Athena

Athena is named after the Greek goddess of wisdom and strategy and is comprised of PhD and master's students researching conversational AI, natural language processing, and computer vision.

Coming straight from the redwoods of Santa Cruz, the Natural Language and Dialogue Systems Lab is making its fifth appearance in the competition. Our social bot will be able to use commonsense knowledge and external information to generate meaningful responses.

team athena 2023
Team Athena (2023)

Yue Fan - Team leader

Fan is a second year PhD student at UCSC. Fan received a master's robotics from Johns Hopkins University and a bachelor's in automation at Shandong University. Fan's study interests are in NLP, CV, and AI. Fan is focusing on how to improve intelligent embodied agents to perform better and converse with humans in real-world.

Saaket Agashe

Agashe is a master's student in the Computer Science Department at UCSC. Agashe's research interests include natural language processing, conversational AI, and, language-based visual grounding. Agashe previously worked studying predictive text systems through qualitative analysis and is currently working on visual grounding, specifically localization using spatial descriptions and dialogs.

Kevin Bowden

Bowden, a sixth year PhD candidate at UCSC, was a member of team Athena for SGC3 and SGC4 and previously led team SlugBot in SGC1 and SGC2. His primary focus has been on the user experience and the design of call flows to maximize user interest in the conversation. Most recently, his work on Athena has focused on his thesis topic: user modeling and personalization in open-domain conversational AI.

Winson Chen

Chen is a first-year master's student in the Applied Mathematics Department at UCSC. Chen earned a bachelors degree in computer science from UCSC in 2022. Chen has worked as undergraduate research assistant in ERIC Lab under Xin (Eric) Wang. Chen's research interests are natural language processing, computer vision, and machine learning.

Wen Cui

Cui is a PhD candidate specializing in deep learning, natural language processing, and conversational AI. Cui's research focuses on applying deep learning techniques and leveraging large-scale knowledge graphs to improve entity linking in open- domain dialogue systems.

Vrindavan Harrison

Harrison is a fifth year PhD student and a member of the Natural Language and Dialogue Systems lab. His research focuses on dialogue systems and natural language generation. Davan participated in the SBGC 3 and 4 as a member of Team Athena. Davan grew up in Santa Cruz and in his free time surfs and practices jiu jitsu.

Xing Wang - Faculty advisor

Xin (Eric) Wang is an assistant professor of computer science and engineering at UC Santa Cruz. His research interests include NLP, CV, and ML, with an emphasis on building embodied AI agents that can communicate with humans using natural language to perform real-world multimodal tasks. Xin has served as Area Chair for ACL, NAACL, EMNLP, ICLR, etc., and Senior Program Committee (SPC) for AAAI and IJCAI. He organized multiple workshops and tutorials at CVPR, ICCV, ACL, NAACL, AACL, etc. He has received a CVPR Best Student Paper Award (2019), an Amazon Alexa Prize Award (2022-2023), a Google Faculty Research Award (2022), etc.

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US, CA, San Francisco
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US, CA, San Francisco
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Member of Technical Staff with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Member of Technical Staff with the AGI team, you will lead the development of algorithms and modeling techniques, to advance the state of the art with LLMs. You will lead the foundational model development in an applied research role, including model training, dataset design, and pre- and post-training optimization. Your work will directly impact our customers in the form of products and services that make use of GenAI technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in LLMs. About the team The AGI team has a mission to push the envelope in GenAI with LLMs and multimodal systems, in order to provide the best-possible experience for our customers.
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US, WA, Seattle
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Alexa+ is Amazon’s next-generation, AI-powered virtual assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalized, and effective experience. As an Applied Scientist II on the Alexa Sensitive Content Intelligence (ASCI) team, you'll be part of an elite group developing industry-leading technologies in attribute extraction and sensitive content detection that work seamlessly across all languages and countries. In this role, you'll join a team of exceptional scientists pushing the boundaries of Natural Language Processing. Working in our dynamic, fast-paced environment, you'll develop novel algorithms and modeling techniques that advance the state of the art in NLP. Your innovations will directly shape how millions of customers interact with Amazon Echo, Echo Dot, Echo Show, and Fire TV devices every day. What makes this role exciting is the unique blend of scientific innovation and real-world impact. You'll be at the intersection of theoretical research and practical application, working alongside talented engineers and product managers to transform breakthrough ideas into customer-facing experiences. Your work will be crucial in ensuring Alexa remains at the forefront of AI technology while maintaining the highest standards of trust and safety. We're looking for a passionate innovator who combines strong technical expertise with creative problem-solving skills. Your deep understanding of NLP models (including LSTM and transformer-based architectures) will be essential in tackling complex challenges and identifying novel solutions. You'll leverage your exceptional technical knowledge, strong Computer Science fundamentals, and experience with large-scale distributed systems to create reliable, scalable, and high-performance products that delight our customers. Key job responsibilities In this dynamic role, you'll design and implement GenAI solutions that define the future of AI interaction. You'll pioneer novel algorithms, conduct ground breaking experiments, and optimize user experiences through innovative approaches to sensitive content detection and mitigation. Working alongside exceptional engineers and scientists, you'll transform theoretical breakthroughs into practical, scalable solutions that strengthen user trust in Alexa globally. You'll also have the opportunity to mentor rising talent, contributing to Amazon's culture of scientific excellence while helping build high-performing teams that deliver swift, impactful results. A day in the life Imagine starting your day collaborating with brilliant minds on advancing state-of-the-art NLP algorithms, then moving on to analyze experiment results that could reshape how Alexa understands and responds to users. You'll partner with cross-functional teams - from engineers to product managers - to ensure data quality, refine policies, and enhance model performance. Your expertise will guide technical discussions, shape roadmaps, and influence key platform features that require cross-team leadership. About the team The mission of the Alexa Sensitive Content Intelligence (ASCI) team is to (1) minimize negative surprises to customers caused by sensitive content, (2) detect and prevent potential brand-damaging interactions, and (3) build customer trust through appropriate interactions on sensitive topics. The term “sensitive content” includes within its scope a wide range of categories of content such as offensive content (e.g., hate speech, racist speech), profanity, content that is suitable only for certain age groups, politically polarizing content, and religiously polarizing content. The term “content” refers to any material that is exposed to customers by Alexa (including both 1P and 3P experiences) and includes text, speech, audio, and video.
IN, KA, Bengaluru
Alexa+ is Amazon’s next-generation, AI-powered virtual assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalized, and effective experience. As an Applied Scientist II on the Alexa Sensitive Content Intelligence (ASCI) team, you'll be part of an elite group developing industry-leading technologies in attribute extraction and sensitive content detection that work seamlessly across all languages and countries. In this role, you'll join a team of exceptional scientists pushing the boundaries of Natural Language Processing. Working in our dynamic, fast-paced environment, you'll develop novel algorithms and modeling techniques that advance the state of the art in NLP. Your innovations will directly shape how millions of customers interact with Amazon Echo, Echo Dot, Echo Show, and Fire TV devices every day. What makes this role exciting is the unique blend of scientific innovation and real-world impact. You'll be at the intersection of theoretical research and practical application, working alongside talented engineers and product managers to transform breakthrough ideas into customer-facing experiences. Your work will be crucial in ensuring Alexa remains at the forefront of AI technology while maintaining the highest standards of trust and safety. We're looking for a passionate innovator who combines strong technical expertise with creative problem-solving skills. Your deep understanding of NLP models (including LSTM and transformer-based architectures) will be essential in tackling complex challenges and identifying novel solutions. You'll leverage your exceptional technical knowledge, strong Computer Science fundamentals, and experience with large-scale distributed systems to create reliable, scalable, and high-performance products that delight our customers. Key job responsibilities In this dynamic role, you'll design and implement GenAI solutions that define the future of AI interaction. You'll pioneer novel algorithms, conduct ground breaking experiments, and optimize user experiences through innovative approaches to sensitive content detection and mitigation. Working alongside exceptional engineers and scientists, you'll transform theoretical breakthroughs into practical, scalable solutions that strengthen user trust in Alexa globally. You'll also have the opportunity to mentor rising talent, contributing to Amazon's culture of scientific excellence while helping build high-performing teams that deliver swift, impactful results. A day in the life Imagine starting your day collaborating with brilliant minds on advancing state-of-the-art NLP algorithms, then moving on to analyze experiment results that could reshape how Alexa understands and responds to users. You'll partner with cross-functional teams - from engineers to product managers - to ensure data quality, refine policies, and enhance model performance. Your expertise will guide technical discussions, shape roadmaps, and influence key platform features that require cross-team leadership. About the team The mission of the Alexa Sensitive Content Intelligence (ASCI) team is to (1) minimize negative surprises to customers caused by sensitive content, (2) detect and prevent potential brand-damaging interactions, and (3) build customer trust through appropriate interactions on sensitive topics. The term “sensitive content” includes within its scope a wide range of categories of content such as offensive content (e.g., hate speech, racist speech), profanity, content that is suitable only for certain age groups, politically polarizing content, and religiously polarizing content. The term “content” refers to any material that is exposed to customers by Alexa (including both 1P and 3P experiences) and includes text, speech, audio, and video.