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Earlier this year, eight scientists were named as 2021 Amazon AI4Science Fellows at Caltech. The program is a result of a collaboration between Caltech and Amazon focused on supporting the AI4Science initiative, and its goal of sharing advances in artificial intelligence and machine learning.
Machine learning

Caltech names eight AI4Science fellows supported by Amazon

Amazon is collaborating with Caltech to support research, education, and outreach programs that help build bridges between AI and other areas of science and engineering.

By Douglas Gantenbein
April 30, 2021
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In January, eight scientists were named as 2021 Amazon AI4Science Fellows at Caltech, the world-renowned science and engineering research institution based in Pasadena, Calif. The Fellows program is a result of a collaboration between Caltech and Amazon around supporting the AI4Science initiative and its goal of sharing the latest advances in artificial intelligence (AI) and machine learning (ML) to benefit all branches of scientific and engineering research.

There’s a huge level of demand among graduate students and post-doctoral scholars across campus to leverage the techniques and advantages afforded by using AI and machine learning in their own research.
Yisong Yue

“Amazon’s gift will have a real impact on our program,” said Yisong Yue, professor of Computing and Mathematical Sciences and co-founder of the AI4Science initiative. “There’s a huge level of demand among graduate students and post-doctoral scholars across campus to leverage the techniques and advantages afforded by using AI and machine learning in their own research.”

“Caltech is uniquely placed to be a leader in AI4science given its interdisciplinary collaborations and small size,” added Anima Anandkumar, Bren Professor of Computing and Mathematical Sciences and co-founder of the AI4Science initiative. “We thank Amazon for supporting this groundbreaking initiative.”

For those students specializing in data sciences, Yue said, “it allows them to be exposed to the datasets and research questions faced by scientists in other fields, as well as in companies such as Amazon, and to push the boundaries of existing AI and machine-learning algorithms to effectively address these questions.”

“At Amazon, we strongly believe that AI should be an integral part of all science, not just computer science,” said Marzia Polito, AWS senior manager of applied science. “We are building products supporting the use of AI in many fields of science and many science-based business applications. We are thrilled to collaborate with Caltech, a world-class institution doing ground-breaking science work, and we are honored to have a chance to contribute to their amazing results. There could be no better evidence toward a future where AI and science thrive together.”

This year’s cohort of Fellows comes from the Division of Biology and Biological Engineering, the Division of Chemistry and Chemical Engineering, and the Division of Engineering and Applied Science, reflecting the broad range of research being explored. The Fellows will apply cutting-edge ML and AI techniques to research areas ranging from neural prosthetics and theoretical chemistry, to the human microbiome.

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Earlier this year, eight scientists were named as 2021 Amazon AI4Science Fellows at Caltech. The program is a result of a collaboration between Caltech and Amazon focused on supporting the AI4Science initiative, and its goal of sharing advances in artificial intelligence and machine learning.
Credit: Glynis Condon

The Amazon AI4Science Fellows and research areas are:

  • Carmen Amo Alonso, a graduate student pursuing her PhD in control and dynamical systems in the lab of John Doyle, Jean-Lou Chameau Professor of Control and Dynamical Systems, Electrical Engineering, and Bioengineering, is studying the application of AI to large-scale complex systems in areas as diverse as understanding the gut microbiome to designing optimized “smart” grids.
  • Sara Beery, a graduate student pursuing her PhD in computing and mathematical sciences in the lab of Pietro Perona, Allen E. Puckett Professor of Electrical Engineering, is developing approaches to collect global-scale, real-time ecological data for conservation purposes.
  • Charles Guan, a graduate student pursuing his PhD in bioengineering in the lab of Richard Andersen, James G. Boswell Professor of Neuroscience, T&C Chen Brain-Machine Interface Center Leadership Chair, and director of the T&C Brain-Machine Interface Center, is developing decoding algorithms for neural prostheses and studying the neural basis of movement.
  • Kadina Johnston, a graduate student pursuing her PhD in bioengineering in the lab of Nobel-prize winner Frances Arnold, Linus Pauling Professor of Chemical Engineering, Bioengineering, and Biochemistry and director of the Donna and Benjamin M. Rosen Bioengineering Center, is applying deep learning techniques to the directed evolution approach for enzyme engineering.
  • Nikola Kovachki, a graduate student pursuing his PhD in applied and computational mathematics in the lab of Andrew Stuart, Bren Professor of Computing and Mathematical Sciences, is using deep learning techniques for solving partial differential equations, which has applications for climate modeling, understanding turbulent flow of fluids, and a wide range of materials science problems.
  • Zhuoran Qiao, a graduate student pursuing his PhD in chemistry in the lab of professor of chemistry Tom Miller, is developing physics-based machine learning methods for studying problems in complex chemical systems.    
  • Guannan Qu, a post-doctoral scholar working under the supervision of Steven Low, Frank J. Gilloon Professor of Computing and Mathematical Sciences and Electrical Engineering, and Adam Wierman, professor of computing and mathematical sciences and director of Information Science and Technology, is developing multi-agent reinforcement learning approaches that are scalable, distributed, and have provable guarantees such that they will be usable for safety-critical applications.
  • He Sun, a post-doctoral scholar working under the supervision of Katie Bouman, assistant professor of computing and mathematical sciences, electrical engineering and astronomy and Rosenberg Scholar, is developing new machine learning algorithms that can improve current computational imaging approaches.

The diverse interests of the Fellows reflect a trend in AI and machine learning that emphasizes cross-disciplinary research and is in line with the AI4Science focus.

“Today we need students who are experts in their own fields, but who also can communicate across different fields,” Yue said. “Effective communication requires a mix of fundamentally sound rigorous thinking coupled with a broad perspective on how to apply that approach to wide range of domains, in order to reveal and distill the core technical challenges that underlie the pressing problems facing science and engineering research today.”

The AI4Science Fellows program is one component within a larger collaboration between Amazon and Caltech. In the area of AI4Science, Amazon is also providing funds for Caltech’s Carver Mead New Adventures Fund, AWS credits for research projects across campus, and support for AI4Science events to build community and share research results.

Beyond the AI4Science initiative, Caltech and Amazon are collaborating in a number of other areas. A group of scientists within AWS’s Amazon Rekognition team is a part of Caltech’s Innovation Center, a building near campus that houses Caltech corporate collaborators and startups. In 2019, AWS and Caltech also announced a collaboration around quantum computing, which will include the AWS Center for Quantum Computing, set to open later this year.

“Caltech prides itself as being an incubator for concepts like AI4Science and next-generation technologies like quantum computing,” said Caltech’s Kaushik Bhattacharya, vice provost for Research and Howell N. Tyson, Sr., Professor of Mechanics and Materials Science. “Our small size, our relentless focus on the most challenging scientific questions — along with our close-knit community that is interdisciplinary by design — encourage and enable us to always be pioneering in the application of tools and techniques from other fields to all areas of science and engineering. To help make sure our findings have impacts beyond academia, we greatly value our collaborations with partners like Amazon.”

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Douglas Gantenbein
Douglas Gantenbein is a contributor to Amazon Science.

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Sr. Economist
US, WA, Seattle
Amazon strives to be Earth's most customer-centric company. To achieve this, we hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment.Economists for Amazon will be expected to work directly with senior management on key business problems faced in retail and marketing. The role allows you to influence company-wide strategy by applying the frontier of economic thinking to forecasting, program evaluation, customer behavior and other areas. Economists at Amazon will be expected to develop new techniques to process large data sets, use econometric models and methods to address complex problems, design and test hypothesis on customer pain points and key growth ideas and contribute to design of automated systems around the company. Economists in our team will work closely with other research scientists, machine learning experts, and economists globally to design new frameworks for understanding business outcome and what impacts customer experiences. Our economists and scientists work closely with software engineers to put algorithms into practice.We are an interdisciplinary team on the cutting edge of economics, statistical analysis, and machine learning whose mission is to solve AI and ML problems that have high risk with high returns Our team seeks an outstanding econometrician with demonstrated experience tackling large-scale time-series forecasting challenges. We prize creative problem solvers with the ability to adapt and extend cutting-edge forecasting models to the unique and interesting problems we have in measuring customer experiences and Amazon business outcome. Our problems include forecasting key customer experiences metrics at different levels of granularities and explaining the drivers of the changes in these metrics. The ideal candidate combines acumen in statistics and applied time-series modeling to grapple with these and other challenges and guide decision-making at the highest levels of accuracy and model explain-ability.
Applied Scientist
US, CA, Cupertino
Amazon's Simple Storage Service (S3) offers industry-leading scalability, data availability, security, and performance. S3’s Automated Reasoning Group (S3-ARG) develops and applies automated reasoning techniques to deliver correct, secure, durable, and available distributed systems and storage services. S3 is complex: it consists of over 300 microservices each of which is a distributed system. With a very large number of servers and 10s of millions of requests per second, it is also highly concurrent. S3 has a sizable codebase, developed and maintained by a large team of engineers. Getting such a complex and fast-evolving system right requires developing cutting edge automated reasoning methods that are continuously integrated into the software development process. This is what our team does.We work on techniques ranging from deductive proofs to model checking, from static analysis to runtime verification of protocols. We work both at the design and the code level, and connecting the two is essential for us. We partner with development teams to make sure that our methods are deployed across S3 and that correctness is maintained as the software evolves. We have had significant success with adoption and we are key contributors to recent S3 launches such as strong consistency. We are developing innovative methods all the time. We publish our results at conferences and journals.We are a diverse team and are looking for teammates who are enthusiastic to work on these problems and further the state of the art with us. We are seeking candidates who are deep in one area of expertise but also broad enough to take on the most complex cloud computing challenges. If you are interested in exploring, please e-mail s3-arg-jobs@amazon.com.About UsInclusive 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. 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.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.
Data Scientist
US, WA, Seattle
At Alexa Shopping, we strive to enable shopping in everyday life. We allow customers to instantly order whatever they need, by simply interacting with their Smart Devices such as Amazon Show, Spot, Echo, Dot or Tap. Our Services allow you to shop, no matter where you are or what you are doing, you can go from 'I want that' to 'that's on the way' in a matter of seconds. We are seeking the industry's best to help us create new ways to interact, search and shop. Join us, and you'll be taking part in changing the future of everyday lifeWe are seeking a Data Scientist to be part of the NLU science team for Alexa Shopping. This is a strategic role to shape and deliver our technical strategy in developing and deploying NLU, Machine Learning solutions to our hardest customer facing problems. Our goal is to delight customers by providing a conversational interaction. These initiatives are at the heart of the organization and recognized as the innovations that will allow us to build a differentiated product that exceeds customer expectations. We're a high energy, fast growth business excited to have the opportunity to shape Alexa Shopping NLU is defined for years to come. If this role seems like a good fit, please reach out, we'd love to talk to you.This role requires working closely with business, engineering and other scientists within Alexa Shopping and across Amazon to deliver ground breaking features. You will lead high visibility and high impact programs collaborating with various teams across Amazon. You will work with a team of Language Engineers and Scientists to launch new customer facing features and improve the current features.
Data Scientist I - AMZ5650
US, NY, New York
MULTIPLE POSITIONS AVAILABLEEntity: Amazon Web Services, Inc.Title: Data Scientist ILocation: New York, NYPosition Responsibilities:Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production.Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000
Applied Scientist - AMZ5624
US, WA, Seattle
MULTIPLE POSITIONS AVAILABLEEntity: Amazon.Com Services LLCTitle: Applied ScientistWorksite: Seattle, WAPosition Responsibilities:Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists.Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000
Data Scientist, Public Sector - AWS Professional Services
US, CO, Denver
Excited by using massive amounts of data to develop Machine Learning (ML) and Deep Learning (DL) models? Want to help public sector, medical center and non-profit agencies derive business value through the adoption of Artificial Intelligence (AI)? Eager to learn from many different enterprise’s use cases of AWS ML and DL? Thrilled to be key part of Amazon, who has been investing in Machine Learning for decades, pioneering and shaping the world’s AI technology?At Amazon Web Services (AWS), we are helping large enterprises build ML and DL models on the AWS Cloud. We are applying predictive technology to large volumes of data and against a wide spectrum of problems. Our Professional Services organization works together with our AWS customers to address their business needs using AI.AWS Professional Services is a unique consulting team. We pride ourselves on being customer obsessed and highly focused on the AI enablement of our customers. If you have experience with AI, including building ML or DL models, we’d like to have you join our team. You will get to work with an innovative company, with great teammates, and have a lot of fun helping our customers.If you do not live in a market where we have an open Data Scientist position, please feel free to apply. Our Data Scientists can live in any location where we have a Professional Service office.A successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term solutions. It will be a person who likes to have fun, loves to learn, and wants to innovate in the world of AI. Major responsibilities include:· Understand the customer’s business need and guide them to a solution using our AWS AI Services, AWS AI Platforms, AWS AI Frameworks, and AWS AI EC2 Instances .· Assist customers by being able to deliver a ML / DL project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models to deliver business impact to the organization.· Use Deep Learning frameworks like PyTorch, Tensorflow, and MxNet to help our customers build DL models.· Use SparkML and Amazon Machine Learning (AML) to help our customers build ML models.· Work with our Professional Services Big Data consultants to analyze, extract, normalize, and label relevant data.· Work with our Professional Services DevOps consultants to help our customers operationalize models after they are built.· Assist customers with identifying model drift and retraining models.· Research and implement novel ML and DL approaches, including using FPGA.· This position can have periods of up to 10% travel.
Data Scientist
US, WA, Seattle
At Alexa Shopping, we strive to enable shopping in everyday life. We allow customers to instantly order whatever they need, by simply interacting with their Smart Devices such as Amazon Show, Spot, Echo, Dot or Tap. Our Services allow you to shop, no matter where you are or what you are doing, you can go from 'I want that' to 'that's on the way' in a matter of seconds. We are seeking the industry's best to help us create new ways to interact, search and shop. Join us, and you'll be taking part in changing the future of everyday lifeWe are seeking a Data Scientist to be part of the Correction and Automated Recovery (CARe) team for Alexa Shopping. Our team focuses on solving the hard problem of recovering from shopping errors in the Alexa pipeline and improve customer CX. The solutions will help address unique shopping challenges and maximize the self-learning benefits for shopping. This is a strategic role to shape and deliver our science strategy in developing and deploying Machine Learning solutions to our hardest customer facing problems. The initiatives are at the heart of the organization and recognized as the innovations that are ground breaking and will allow us to exceed customer expectations. If this role seems like a good fit, please reach out, we'd love to talk to you.This role requires working closely with business, engineering and other scientists within Alexa, Shopping and across Amazon to deliver ground breaking features. You will lead high visibility and high impact programs collaborating with various teams across Amazon. You will work with a team of SDEs and Scientists to launch new customer facing features and improve the current features.
Applied Scientist, Alexa AI
US, MA, Cambridge
The Alexa Artificial Intelligence (AI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background, to help build industry-leading Speech and Language technology.About the hiring groupThe Alexa AI team has a mission to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers.Job responsibilitiesAs an Applied Scientist with the Alexa AI team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding.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, please visit https://www.amazon.jobs/en/disability/us.
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