KingFisher

KingFisher is a team of several graduate and undergraduate students from the University of Illinois, Urbana-Champaign led by faculty advisor Julia Hockenmaier.

The team's interests and experiences include computer vision, goal-oriented dialogue, multimodal learning, robotics and action planning, and real world applications of embodied NLP agents. Their vision for the project is a robot that can both understand and utilize the complexities of human language to interact with users and the environment in meaningful ways.

uofillinois_kingfisher_teamphoto.jpg
Location: Urbana-Champaign, Illinois
Faculty advisor: Julia Hockenmaier

Neeloy C. — Team leader

Neeloy is a second year PhD student in the Human-Centered Autonomy Lab at UIUC studying robotics and artificial intelligence. Some of his research works include applying reinforcement learning (RL) to dense robot crowd navigation, tackling sparse reward RL problems, vehicle anomaly detection, and human-robot interaction tasks in vehicle cockpits. Throughout his higher-level education, he has gained industry experience from companies such as Anheuser-Busch, Qualcomm, Brunswick, and Ford. He has also been a teaching assistant for the Introduction to Robotics class at UIUC, aiding students to learn the fundamentals of robotics in a laboratory setting. Neeloy is excited to apply what he has learned from other problem settings to the embodied AI task, and gain experience in computer vision and natural language processing.

Abhinav A.

Abhinav is a first year Statistics (Concentration: Analytics) Graduate student at UIUC with 5 years of experience at Verizon as a Data Scientist. He completed his undergraduate in Computer Science & Engineering (Concentration: AI) in 2016 from Lovely Professional University, India. He has worked as a DevOps Administrator, Applications Developer, Real Time Streaming Data Engineer along with experience in Data Science. In that space, he has worked on Predictive Modeling, NLP, Anomaly Detection, Sequence Mining, XAI, and CV. He has been a Microsoft Student Ambassador in 2014-2015 and a AI6 city ambassador of Hyderabad, India in 2018.

Blerim A.

Blerim is a 3rd-year undergraduate studying computer engineering at UIUC and a recent transfer from the College of DuPage. His research interests include computer vision and perception with applications in robotics. His main areas of expertise include embedded systems and electronics with applications in robotics and IoT. He has worked as an embedded security intern at Pacific Northwest National Laboratory creating machine learning models for network security within IoT devices. He has also led the development of a mining robot for the NASA Lunabotics Competition which leveraged ROS, Realsense cameras and various other electronics.

Peixin C.

Peixin is an Electrical and Computer Engineering Ph.D. student at UIUC in the area of Robotics and Artificial Intelligence. His research interests are embodied language understanding, robotics, and reinforcement learning. His works involve developing embodied vision-based spoken language understanding agents for robotic systems using reinforcement learning. He also has experience in learning-based robotic navigation in both static and dynamic environments. He is familiar with robotic simulation and has designed and created multiple OpenAI Gym environments based on PyBullet and AI2Thor. He is also familiar with deep learning packages such as TensorFlow and Pytorch.

Haomiao C.

Haomiao is an undergraduate student at UIUC studying statistics, computer science and physics. He is interested in machine learning, robotics, NLP and computer vision. Haomiao has experience working on computer vision projects focusing on 3D structure reconstruction. Haomiao also has experience with implementing, training, and optimizing different machine learning models. Haomiao has some previous experience in NLP, applying semi-supervised learning in language classification. Haomiao is interested in all kinds of NLP models and applications and is willing to learn and explore more through the project.

Runxiang (Sam) C.

Sam is a third year Computer Science PhD student at UIUC. I work on machine learning, currently focusing on multimodal learning. Previously, Sam researched on reliability of distributed systems, specifically on misconfiguration-related failure prevention. Sam obtained a Bachelor of Science in Computer Science from UC Davis in 2019, where he worked on multimodal machine translation, conversational AI, and software data analysis.

Jongwon P.

Jongwon is an undergraduate student at UIUC majoring in Computer Science. Jognwon's interest lies in the intersection of NLU and Multimodal Learning, envisioning weakly supervised models that assimilate the functionalities of the brain. I am passionate about the attention mechanism employed by transformers and their applications outside language tokens. Jognwon's prior experience includes creating a BERT model that simulates the day-and-night continual learning process of the brain for text summarization. Outside the ML research, Jognwon develops websites (fullstack) and deploys ML strategies for quantitative trading in the cryptocurrency space.

Devika P.

Devika is a third-year undergraduate at UIUC majoring in Computer Science. She has previously interned at Motorola Solutions as a Software Engineering Intern working on their predictive analytics team developing machine learning algorithms for mission-critical radio networks. Devika has also interned at Apple on the Siri Product team within their ML organization working on optimizing resources for best performance using data analytics and ML models. Previously, her research interests have included packet-scheduling in high criticality networks and theoretical topology

Nikil R.

Nikil is an undergraduate studying Mathematics and Computer Science at UIUC. His research interests are primarily in natural language processing and computer vision. He has experience working on multiple NLP sub-areas such as topic modeling, semantic similarity, keyphrase extraction and generation, and text embeddings. He also has experience training,
testing, optimizing and deploying deep learning models (involving computer vision and time series forecasting) using the power of high performance computing, with applications to diverse domains including astrophysics, spectroscopy and cancer research. In addition, he has some familiarity with AWS, having used it in projects involving NLP and machine learning.

Risham S.

Risham is a Computer Science PhD student at UIUC in the area of Artificial Intelligence. Her current interests are grounding and multimodal networks and she is working on a similar goal-oriented dialogue task on a Commander model on the Minecraft Dialogue Corpus. She also has experience working on a range of NLP projects including evaluating the faithfulness of grounded representations and their training dynamics within VQA, information extraction from scientific papers, annotating, creating, and updating datasets, and text classification and generation.

Kulbir S.

Kulbir is currently pursuing a PhD at UIUC where he works to integrate the Alexa API with Agricultural robots to enable remote voice control of CNC based gardening robots. Kulbir's interest in Robotics was fostered during undergraduate studies in Electrical Engineering. During Kulbir's masters in robotics at the University of Maryland, he built a solid theoretical foundation in computer science and robotics, by taking core robotics courses focussing on Planning and Perception for Autonomous Systems, ROS and Decision Making.

Julia Hockenmaier — Faculty advisor

Julia Hockenmaier is a full professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. Her main area of research is computational linguistics or natural language processing.

Latest news

The latest updates, stories, and more about Alexa Prize.
US, NY, New York
We are seeking a Robotics/AI Motor Control Scientist to develop cutting-edge machine learning algorithms for motor control systems in robots. In this role, you will focus on creating and optimizing intelligent motor control strategies to enable robots to perform complex, whole-body tasks. Your contributions will be essential in advancing robotics by enabling fluid, reliable, and safe interactions between robots and their environments. Key job responsibilities - Develop controllers that leverage reinforcement learning, imitation learning, or other advanced AI techniques to achieve natural, robust, and adaptive motor behaviors - Collaborate with multi-disciplinary teams to integrate motor control systems with robotic hardware, ensuring alignment with real-world constraints such as actuator dynamics and energy efficiency - Use simulation and real-world testing to refine and validate control algorithms - Stay updated on advancements in robotics, AI, and control systems to apply advanced techniques to robotic motion challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you. an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.
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 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.
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.
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.
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.
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.
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 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.
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.
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.
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 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.