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, MA, N.reading
Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. We are seeking a talented Applied Scientist to join our advanced robotics team, focusing on developing and applying cutting-edge simulation methodologies for advanced robotics systems. This role centers on research and development of physics-based simulation techniques, sim-to-real transfer methods, and machine learning approaches that enable rapid development, testing, and validation of robotic systems operating in complex, real-world environments. Key job responsibilities - Advance physics-based simulation fidelity for contact-rich manipulation and locomotion - Design and build high-performance simulation tools integrated into a production robotics stack - Translate research ideas into robust, scalable software pipelines - Develop methods to quantify and reduce simulation-to-reality gaps across design, safety, and control - Architect scalable simulation solutions for rigid and deformable body dynamics - Build simulation pipelines optimized for large-scale reinforcement and policy learning - Establish frameworks for continuous simulation improvement using real-world deployment data - Collaborate with engineering, science, and safety teams on simulation requirements and validation About the team Our team is building a comprehensive simulation platform for advanced robotics development, combining locomotion and manipulation capabilities. We operate at the cutting edge of physics simulation, reinforcement learning, and sim-to-real transfer, collaborating with world-class robotics engineers, applied scientists, and mechanical designers in a fast-paced, innovation-driven environment. This role uniquely combines fundamental research with real-world deployment. You will pursue core research questions in physics-based simulation while seeing your work translated into production systems, validated on real hardware, and informed by deployment data. Working alongside Simulation Software Engineers, you will help transform research ideas into scalable, production-grade simulation capabilities that directly impact how robots are designed, trained, and deployed.
US, WA, Redmond
Amazon Leo is Amazon’s low Earth orbit satellite network. Our mission is to deliver fast, reliable internet connectivity to customers beyond the reach of existing networks. From individual households to schools, hospitals, businesses, and government agencies, Amazon Leo will serve people and organizations operating in locations without reliable connectivity. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. This position is part of the Satellite Attitude Determination and Control team. You will design and analyze the control system and algorithms, support development of our flight hardware and software, help integrate the satellite in our labs, participate in flight operations, and see a constellation of satellites flow through the production line into orbit. Key job responsibilities - Design and analyze algorithms for estimation, flight control, and precise pointing using linear methods and simulation. - Develop and apply models and simulations, with various levels of fidelity, of the satellite and our constellation. - Component level environmental testing, functional and performance checkout, subsystem integration, satellite integration, and in space operations. - Manage the spacecraft constellation as it grows and evolves. - Continuously improve our ability to serve customers by maximizing payload operations time. - Develop autonomy for Fault Detection and Isolation on board the spacecraft. A day in the life This is an opportunity to play a significant role in the design of an entirely new satellite system with challenging performance requirements. The large, integrated constellation brings opportunities for advanced capabilities that need investigation and development. The constellation size also puts emphasis on engineering excellence so our tools and methods, from conceptualization through manufacturing and all phases of test, will be state of the art as will the satellite and supporting infrastructure on the ground. You will find that Amazon Leo's mission is compelling, so our program is staffed with some of the top engineers in the industry. Our daily collaboration with other teams on the program brings constant opportunity for discovery, learning, and growth. About the team Our team has lots of experience with various satellite systems and many other flight vehicles. We have bench strength in both our mission and core GNC disciplines. We design, prototype, test, iterate and learn together. Because GNC is central to safe flight, we tend to drive Concepts of Operation and many system level analyses.
US, NY, New York
Advertising at Amazon is growing incredibly fast and we are responsible for defining and delivering a collection of advertising products that drive discovery and sales. Amazon Business Ads is equally growing fast ($XXXMs to $XBs) and owns engineering and science for the AB WW ad experience. We build business-to-business (“B2B”) specific ad solutions distributed across retail and ad systems for shopper and advertiser experiences. Some include new ad placements or widgets, creatives, sourcing techniques, ad campaign management capabilities and much more! We consider unique AB qualities which are differentiated from the consumer experience such as varying shopper role types, purchasing complexities based on business size and industry (eg education vs healthcare), AB specific features (eg business discounts, buying policies to restrict and prefer products), and AB buyer behaviors (eg buying in bulk). We are seeking a scientific leader who can drive innovation in complex problem areas and new business initiatives. The ideal candidate will: Technical & Research Requirements: * Demonstrate fluency in Python, R, Matlab or other statistical languages and familiarity with deep learning frameworks like PyTorch, TensorFlow * Lead end-to-end solution development from research to prototyping and experimentation * Write and deploy significant parts of scientifically novel software solutions into production Leadership & Influence: * Drive team's scientific agenda by proposing new initiatives and securing management buy-in including PM, SDM * Build consensus on large projects and influence decisions across different teams in Ads Key Leadership Principles: * Dive Deep: Uncover non-obvious insights in data * Deliver Results: Create solutions aligned with customer and product needs * Learn and Be Curious: Demonstrate self-driven desire to explore new research areas * Earn Trust: Build relationships with stakeholders through understanding business needs
US, WA, Seattle
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! As an Applied Scientist in the Prime Video Playback Intelligence Organization, you will have deep subject matter expertise in applied machine learning and data science, with specializations in video streaming optimization, information retrieval, anomaly detection and root-causing systems, large language models and generative AI across various modalities. Key job responsibilities - Work with multiple teams of scientists, engineers, and product managers to translate business and functional requirements into concrete deliverables leading strategic efforts to enhance customer quality of experiences. - Work on problems spaces such as: improving the customer playback quality of experience across Video on Demand, Live Events and Linear Content. - Reduce the time/cost/effort to optimize the customer experience as well as detect, root-cause, and mitigate defects in the customer experience. You’ll seek to understand the depth and nuance of streaming video at scale and identify opportunities to grow our business and improve customer quality of experience via principled ML/AI solutions. - Lead integration of new algorithms and processes into existing modeling stacks, simplify and streamline the existing modeling stacks, and develop testing and evaluation strategies. Ultimately, you'll work backwards from the desired outcomes and lead the way on determining the ideal solution (statistical techniques, traditional ML, GenAI, etc). A day in the life We love solving challenging and hard problems in our quest to innovate on behalf of our customers and provide the best video streaming experience. We push the boundaries to leverage and invent technologies which help create unrivaled experiences for our customers to help us move fast in a growing and changing environment. We use data to guide our decisions, work closely with our engineering and product counterparts, and partner with other Science teams as well as academic institutions to learn and guide in an environment of innovation.
IN, KA, Bengaluru
Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger. In order to drive expansion of the Amazon catalog, we develop advanced ML/AI technologies to process billions of products and algorithmically find products not already sold on Amazon. We work with structured, semi-structured and Visually Rich Documents using deep learning, NLP and image processing. The role demands a high-performing and flexible candidate who can take responsibility for success of the system and drive solutions from research, prototype, design, coding and deployment. We are looking for Applied Scientists to tackle challenging problems in the areas of Information Extraction, Efficient crawling at internet scale, developing ML models for website comprehension and agents to take multi-step decisions. You should have depth and breadth of knowledge in text mining, information extraction from Visually Rich Documents, semi structured data (HTML) and advanced machine learning. You should also have programming and design skills to manipulate Semi-Structured and unstructured data and systems that work at internet scale. You will encounter many challenges, including: - Scale (build models to handle billions of pages), - Accuracy (requirements for precision and recall) - Speed (generate predictions for millions of new or changed pages with low latency) - Diversity (models need to work across different languages, market places and data sources) You will help us to - Build a scalable system which can algorithmically extract information from world wide web. - Intelligently cluster web pages, segment and classify regions, extract relevant information and structure the data available on semi-structured web. - Build systems that will use existing Knowledge Base to perform open information extraction at scale from visually rich documents. Key job responsibilities - Use AI, NLP and advances in LLMs/SLMs and agentic systems to create scalable solutions for business problems. - Efficiently Crawl web, Automate extraction of relevant information from large amounts of Visually Rich Documents and optimize key processes. - Design, develop, evaluate and deploy, innovative and highly scalable ML models, esp. leveraging latest advances in RL-based fine tuning methods like DPO, GRPO etc. - Work closely with software engineering teams to drive real-time model implementations. - Establish scalable, efficient, automated processes for large scale model development, model validation and model maintenance. - Lead projects and mentor other scientists, engineers in the use of ML techniques. - Publish innovation in research forums.
BR, SP, Sao Paulo
Do you like working on projects that are highly visible and are tied closely to Amazon’s growth? Are you seeking an environment where you can drive innovation leveraging the scalability and innovation with Amazon's AWS cloud services? The Amazon International Technology Team is hiring Applied Scientists to work in our Machine Learning team in Mexico City. The Intech team builds International extensions and new features of the Amazon.com web site for individual countries and creates systems to support Amazon operations. We have already worked in Germany, France, UK, India, China, Italy, Brazil and more. Key job responsibilities About you You want to make changes that help millions of customers. You don’t want to make something 10% better as a part of an enormous team. Rather, you want to innovate with a small community of passionate peers. You have experience in analytics, machine learning, LLMs and Agentic AI, and a desire to learn more about these subjects. You want a trusted role in strategy and product design. You put the customer first in your thinking. You have great problem solving skills. You research the latest data technologies and use them to help you innovate and keep costs low. You have great judgment and communication skills, and a history of delivering results. Your Responsibilities - Define and own complex machine learning solutions in the consumer space, including targeting, measurement, creative optimization, and multivariate testing. - Design, implement, and evolve Agentic AI systems that can autonomously perceive their environment, reason about context, and take actions across business workflows—while ensuring human-in-the-loop oversight for high-stakes decisions. - Influence the broader team's approach to integrating machine learning into business workflows. - Advise leadership, both tech and non-tech. - Support technical trade-offs between short-term needs and long-term goals.
US, WA, Bellevue
Alexa International Science team is looking for a passionate, talented, and inventive Senior Applied Scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. At this level, you will drive cross-team scientific strategy, influence partner teams, and deliver solutions that have broad impact across Alexa's international products and services. Key job responsibilities As a Senior Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs, particularly delivering industry-leading scientific research and applied AI for multi-lingual applications — a challenging area for the industry globally. Your work will directly impact our global customers in the form of products and services that support Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in text, speech, and vision domains. The ideal candidate possesses a solid understanding of machine learning, speech and/or natural language processing, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environment, like to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and are able to influence and align multiple teams around a shared scientific vision.
US, NY, New York
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their structural econometrics skillsets to solve real world problems. The intern will work in the area of Amazon Private Brands and develop models to improve our product selection. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The Amazon Private Brands science advance team applies Machine Learning, Statistics and Econometrics/economics to solve high-impact business problems, develop prototypes for Amazon-scale science solutions, and optimize key business functions of Amazon Private Brands and other Amazon orgs. We are an interdisciplinary team, using science and technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon, covering areas such as pricing, discovery, negotiation, forecasting, supply chain and product selection/development.
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 extreme. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.
US, CA, San Francisco
Amazon has launched a new research lab in San Francisco to develop foundational capabilities for useful AI agents. We’re enabling practical AI to make our customers more productive, empowered, and fulfilled. Our work leverages large vision language models (VLMs) with reinforcement learning (RL) and world modeling to solve perception, reasoning, and planning to build useful enterprise agents. Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. Key job responsibilities You will contribute directly to AI agent development in an applied research role to improve the multi-model perception and visual-reasoning abilities of our agent. Daily responsibilities including model training, dataset design, and pre- and post-training optimization. You will be hired as a Member of Technical Staff.