whats-up-bot.jpg
Location: Edinburgh, Scotland, UK
Faculty advisor: Oliver Lemon

What's Up Bot

Our international team of 6 PhD students and faculty advisors has a wide range of experience from both academic and industrial research.

Our team is based in the Interaction Lab at Heriot-Watt University in Edinburgh, which has a long history of building data-driven dialogue systems using machine learning methods. Our vision is to create a humorous and engaging socialbot that keeps users engaged and enjoying conversation on topics of their choice. Our inspiration is the kind of conversation that two new acquaintances might have in a pub -- a mixture of topic-related chat, finding out about each other, and sharing stories.

Ioannis P. - Team leader

During my professional career as a presales engineer, I was engaged in numerous large-scale interdisciplinary projects, where I had to carefully design the technical implementation, weeding out any problems along the way. As a software developer, I was part of large groups as well as working alone, with a wide variety of programming languages and technologies. Both of these positions allowed me to develop invaluable skills like leadership, teamwork, communication and time management. In 2016 I received my MSc degree in Artificial Intelligence with distinction, and am currently working to further my knowledge in HRI during my PhD.

Amanda C.C.

Amanda is a first-year PhD student working on automatic evaluation of NLG systems. She holds a Bachelor's in Computer Science with first class honours from Heriot-Watt University. Her dissertation project focused on generating context-dependent navigation instructions and won first prize at the BSCWomen Lovelace Poster Competition. Following graduation, she worked as a research assistant at the Interaction Lab, working on how best to communicate uncertainty in weather reports. In her free time, Amanda enjoys travelling, reading and home brewing.

Igor S.

I'm a PhD student interested in deep learning for dialogue systems. I hold an Engineer degree (MSc equivalent) with distinction in Computer Science from Moscow State University of Instrument Engineering and Computer Science and Yandex School for Data Analysis. Prior to HWU, I worked as a software engineer at Yandex on projects in computational linguistics such as Russian National Corpus and conversational user interfaces platform. I interned at Microsoft Research (distributed systems research for Bing) and Intel (optimizing C++ compiler). In 2016, I was awarded the James Watt Scholarship for postgraduate study from HWU.

Jose P.

I hold an Electronics Engineering degree from the National University of Rosario in Argentina and a European Master's in Vision and Robotics jointly awarded by three European Universities. Currently, I am pursuing a PhD as part of the Centre for Doctoral Training in Robotics and Autonomous Systems at the Edinburgh Centre for Robotics. My research topic involves the development of a cognitive architecture that would enable robots to learn about their environment and how to perform tasks interactively with a tutor through situated dialogue and physical demonstration. My research interests span artificial intelligence, natural language understanding and robotics.

Xinnuo X.

I got my bachelor's degree in Computer Science in 2012 from Capital University of Economics and Business, Beijing, China. After that, I worked in the Nature Language Processing department of Baidu Inc. for four years before I came to Edinburgh to pursue my MSc and PhD degrees. During the last two year of my Baidu career, I was involved in Baidu voice assistant program, a task based dialogue system; Baidu voice map program, a task based dialogue system preferred to navigation and localisation, and Baidu Duer, a chat based dialogue system.

Yanchao Y.

I'm studying for a PhD degree focusing on Semantic Language grounding using Multimodal Interaction. It aims at building a teachable system that can learn users' word meanings through dialogue. It lies in several fields, including the incremental and attribute-based object recognition, an incremental dialogue management with a word-level adaptive dialogue policy, as well as dynamically semantic grounding. Before my PhD studies, I was awarded a Master's degree with distinction in Software Engineering, and worked on several task-oriented spoken dialogue system projects, including Parlance and SpeechCity. The SpeechCity project won a civic challenge organised by the City of Edinburgh Council in 2014.

Oliver Lemon - Faculty advisor

The faculty advisory team consists of Oliver Lemon and Verena Rieser. Oliver and Verena are both Professors at Heriot-Watt University, Edinburgh, and lead the Interaction Lab and NLP Lab respectively. Their research focuses on machine learning approaches to spoken and multimodal interaction, and socially intelligent Human-Robot Interaction.

Oliver was previously a research fellow at Stanford and Edinburgh Universities, and holds a PhD from Edinburgh. He has led several national and international research projects.

Verena has gained her PhD in 2008 from Saarland University and spent her postdoctoral years at the University of Edinburgh, before she joined Heriot-Watt in 2011. She currently leads a group of 7 full-time researchers (4 PostDocs, 3 PhDs), mainly funded by the EPSRC.

Latest news

The latest updates, stories, and more about Alexa Prize.
  • Behnam Hedayatnia
    March 5, 2019
    The 2018 Alexa Prize featured eight student teams from four countries, each of which adopted distinctive approaches to some of the central technical questions in conversational AI. We survey those approaches in a paper we released late last year, and the teams themselves go into even greater detail in the papers they submitted to the latest Alexa Prize Proceedings. Here, we touch on just a few of the teams’ innovations.
  • Anushree Venkatesh
    February 27, 2019
    To ensure that Alexa Prize contestants can concentrate on dialogue systems — the core technology of socialbots — Amazon scientists and engineers built a set of machine learning modules that handle fundamental conversational tasks and a development environment that lets contestants easily mix and match existing modules with those of their own design.
RO, Iasi
Are you a MS or PhD student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models and speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, Spain, South Africa, UAE, and UK). Please note these are not remote internships.
EE, Tallinn
Are you a MS or PhD student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, Spain, South Africa, UAE, and UK). Please note these are not remote internships.
GB, London
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IL, Tel Aviv
Are you a MS or PhD student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, South Africa, Spain, Sweden, UAE, and UK). Please note these are not remote internships.
GB, London
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US, WA, Seattle
Passionate about books? The Amazon Books personalization team is looking for a talented Applied Scientist II to help develop and implement innovative science solutions to make it easier for millions of customers to find the next book they will love. In this role you will: - Collaborate within a dynamic team of scientists, economists, engineers, analysts, and business partners. - Utilize Amazon's large-scale computing and data resources to analyze customer behavior and product relationships. - Contribute to building and maintaining recommendation models, and assist in running A/B tests on the retail website. - Help develop and implement solutions to improve Amazon's recommendation systems. Key job responsibilities The role involves working with recommender systems that combine Natural Language Processing (NLP), Reinforcement Learning (RL), graph networks, and deep learning to help customers discover their next great read. You will assist in developing recommendation model pipelines, analyze deep learning-based recommendation models, and collaborate with engineering and product teams to improve customer-facing recommendations. As part of the team, you will learn and contribute across these technical areas while developing your skills in the recommendation systems space. A day in the life In your day-to-day role, you will contribute to the development and maintenance of recommendation models, support the implementation of A/B test experiments, and work alongside engineers, product teams, and other scientists to help deploy machine learning solutions to production. You will gain hands-on experience with our recommendation systems while working under the guidance of senior scientists. About the team We are Books Personalization a collaborative group of 5-7 scientists, 2 product leaders, and 2 engineering teams that aims to help find the right next read for customers through high quality personalized book recommendation experiences. Books Personalization is a part of the Books Content Demand organization, which focuses on surfacing the best books for customers wherever they are in their current book journey.
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
CA, ON, Toronto
Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique opportunity to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. As a Principal Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work at scale. This position requires experience with developing Computer Vision, Multi-modal LLMs and/or Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms. Key job responsibilities - You will be responsible for defining key research directions in Multimodal LLMs and Computer Vision, adopting or inventing new techniques, conducting rigorous experiments, publishing results, 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. - You will also participate in organizational planning, hiring, mentorship and leadership development. - You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).
DE, BE, Berlin
Are you interested in enhancing Alexa user experiences through Large Language Models? The Alexa AI Berlin team is looking for an Applied Scientist to join our innovative team working on Large Language Models (LLMs), Natural Language Processing, and Machine/Deep Learning. You will be at the center of Alexa's LLM transformation, collaborating with a diverse team of applied and research scientists to enhance existing features and explore new possibilities with LLMs. In this role, you'll work cross-functionally with science, product, and engineering leaders to shape the future of Alexa. Key job responsibilities As an Applied Scientist in Alexa Science team: - You will develop core LLM technologies including supervised fine tuning and prompt optimization to enable innovative Alexa use cases - You will research and design novel metrics and evaluation methods to measure and improve AI performance - You will create automated, multi-step processes using AI agents and LLMs to solve complex problems - You will communicate effectively with leadership and collaborate with colleagues from science, engineering, and business backgrounds - You will participate in on-call rotations to support our systems and ensure continuous service availability A day in the life As an Applied Scientist, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create technical roadmaps and drive production level projects that will support Amazon Science. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. About the team You would be part of the Alexa Science Team where you would be collaborating with Fellow Applied and research scientists!
US, WA, Redmond
Project Kuiper is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to unserved and under-served communities around the world. We are looking for an accomplished Applied Scientist who will deliver science applications such as anomaly detection, advanced calibration methods, space engineering simulations, and performance analytics -- to name a few. Key job responsibilities • Translate ambiguous problems into well defined mathematical problems • Prototype, test, and implement state-of-the-art algorithms for antenna pointing calibration, anomaly detection, predictive failure models, and ground terminal performance evaluation • Provide actionable recommendations for system design/definition by defining, running, and summarizing physically-accurate simulations of ground terminal functionality • Collaborate closely with engineers to deploy performant, scalable, and maintainable applications in the cloud 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. A day in the life In this role as an Applied Scientist, you will design, implement, optimize, and operate systems critical to the uptime and performance of Kuiper ground terminals. Your contributions will have a direct impact on customers around the world. About the team This role will be part of the Ground Software & Analytics team, part of Ground Systems Engineering. Our team is responsible for: • Design, development, deployment, and support of a Tier-1 Monitoring and Remediation System (MARS) needed to maintain high availability of hundreds of ground terminals deployed around the world • Ground systems integration/test (I&T) automation • Ground terminal configuration, provisioning, and acceptance automation • Systems analysis • Algorithm development (pointing/tracking/calibration/monitoring) • Software interface definition for supplier-provided hardware and development of software test automation