ucd-gunrock-team-650px.jpg
Location: Davis, CA, USA
Faculty advisor: Zhou Yu

Gunrock (2018)

Named for our university's mascot, Gunrock, our team is a group of students who all share a passion for improving everyday human experiences through artificial intelligence.

Our team consists of 14 graduate and undergraduate computer science and electrical and computer engineering students with diverse, international perspectives. Our fearless leader is Zhou Yu, an assistant professor of computer science who was recently recognized in Forbes' 2018 30 Under 30 in Science list for her research in developing algorithms that enable software to adapt to users. Using our combined knowledge and expertise in developing large-scale distributed computing platforms, sub-systems, machine learning and application software, our team can't wait to use Amazon's platform and user pool to tackle the real-world needs of the general public.

Chun-Yen C. - Team leader

Chun-Yen was a senior software engineer with 5 years hands-on experience specializing on developing a large-scale distributed platform and scalable machine learning systems, in telecommunication company HTC. He received his master's degree in Communication Engineering from National Taiwan University in 2012.

Chun-Yen is currently a first-year master student and a Graduate Student Researcher in computer science department at the University of California, Davis. His main focus is to build a data management framework for the general usage of visualization systems and architect a robust framework for the chatbot system.

Ashwin B.

I am a Masters in Computer Science student studying at the University of California, Davis. I am a passionate programmer having a strong Data Structures and Algorithms knowledge base. In this information age, my research interest lies in Data Science/ Data Analytics. Previously, I have worked with Dell-EMC where I applied the concept of Software Defined Networking to WAN to implement an SD-WAN solution which reduced the network reconfiguration speed by 60%. My hobbies include but are not limited to sketching, writing, reading, hiking, adventure sports and exploring the unknown. I love trying out new things and having new experiences.

Austin C.

I earned my Neuroscience B.S. at University of California, Los Angeles, with a focus on psychology and cognitive science. During my undergraduate, I started learning programming and mobile app development and switched my pursuit to computer science. I have also taken coursework in machine learning and neural networks on top of my major. I am pursuing my masters in computer science at UC Davis focusing on NLP, HCI and dialogue systems and researching under Prof. Zhou Yu. My current project is a dialogue-based movie recommendation system that generates recommendation using matrix factorization and collaborative filtering.

Weiming W.

N/A

Dian Y.

I am a first year PhD student working with Prof. Kenji Sagae on dialogue systems and machine translation at University of California, Davis. We are currently working on dialogue state tracking and parsing. Besides NLP, I am also interested in computer vision. Before this, I earned a B.S. in Computer Science and a B.S. in Finance at New York University. I was advised by Prof. Keith Ross working on reinforcement learning with a focus on natural language processing, as well as researching on computer networking.

Giritheja S.

I am a first year graduate student majoring in Computer Science. I graduated from the National Institute of Technology, Karnataka, India in 2017 with a major in Electrical and Electronics engineering. I have previously worked as a Summer Intern in the Cloud team of Fidelity Investments. I contribute to Open Source organizations involving Software Development. My recent course project involved exploring Deep Learning techniques to recover variable names from minified javascript files, I was intrigued by applications of Deep Learning and AI. I look forward to exploring it.

Kevin J.

I earned my Computer Science B.S and Computer Engineering B.S at the University of California, Santa Cruz. At the University of California, Davis I am currently working with Professor Yu Zhou for a Ph.D. in NLP and dialogue systems. My work in dialogue systems has led me to create a movie recommendation dialogue bot using collaborative filtering and matrix factorization.

Mingyang Z.

Previously, I worked with Professor Jason Corso on video activity segmentation and video classification research problem where I have experience of using sparse coding, CNN and RNN. I also did a humor classification project with Professor Rada Mihalcea to classify whether an image can pair with a humorous punchline to make good memes. Currently, I am working with Professor Yu Zhou at UC Davis for Ph.D, where I worked on the research problem of multimodality machine translation research. I implemented a sequence to sequence model and a visual semantic meaning embedding algorithm as the starting baseline model for this research.

Shreenath I.

I'm a first year Master's student at UC Davis with my areas of research being Software Engineering, Distributed Operating Systems and Machine Learning. I received my Bachelor's in Computer Science in 2015 from the University of Pune and I've worked with Fidelity National Information Services for two years as a Product Development Engineer. I have primarily worked on Python, Django, and Buildbots in a Continuous Integration environment to facilitate the build and release process. I have worked with recommendation systems and language processing before and I look forward to using my experience and building on it through this project.

Yi Mang (Terry) Y.

I am an undergraduate Computer Science major interested in artificial intelligence. Conversational artificial intelligence is enabling a natural and engaging way for people to interact with machines. It is an exciting time but creating a smart socialbot presents many challenges. For our team, I bring my experience in building full-stack software systems that integrate machine learning models. I also have research experience in applying deep learning to computer vision problems.

Antara B.

I'm a first year Master's student at UC Davis in computer science and my research interests lie in machine learning and natural language processing. I completed my undergraduate degree in computer science in 2017 from SRM University and I've worked on computer vision and NLP problems as part of my internship at Medyug Technologies.

Zhou Yu - Faculty advisor

Education: Ph.D in Language Technology Institute, School of Computer Science, Carnegie Mellon University, 2017

B.S. in Computer Science Department & B.A. in the Foreign Language Department with a linguistics focus in Zhejiang University, 2011

Professional Experience: Assistant Professor, University of California, Davis, 2017-present

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US, NY, New York
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US, NY, New York
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US, NY, New York
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US, WA, Seattle
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AU, VIC, Melbourne
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US, CA, San Francisco
Amazon’s Frontier AI & Robotics (FAR) team is seeking a Member of Technical Staff to drive foundational research and build intelligent robotic systems from the ground up. In this role, you will operate at the intersection of cutting-edge AI research and real-world robotics - conducting original research, publishing, and deploying your innovations into production systems at Amazon scale. We’re looking for researchers who think from first principles, push the boundaries of what’s possible, and take full ownership of turning breakthrough ideas into working systems.  You will join the next revolution in robotics, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll be at the forefront of developing breakthrough foundation models and full-stack robotics systems that enable robots to perceive, understand, and interact with the world in unprecedented ways. 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Key job responsibilities - Drive independent research initiatives across the robotics stack, driving breakthrough approaches through hands-on research and development in areas including robot co-design, dexterous manipulation mechanisms, innovative actuation strategies, state estimation, low-level control, system identification, reinforcement learning, sim-to-real transfer, as well as foundation models focusing on breakthrough approaches in perception, and manipulation. - Lead and Guide technical direction for full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development - Develop and optimize control algorithms and sensing pipelines that enable robust performance in production environments - Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications - Contribute to team's technical decisions and influence implementation strategies to help shape our approach to next-generation robotics challenges - Mentor fellow researchers while maintaining solid individual technical contributions A day in the life - Design and implement novel foundation model architectures and innovative systems and algorithms, leveraging our extensive infrastructure to prototype and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges across the full robotics stack - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions and brainstorming sessions with team leaders, fellow researchers and key stakeholders - Conduct experiments and prototype new ideas using our massive compute cluster and extensive robotics infrastructure - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through innovative foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.
US, CA, San Francisco
Amazon’s Frontier AI & Robotics (FAR) team is seeking a Member of Technical Staff to drive foundational research and build intelligent robotic systems from the ground up. In this role, you will operate at the intersection of cutting-edge AI research and real-world robotics - conducting original research, publishing, and deploying your innovations into production systems at Amazon scale. We’re looking for researchers who think from first principles, push the boundaries of what’s possible, and take full ownership of turning breakthrough ideas into working systems.  You will join the next revolution in robotics, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll be at the forefront of developing breakthrough foundation models and full-stack robotics systems that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive technical excellence and independent research initiatives in areas such as locomotion, manipulation, perception, sim2real transfer, multi-modal, multi-task robot learning, designing novel frameworks that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You’ll have the freedom to pursue ambitious research directions while leveraging Amazon’s vast computational resources to tackle ambiguous problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications. Key job responsibilities - Drive independent research initiatives across the robotics stack, including robot co-design, dexterous manipulation mechanisms, innovative actuation strategies, state estimation, low-level control, system identification, reinforcement learning, sim-to-real transfer, as well as foundation models focusing on breakthrough approaches in perception, and manipulation, for example open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Guide technical direction for full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development, ensuring robust performance in production environments - Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications - Contribute to team's technical decisions and influence implementation strategies to help shape our approach to next-generation robotics challenges - Mentor fellow researchers while maintaining solid individual technical contributions A day in the life - Design and implement novel foundation model architectures and innovative systems and algorithms, leveraging our extensive infrastructure to prototype and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges across the full robotics stack - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions and brainstorming sessions with team leaders, fellow researchers and key stakeholders - Conduct experiments and prototype new ideas using our massive compute cluster and extensive robotics infrastructure - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through innovative foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.
IN, KA, Bengaluru
Amazon is looking for a passionate, talented, and inventive Applied Scientists with machine learning background to help build industry-leading Speech and Language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV). Key job responsibilities Amazon is looking for a passionate, talented, and inventive Applied Scientists with machine learning background to help build industry-leading Speech and Language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV). As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services that make use of speech and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, and structured data sources, and large-scale computing resources to accelerate advances in spoken language understanding. We are hiring in all areas of human language technology: ASR, MT, NLU, text-to-speech (TTS), and Dialog Management, in addition to Computer Vision. We are also looking for talents with experiences/expertise in building large-scale, high-performing systems. A day in the life 0
IN, KA, Bengaluru
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major responsibilities - Use machine learning and analytical techniques to create scalable solutions for business problems - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes - Design, development, evaluate and deploy innovative and highly scalable models for predictive learning - Research and implement novel machine learning and statistical approaches - Work closely with software engineering teams to drive real-time model implementations and new feature creations - Work closely with business owners and operations staff to optimize various business operations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Mentor other scientists and engineers in the use of ML techniques A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the International Emerging Stores organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team Central Machine Learning team works closely with the IES business and engineering teams in building ML solutions that create an impact for Emerging Marketplaces. This is a great opportunity to leverage your machine learning and data mining skills to create a direct impact on millions of consumers and end users.
US, TX, Austin
What happens when you combine startup speed with Amazon-scale impact? You get this team. Amazon Enterprise Security Products is a newly launched group building intelligent, cloud-agnostic security tools using AI-first development practices. Here, you build AI and you build with AI — at the same time. This role is a chance to shape the future of security tooling with a small, fast team that ships like a startup but deploys at Amazon scale. We're looking for a Data Scientist who thrives at the intersection of applied ML, agentic AI, and security. You'll design and deploy models that detect threats, power intelligent agents, and make security decisions at cloud scale. You'll work shoulder-to-shoulder with SDEs, applied scientists, security researchers, and PMs on a team where the best idea wins, regardless of title or tenure. 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We're a small team where there are no layers between you and the decision, no waiting quarters to see your work reach customers. Every team member brings an owner's mentality. If there's a problem worth solving, we solve it. No mission is beyond reach, no detail beneath our attention. We move fast, we ship fast, and we learn from what we ship. This is where builders who want to make the impossible routine come to do their best work. Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.