uci-zotbot.jpg
Location: Irvine, CA, USA
Faculty advisor: Sameer Singh

ZotBot

Our team envisions creating a socialbot that will be able to engage in memorable interactions, and can tailor the conversation to reflect the interests of each unique individual.

Our team envisions creating a socialbot that will be able to engage in memorable interactions, and can tailor the conversation to reflect the interests of each unique individual.

William S. - Team leader

William is currently a fifth year undergraduate double majoring in Computer Science and Computational Physics, with a minor in mathematics. His primary focus is information extraction and computational modeling.

Claire U.

Claire is an undergraduate mathematics major at UC Irvine. Her previous experience in programming focused on robotics projects and website design, mainly using Python. Claire is excited for this new experience as a project manager for ZotBot. She has gained valuable communication, organizational, and time management skills through her previous work experiences, as an intern at a nonprofit and a peer academic advisor at UCI. Currently, Claire manages projects that require correspondence among coworkers and is responsible for ensuring the projects are kept to their deadlines.

Yoshitomo M.

Yoshi is a Ph.D. candidate in Computer Science at UCI, working on Machine Learning and its application with Profs. Sameer Singh and Marco Levorato. Before UCI, he obtained his master's and bachelor's degrees from the University of Hyogo and National Institute of Technology, Akashi College, respectively. His master's and bachelor's thesis topics were on behavioral biometrics such as keystroke dynamics and flick authentication. In industry, his projects were on recommender systems for image and online advertisement, and ML model interpretability in NLP tasks.

Dheeru D.

Dheeru is a second year Ph.D. student working under Prof. Sameer Singh. She completed her master’s from LTI at Carnegie Mellon University before joining the Ph.D. program at UCI. Dheeru is interested in complex question and context understanding techniques applied to reading comprehension. Her current work is focused towards inducing natural language questions as programs that can be executed on unstructured context. Conversational agents add a layer of compositional complexity to questions which can be very challenging for machines. This confluence of user and context is exciting for me.

Yao D.

Yao is a Ph.D. candidate in Informatics at the University of California, Irvine (advisor: Katie Salen Tekinbas). Her research examines best practices in interaction design for children with disabilities, service design for speech language pathologists, and game design for therapy activities through touch-based and voice-based interfaces. Using both quantitative (e.g., experiment, survey) and qualitative (e.g., interviews, content analysis) techniques, Yao's empirical projects aim to transform clinical knowledge to inform technical design and development of educational, assistive, and health technology.

Xuan L.

Xuan is a first-year master's student majoring in statistics at the University of California, Irvine. She is a motivated learner with a strong foundation in mathematical and statistical theory. Her research interests lie in data science and machine learning. She is passionate about NLP and can’t wait to explore it!

Moeez Q.

Moeez is a 3rd year Informatics major at UCI and he loves technology.

Lyuyang H.

Lyuyang is a third-year computer science and engineering major at UC-Irvine. Having worked on two research projects where he built control systems for an autonomous sailboat and a linear generator, he has gained much experience in prototyping, research, and software engineering. Last Summer, Lyuyang joined MData (Shanghai) as a Data Engineer Intern and worked on REST APIs, search engines and databases. His interests in technology have also brought him to photography and filmmaking. His current project includes 3D reconstruction with video and image/sound generation with Generative Adversarial Networks.

Arsenii M.

Arseny is a second year Cognitive Science Ph.D. student in the University of California, Irvine. He has a diverse background: Psyhology, Neuroscience, and Machine Learning. In his work, Arseny combines his knowledge and skills of these disciplines in order to contribute to both AI and Cognitive Science research. To learn more, check out his website: r-seny.com.

Michelle L.

Michelle is a second year undergraduate student double majoring in Data Science and Business Economics. Her interests lie in machine learning and artificial intelligence.

Ilene D.

Ilene is an undergraduate Computer Science student at the University of California, Irvine specializing in algorithms with strong interest in blockchain and artificial intelligence. Ilene has experience in cloud computing and programming in object-oriented languages and AI languages. As a Software Developer Summer Intern at Stanford University, they built a REST API on the AWS platform. Ilene's hobbies include cooking, collecting vinyls, and investing in cryptocurrency. Ilene is excited to apply their knowledge and learn more skills while participating in the Alexa Prize.

Daniel A.

Daniel is a Ph.D. student in applied mathamatics, whose research focuses on using kernel based methods to solve partial differential equations. He brings a strong background in probabiliy, statistics, and numerical analysis to UCI's Alexa team.

Sameer Singh - Faculty advisor

Sameer Singh is an Assistant Professor of Computer Science at the University of California, Irvine. He is working on machine learning applied to natural language processing, in particular on explanations for black-box models, adversarial examples for NLP, information extraction, and question answering. Sameer was a postdoctoral researcher at the University of Washington and received his Ph.D. from the University of Massachusetts, Amherst, during which he also worked at Microsoft, Google, and Yahoo!. His group has received funding from Allen Institute for AI, NSF, DARPA, Adobe, and FICO.

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US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for healthcare. 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 forefront 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 other teams. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives You’ll need a strong background in AI/ML, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. 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 Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
US, WA, Seattle
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US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As a Senior Applied Scientist on our team, you will focus on building state-of-the-art ML models for healthcare. 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 forefront 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 other teams. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives You’ll need a strong background in AI/ML, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. 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 Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
US, CA, Sunnyvale
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Principal Applied Scientist with a strong deep learning background, to lead the development of industry-leading technology with multimodal systems. As a Principal Scientist within the Artificial General Intelligence (AGI) organization, you are a trusted part of the technical leadership. You bring business and industry context to science and technology decisions, set the standard for scientific excellence, and make decisions that affect the way we build and integrate algorithms. A Principal Applied Scientist will solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization. You are a hands-on scientific leader; develop solutions that are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility; and tackle intrinsically hard problems, acquiring expertise as needed. Principal Applied Scientists are expected to decompose complex problems into straightforward solutions. You amplify your impact by leading scientific reviews within your organization or at your location; and scrutinize and review experimental design, modeling, verification and other research procedures. You also probe assumptions, illuminate pitfalls, and foster shared understanding; align teams toward coherent strategies; and educate keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends. AGI Principal Applied Scientists help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads. You will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities You will be responsible for defining key research directions, inventing new machine learning techniques, conducting rigorous experiments, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. A Principal Applied Scientist will participate in organizational planning, hiring, mentorship and leadership development. You will also be build scalable science and engineering solutions, and serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).