is one of several Amazon Postdoctoral Scientist postings. Please only apply to a maximum of 2 Amazon Postdoctoral Scientist postings that are relevant to your technical field and subject matter expertise. Key job responsibilities * Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. * Publish your innovation in top-tier academic venues and hone your presentation skills. * Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.