KDD: Graph neural networks, fairness, and inclusivity

The general chair of this year’s Conference on Knowledge Discovery and Data Mining on what excites him most about the conference program.

As general chair of this year’s ACM Conference on Knowledge Discovery and Data Mining (KDD), Huzefa Rangwala, a senior manager at the Amazon Machine Learning Solutions Lab, has a broad view of the topics under discussion there. Two of the most prominent, he says, are graph neural networks and fairness in AI.

Graphs are data representations that can encode relationships between different data items, and graph neural networks are machine learning models that are useful for knowledge discovery because they can be used to infer graph structures.

Huzefa.png
Huzefa Rangwala, a senior manager at the Amazon Machine Learning Solutions Lab and the general chair of this year's ACM Conference on Knowledge Discovery and Data Mining (KDD).

“Our world is connected in lots of ways, so you'll see graph neural networks find applications in lots of different domains, all the way from social networks and transportation networks to knowledge graphs and drug discovery,” Rangwala says.

The Amazon Machine Learning Solutions Lab brings the expertise of Amazon scientists and the resources of Amazon Web Services to bear on customers’ machine learning problems. Before joining Amazon, Rangwala was a professor of computer science at George Mason University, where he focused on interdisciplinary applications of machine learning — particularly, in biomedicine, learning sciences, and social sciences. Similarly, his team at the ML Solutions Lab works with customers across industries, including health care and life sciences, sports, and manufacturing.

Related content
Information extraction, drug discovery, and software analysis are just a few applications of this versatile tool.

“We’re using graph neural networks to represent macromolecules like proteins and their interacting partners,” Rangwala says. “So we’re using graph neural networks to essentially accelerate drug discovery or to find new biotherapeutics. And we’ve already deployed this approach with one of our customers, Janssen Pharmaceuticals.

“One of the outstanding questions is how you take the input from, let’s say, proteins and transform them into a representation for these graph structures. That’s step one: how do you engineer this in a robust manner, so you get good results.

“Some of the other open challenges are similar to the challenges that you see in deep-learning approaches: how do you ensure that the end results that you're getting are explainable and robust? At the end of the day, the end user might not be happy with just the prediction score. They might want to know why the predictions make sense.

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.”

“At KDD, there are several ideas being presented on how to scale, how to be efficient at running these and training these, as the dataset gets larger, the number of interactions get larger, and hence the representation gets larger. There are approaches to parallelize this, and there are also approaches to use efficient data structures. And then there are approaches to developing new formulations and computer architectures that can that can work nicely on these structures.

“But the really exciting thing for me is that we are seeing so many uses — proteins, molecules, information extraction, recommendations, anomaly detection — that all lead to improved scientific and business outcomes. These are some of the challenges and excitement around these techniques.”

Theory into practice

Indeed, Rangwala says, the breadth of the applications on display at KDD is, for him, one of the conference’s chief points of appeal.

I really like applied science. I'm not tied to one particular method or one particular domain. I'm most interested in how we can use these computing and machine learning techniques to solve challenging problems.
Huzefa Rangwala

“I'm mostly excited about KDD as a conference because it not only has innovations on the core data science methodologies, but many researchers are focused on how to use them,” Rangwala says. “How do you go from theory to practice? How do you translate machine learning research into the hands of end users?

“There's a lot of interdisciplinary work, first of all, even on the research track. And for many years KDD has had an applied-data-science track, so you not only get to see cutting-edge research, but you also got to see translational research, where you get to see how these things are applied.

“This suits my background, because I really like applied science. I'm not tied to one particular method or one particular domain. I'm most interested in how we can use these computing and machine learning techniques to solve challenging problems in different domains, be it physics, biology, chemistry, all the way to social sciences.”

Trustworthy computing

In knowledge discovery, as in many other fields related to machine learning, fairness has become a prominent research topic in recent years, Rangwala explains.

“Trustworthiness is crucial for the adoption of AI technologies and realizing their potential gains to the society. Being trustworthy means they need to be fair, they need to be explainable, and they also need to be reproducible.

Related content
New method enables two- to 14-fold speedups over best-performing predecessors.

“Now, there's a whole argument around this: is it that the data is biased, or is it the society that's biased? I think the field overall is cognizant of these issues, and they are asking the right questions — for example, building auditing approaches or mitigation approaches. Most importantly, they’re empowering the different stakeholders — developers, decision makers, and end users — to complement the developed solutions and ensure that algorithms are trustworthy.

“At KDD, there is a special day that is devoted to this topic, called Trustworthy AI Day. Also, if you look at the research track, there are lots of sessions on these topics.

“I also want to highlight the Women in KDD event. It's really exciting because it’s the first time it’s in-person. Judith Spitz, who founded an organization called Break Through Tech, is co-leading the event with Johannes Gehrke at Microsoft Research, and there is a plan to have power lunches and also to hear panelists talk about career journeys, especially for women and non-binary individuals in KDD. It's something that I'm very passionate about — how to have a more inclusive community.”

Research areas

Related content

US, CA, Palo Alto
The 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.
JP, Tokyo
The Amazon Logistics (AMZL) Team is responsible for the acquisition, design, construction, and management of all facilities in the Amazon Delivery Station Network. AMZL is looking for a talented and passionate Data Scientist to help shape its Last Mile business with technical strategies and solutions, by processing, analyzing and interpreting huge data sets. You should be comfortable with ambiguity, problem solving and enjoy working in a fast-paced, diverse and dynamic environment. Using analytical rigor and statistical methods, you mine through data to identify opportunities for Amazon and our delivery channels. And you collaborate with other scientists, engineers, Product and Program Managers to deploy new products and solutions. [More Information] Last Mile Department Data Analyst/BI Engineer Tokyo Office *Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, visit https://www.amazon.jobs/disability/jp Key job responsibilities Creating a roadmap of the most challenging business questions and use data to articulate possible root cause analysis and solutions Managing and executing entire projects or components of large projects from start to finish including project management, data gathering and manipulation, synthesis and modeling, problem solving, and communication of insights Partnering with Product, Program and Engineering teams to design and run models, research new algorithms, and prove incrementality and drive growth Understanding drivers, impacts, and key influences on seller growth dynamics Developing and scaling end-to-end ML Models and solutions Automating feedback loops for algorithms in production Utilizing Amazon systems and tools to effectively work with terabytes of data About the team Last Mile Execution Analytics (LMEA) team of JP works as an integral part of Amazon Logistics to ensure that its business intelligence, analytics, tools and planning needs are met. By providing information, insight, and decision support, we strive to enable success of all parts of AMZL. Our customer set includes senior management, station operations, external vendors, long-term planning, Ops technology (Voice of the Delivery Station, Voice of the Customer), network planning, and pretty much every BI and Ops teams. Voice of Employee [Work Life Harmony] We believe, it is important to spend private time such as spending time with your family or doing anything you like to spur innovation. Amazon promotes a fulfilling and flexible work style according to the work volume and lifestyle of each employee.
US, CA, San Francisco
About Twitch Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch on Linkedin, Twitter and on our Blog. About the role: Twitch builds data-driven machine learning solutions across several rich problem spaces: Natural Language Processing (NLP), Recommendations, Semantic Search, Classification/Categorization, Anomaly Detection, Forecasting, Safety, and HCI/Social Computing/Computational Social Science. As an Intern, you will work with a dedicated Mentor and Manager on a project in one of these problem areas. You will also be supported by an Advisor and participate in cohort activities such as research teach backs and leadership talks. This position can also be located in San Francisco, CA or virtual. You Will: Solve large-scale data problems. Design solutions for Twitch's problem spaces Explore ML and data research
US, CA, San Francisco
About Twitch Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch on Linkedin, Twitter and on our Blog. About the role: Twitch builds data-driven machine learning solutions across several rich problem spaces: Natural Language Processing (NLP), Recommendations, Semantic Search, Classification/Categorization, Anomaly Detection, Forecasting, Safety, and HCI/Social Computing/Computational Social Science. As an Intern, you will work with a dedicated Mentor and Manager on a project in one of these problem areas. You will also be supported by an Advisor and participate in cohort activities such as research teach backs and leadership talks. This position can also be located in San Francisco, CA or virtual. You Will: Solve large-scale data problems. Design solutions for Twitch's problem spaces Explore ML and data research
LU, Luxembourg
Are you a talented and inventive scientist with a strong passion about modern data technologies and interested to improve business processes, extracting value from the data? Would you like to be a part of an organization that is aiming to use self-learning technology to process data in order to support the management of the procurement function? The Global Procurement Technology, as a part of Global Procurement Operations, is seeking a skilled Data Scientist to help build its future data intelligence in business ecosystem, working with large distributed systems of data and providing Machine Learning (ML) and Predictive Modeling expertise. You will be a member of the Data Engineering and ML Team, joining a fast-growing global organization, with a great vision to transform the Procurement field, and become the role model in the market. This team plays a strategic role supporting the core Procurement business domains as well as it is the cornerstone of any transformation and innovation initiative. Our mission is to provide a high-quality data environment to facilitate process optimization and business digitalization, on a global scale. We are supporting business initiatives, including but not limited to, strategic supplier sourcing (e.g. contracting, negotiation, spend analysis, market research, etc.), order management, supplier performance, etc. We are seeking an individual who can thrive in a fast-paced work environment, be collaborative and share knowledge and experience with his colleagues. You are expected to deliver results, but at the same time have fun with your teammates and enjoy working in the company. In Amazon, you will find all the resources required to learn new skills, grow your career, and become a better professional. You will connect with world leaders in your field and you will be tackling Data Science challenges to ensure business continuity, by taking the right decisions for your customers. As a Data Scientist in the team, you will: -be the subject matter expert to support team strategies that will take Global Procurement Operations towards world-class predictive maintenance practices and processes, driving more effective procurement functions, e.g. supplier segmentation, negotiations, shipping supplies volume forecast, spend management, etc. -have strong analytical skills and excel in the design, creation, management, and enterprise use of large data sets, combining raw data from different sources -provide technical expertise to support the development of ML models to facilitate intelligent digital services, such as Contract Lifecycle Management (CLM) and Negotiations platform -cooperate closely with different groups of stakeholders, e.g. data/software engineers, product/program managers, analysts, senior leadership, etc. to evaluate business needs and objectives to set up the best data management environment -create and share with audiences of varying levels technical papers and presentations -deal with ambiguity, prioritizing needs, and delivering results in a dynamic environment Basic qualifications -Master’s Degree in Computer Science/Engineering, Informatics, Mathematics, or a related technical discipline -3+ years of industry experience in data engineering/science, business intelligence or related field -3+ years experience in algorithm design, engineering and implementation for very-large scale applications to solve real problems -Very good knowledge of data modeling and evaluation -Very good understanding of regression modeling, forecasting techniques, time series analysis, machine-learning concepts such as supervised and unsupervised learning, classification, random forest, etc. -SQL and query performance tuning skills Preferred qualifications -2+ years of proficiency in using R, Python, Scala, Java or any modern language for data processing and statistical analysis -Experience with various RDBMS, such as PostgreSQL, MS SQL Server, MySQL, etc. -Experience architecting Big Data and ML solutions with AWS products (Redshift, DynamoDB, Lambda, S3, EMR, SageMaker, Lex, Kendra, Forecast etc.) -Experience articulating business questions and using quantitative techniques to arrive at a solution using available data -Experience with agile/scrum methodologies and its benefits of managing projects efficiently and delivering results iteratively -Excellent written and verbal communication skills including data visualization, especially in regards to quantitative topics discussed with non-technical colleagues
US, CA, San Francisco
About Twitch Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch on Linkedin, Twitter and on our Blog. About the role: Twitch builds data-driven machine learning solutions across several rich problem spaces: Natural Language Processing (NLP), Recommendations, Semantic Search, Classification/Categorization, Anomaly Detection, Forecasting, Safety, and HCI/Social Computing/Computational Social Science. As an Intern, you will work with a dedicated Mentor and Manager on a project in one of these problem areas. You will also be supported by an Advisor and participate in cohort activities such as research teach backs and leadership talks. This position can also be located in San Francisco, CA or virtual. You Will: Solve large-scale data problems. Design solutions for Twitch's problem spaces Explore ML and data research
US, CA, San Francisco
About Twitch Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch on Linkedin, Twitter and on our Blog. About the role: Twitch builds data-driven machine learning solutions across several rich problem spaces: Natural Language Processing (NLP), Recommendations, Semantic Search, Classification/Categorization, Anomaly Detection, Forecasting, Safety, and HCI/Social Computing/Computational Social Science. As an Intern, you will work with a dedicated Mentor and Manager on a project in one of these problem areas. You will also be supported by an Advisor and participate in cohort activities such as research teach backs and leadership talks. This position can also be located in San Francisco, CA or virtual. You Will: Solve large-scale data problems. Design solutions for Twitch's problem spaces Explore ML and data research
US, CA, San Francisco
About Twitch Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch on Linkedin, Twitter and on our Blog. About the role: Twitch builds data-driven machine learning solutions across several rich problem spaces: Natural Language Processing (NLP), Recommendations, Semantic Search, Classification/Categorization, Anomaly Detection, Forecasting, Safety, and HCI/Social Computing/Computational Social Science. As an Intern, you will work with a dedicated Mentor and Manager on a project in one of these problem areas. You will also be supported by an Advisor and participate in cohort activities such as research teach backs and leadership talks. This position can also be located in San Francisco, CA or virtual. You Will: Solve large-scale data problems. Design solutions for Twitch's problem spaces Explore ML and data research
US, CA, San Francisco
About Twitch Launched in 2011, Twitch is a global community that comes together each day to create multiplayer entertainment: unique, live, unpredictable experiences created by the interactions of millions. We bring the joy of co-op to everything, from casual gaming to world-class esports to anime marathons, music, and art streams. Twitch also hosts TwitchCon, where we bring everyone together to celebrate, learn, and grow their personal interests and passions. We’re always live at Twitch. Stay up to date on all things Twitch on Linkedin, Twitter and on our Blog. About the role: Twitch builds data-driven machine learning solutions across several rich problem spaces: Natural Language Processing (NLP), Recommendations, Semantic Search, Classification/Categorization, Anomaly Detection, Forecasting, Safety, and HCI/Social Computing/Computational Social Science. As an Intern, you will work with a dedicated Mentor and Manager on a project in one of these problem areas. You will also be supported by an Advisor and participate in cohort activities such as research teach backs and leadership talks. This position can also be located in San Francisco, CA or virtual. You Will: Solve large-scale data problems. Design solutions for Twitch's problem spaces Explore ML and data research
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