ScottyBot

The ScottyBot team hails from Carnegie Mellon University (CMU), and is a joint venture between the Language Technologies and Robotics Institutes.

The CMU School of Computer Science (SCS) is considered to be one of the leading centers of artificial intelligence research in the world, with numerous federal grants, affiliated research institutes, degree programs, and awards in the areas of robotics, language technologies, and human-machine interaction.

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Jonathan F. — Team leader

Jonathan is a PhD Candidate in the Language Technologies Institute at CMU and a Research Scientist at Bosch Research. His research focuses on harnessing domain knowledge for multimodal representation learning, in robotics and autonomous driving. As a former researcher in a major U.S. defense contractor and research committee member for various U.S. Department of Energy programs in distributed sensing and control, he brings over a decade's worth of experience in institutional research and advanced development from public, private, and academic sectors. Jonathan holds Bachelor's and Master's degrees in Electrical & Computer Engineering from Carnegie Mellon.

Adhokshaja M.

Adhokshaja is a Masters student at the Language Technologies Institute at Carnegie Mellon University. He is interested in the confluence of the fields of Computer Vision, Multimodal Machine Learning and Reinforcement Learning, currently researching the domain of audio, video and action with Prof. Yonatan Bisk.

Benny J.

Benny is a student in Master of Computational Data Science. He is interested in natural language generation, ML infrastructure and system design. Prior to CMU, he completed his Bachelors in Computer Science from UC Berkeley.

Jessica Z.

Jessica Zhong is a student from Master of Computational Data Science in Languages Technology Institute at CMU. She has a keen interest in computer vision and multimodal machine learning, and she enjoyed solving real-world challenges during Simbot.

Jimin S.

Jimin is a 2nd year Master’s student in Language Technologies at Carnegie Mellon University, where she is co-advised by Yonatan Bisk and Jean Oh. Her research interest is in language grounding and embodied dialog.

Kushagra M.

Kushagra is a graduate student at CMU pursuing a Masters in Computational Data Science. He is advised by Prof. Louis-Philippe Morency and is presently working on Computer Vision problems for AR/VR glasses. His general research interests are in Computer Vision, Deep Learning and Multimodal ML.

Malaika V.

Malaika is a second year masters student in Computational Data Science at Carnegie Mellon University's Language Technologies Institute. She is interested in Natural Language Processing and Computer Vision, and enjoys working on problems in multimodal machine learning

Nikhil G.

Nikhil is a 2nd year Masters student in the Language Technologies Institute at Carnegie Mellon University. His interests lie in NLP and big data analytics. Prior to joining CMU, he was part of the Cloud team at VMWare.

Prasoon V.

Prasoon is a 2nd year Masters student in Computational Data Science at the Language Technologies Institute at CMU. His interests lie in embodied dialogue agents, multimodal representation learning, and safe and responsible AI. Prior to CMU, he worked at the Franchise Analytics group at Goldman Sachs, and completed Bachelors in Computer Science from IIT Varanasi, India.

Sai Vishwas P.

Sai is a Master's student in the Computational Data Science program at CMU. Sai's research interests are in the areas of multimodal machine learning and embodied AI.

Shubham V.

Shubham is a 2nd year Masters student in the Language Technologies Institute at Carnegie Mellon University. His research interests lie in question answering and cloud computing. Prior to joining CMU, he was an app developer at Oracle, and completed his Bachelors in Computer Science from IIT Roorkee, India.

Shubham P.

Shubham is a 2nd year Masters student in the Language Technologies Institute at Carnegie Mellon University. His research interests lie in NLP and multimodal machine learning. Prior to joining CMU, he worked in the Equities Trading group at Morgan Stanley.

Vineeth R.

Vineeth is a second year Masters Student in Language Technologies Institute at Carnegie Mellon University. Vineeth’s research currently focuses on computer vision and multimodal machine learning. Previously, Vineeth worked in the self-driving domain to build large scale perception models for object detection and lane segmentation.

Xinyue C.

Xinyue is a Masters in Computational Data Science student with experience in natural language tasks, including natural language QA and generation.

Yonatan Bisk — Faculty advisor

Yonatan Bisk is an assistant professor in the Languages Technology Institute at CMU. His work broadly falls into uncovering the latent structures of natural language; modeling the semantics of the physical world; and connecting language to perception and control.

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LU, Luxembourg
The Decision, Science and Technology (DST) team part of the global Reliability Maintenance Engineering (RME) is looking for a Senior Operations Research Scientist interested in solving challenging optimization problems in the maintenance space. Our mission is to leverage the use of data, science, and technology to improve the efficiency of RME maintenance activities, reduce costs, increase safety and promote sustainability while creating frictionless customer experiences. As a Senior OR Scientist in DST you will be focused on leading the design and development of innovative approaches and solutions by leading technical work supporting RME’s Predictive Maintenance (PdM) and Spare Parts (SP) programs. You will connect with world leaders in your field and you will be tackling customer's natural language challenges by carrying out a systematic review of existing solutions. The appropriate choice of methods and their deployment into effective tools will be the key for the success in this role. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail and outstanding ability in balancing technical leadership with strong business judgment to make the right decisions about model and method choices. Key job responsibilities • Provide technical expertise to support team strategies that will take EU RME towards World Class predictive maintenance practices and processes, driving better equipment up-time and lower repair costs with optimized spare parts inventory and placement • Implement an advanced maintenance framework utilizing Machine Learning technologies to drive equipment performance leading to reduced unplanned downtime • Provide technical expertise to support the development of long-term spares management strategies that will ensure spares availability at an optimal level for local sites and reduce the cost of spares A day in the life As a Senior OR Scientist in DST you will be focused on leading the design and development of innovative approaches and solutions by leading technical work supporting RME’s Predictive Maintenance (PdM) and Spare Parts (SP) programs. You will connect with world leaders in your field and you will be tackling customer's natural language challenges by carrying out a systematic review of existing solutions. The appropriate choice of methods and their deployment into effective tools will be the key for the success in this role. About the team Our mission is to leverage the use of data, science, and technology to improve the efficiency of RME maintenance activities, reduce costs, increase safety and promote sustainability while creating frictionless customer experiences. We are open to hiring candidates to work out of one of the following locations: Luxembourg, LUX
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Bellevue, WA, USA | Boston, MA, USA | Los Angeles, CA, USA | New York, NY, USA | San Francisco, CA, USA | Seattle, WA, USA | Sunnyvale, CA, USA
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Bellevue, WA, USA | Boston, MA, USA | Los Angeles, CA, USA | New York, NY, USA | San Francisco, CA, USA | Seattle, WA, USA | Sunnyvale, CA, USA
US, CA, Santa Clara
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US, WA, Seattle
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US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Bellevue, WA, USA | Boston, MA, USA | Los Angeles, CA, USA | New York, NY, USA | San Francisco, CA, USA | Seattle, WA, USA | Sunnyvale, CA, USA
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists in the Forecasting, Macroeconomics & Finance field document, interpret and forecast Amazon business dynamics. This track is well suited for economists adept at combining cutting edge times-series statistical methods with strong economic analysis and intuition. This track could be a good fit for candidates with research experience in: macroeconometrics and/or empirical macroeconomics; international macroeconomics; time-series econometrics; forecasting; financial econometrics and/or empirical finance; and the use of micro and panel data to improve and validate traditional aggregate models. Economists at Amazon are expected to work directly with our senior management and scientists from other fields on key business problems faced across Amazon, including retail, cloud computing, third party merchants, search, Kindle, streaming video, and operations. The Forecasting, Macroeconomics & Finance field utilizes methods at the frontier of economics to develop formal models to understand the past and the present, predict the future, and identify relevant risks and opportunities. For example, we analyze the internal and external drivers of growth and profitability and how these drivers interact with the customer experience in the short, medium and long-term. We build econometric models of dynamic systems, using our world class data tools, formalizing problems using rigorous science to solve business issues and further delight customers. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Bellevue, WA, USA | Boston, MA, USA | Los Angeles, CA, USA | New York, NY, USA | San Francisco, CA, USA | Seattle, WA, USA | Sunnyvale, CA, USA
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists in the Forecasting, Macroeconomics & Finance field document, interpret and forecast Amazon business dynamics. This track is well suited for economists adept at combining cutting edge times-series statistical methods with strong economic analysis and intuition. This track could be a good fit for candidates with research experience in: macroeconometrics and/or empirical macroeconomics; international macroeconomics; time-series econometrics; forecasting; financial econometrics and/or empirical finance; and the use of micro and panel data to improve and validate traditional aggregate models. Economists at Amazon are expected to work directly with our senior management and scientists from other fields on key business problems faced across Amazon, including retail, cloud computing, third party merchants, search, Kindle, streaming video, and operations. The Forecasting, Macroeconomics & Finance field utilizes methods at the frontier of economics to develop formal models to understand the past and the present, predict the future, and identify relevant risks and opportunities. For example, we analyze the internal and external drivers of growth and profitability and how these drivers interact with the customer experience in the short, medium and long-term. We build econometric models of dynamic systems, using our world class data tools, formalizing problems using rigorous science to solve business issues and further delight customers. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Bellevue, WA, USA | Boston, MA, USA | Los Angeles, CA, USA | New York, NY, USA | San Francisco, CA, USA | Seattle, WA, USA | Sunnyvale, CA, USA
US, WA, Seattle
Economists in the Forecasting, Macroeconomics & Finance field document, interpret and forecast Amazon business dynamics. This track is well suited for economists adept at combining cutting edge times-series statistical methods with strong economic analysis and intuition. This track could be a good fit for candidates with research experience in: macroeconometrics and/or empirical macroeconomics; international macroeconomics; time-series econometrics; forecasting; financial econometrics and/or empirical finance; and the use of micro and panel data to improve and validate traditional aggregate models. Economists at Amazon are expected to work directly with our senior management and scientists from other fields on key business problems faced across Amazon, including retail, cloud computing, third party merchants, search, Kindle, streaming video, and operations. The Forecasting, Macroeconomics & Finance field utilizes methods at the frontier of economics to develop formal models to understand the past and the present, predict the future, and identify relevant risks and opportunities. For example, we analyze the internal and external drivers of growth and profitability and how these drivers interact with the customer experience in the short, medium and long-term. We build econometric models of dynamic systems, using our world class data tools, formalizing problems using rigorous science to solve business issues and further delight customers. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Bellevue, WA, USA | Boston, MA, USA | Los Angeles, CA, USA | New York, NY, USA | San Francisco, CA, USA | Seattle, WA, USA | Sunnyvale, CA, USA
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Bellevue, WA, USA | Boston, MA, USA | Los Angeles, CA, USA | New York, NY, USA | San Francisco, CA, USA | Seattle, WA, USA | Sunnyvale, CA, USA