Madrid-genuine2.jpeg
Location: Madrid, Spain
Faculty advisor: Luis Fernando D'Haro

Genuine2

The first Spanish team in the history of the Alexa Challenge!

We're Genuine2, the first Spanish team in the history of the Alexa Challenge! Our team came up together while creating our innovation startup lab, ever since then, our passion for the research and implementation of cutting edge ideas and technologies into mainstream products can be felt in all the skills, algorithms, chatbots, and conversation-assistants that we've brought to life and have had an impact over 60+ countries with dozens of thousands of amazed users. We give extra care to the user experience and the clear personality that all our creations ooze. This the beginning of Genuine2, your new homie ;-)

Natalia R. - Team leader

Coming soon!

Alicia G.

Alicia is a telecommunication Engineer with a major in Telematics with International Intensification certification from Universidad de Cantabria in Spain. She worked with Università degli Studi di Padova (Italy) in the Department of Information Engineering completing the bachelor thesis. Currently, she is studying the Double Master Degree in Telecommunications - Signal Processing and Machine Learning for Big Data at Universidad Politécnica de Madrid. Working in her thesis related to audio and text analysis for content-based recommender systems. One of the few fortunate selected to participate in the "Liderazgo Tech" for women in STEM, sponsored by Banco Santander. Mentor for UPM International Students.

Diego B.

Diego is currently in the process of finishing his Bachelor Thesis in the NLP field. He's been working around the world during the past years as a software engineer, researcher assistant and lead developer. Having a paper published on the SBST@ICSE 2019 and a year on research experience within the ZHAW in Switzerland. Now he's a core developer of the LEXIS' client Portal (EU Granted) with focus in the accounting integration of the High Computing Centers within the Cloud Ecosystem, architect of the latest iteration of the accounting and billing solution from Cyclops Labs and technical advisor in Saturno Labs.

Ramón M.

Valencia. His bachelor thesis was focused on real-time streaming system processing in reproducible environments via Docker. He has a Double Master in Telecommunications major in Machine Learning for Big Data from Universidad Politécnica de Madrid in Spain. In his role as Project Manager at Saturno Labs he's lead the development of chatbots, client defined commercial applications as well as computer vision, machine learning and artificial intelligence solutions. Also, he is a technology enthusiast, who has won some competitions around the world about tecnology and coding.

Diego D.

Diego is a telecommunications engineer with major in Telematics, currently seeking a Masters in Signal Processing and Machine Learning for Big Data at Universidad Politécnica de Madrid. He has worked as a researcher in the Life Supporting Technologies group at ETSIT-UPM. His Bachelor Thesis was developed within the ’Plan4Act’ European project whose aim is to record and understand predictive neural activity and use it to proactively control devices in a smart home. He's been highly involved in the organization of local and international events within the European Student's Associations BEST and EESTEC.

Mario R. C.

Mario is a first-year PhD student in Automation and Robotics in Intelligent Control Group at Centre for Automatic and Robotics (CAR UPM-CSIC). He is advised by Prof. Fernando Matía and Prof. Luis Fernando D'Haro. His research interests are NLP and Dialogue Management, focused on emotions and personality in conversations. He also worked on the integration of software and components for a first prototype of human-robot conversational interaction.

Marcos E. G.

Marcos is a first-year PhD student in the Speech Technology Group (GTH-UPM) advised by Prof. Luis Fernando D'Haro. His current research area of interest is related to open domain knowledge-grounded dialogue systems. Before joining as a PhD student, Marcos spent two years pursing a master's degree in Telecommunication Engineering with major in Machine Learning and Multimedia Data Science at UPM and conducting research with Prof. Ricardo De Córdoba on language recognition.

Luis Fernando D'haro - Faculty advisor

Luis Fernando D’Haro is Associate Professor at Universidad Politécnica de Madrid in Spain and a member of the Speech Technology Group (GTH-ETSIT). His current research for dialogue systems mainly focuses on generative approaches and automatic evaluation metrics; He co-led the International Dialog State Tracking Challenges (DSTC) in 2015 and 2016 and member of the organizing committee from the DSTC6 to DSTC9 editions. He has been PC and organizer member for the Workshop on Spoken Dialog System Technology (IWSDS) in 2018 and general chair in 2020, and senior member for the Chanel workshop at the Johns Hopkins Summer school (JSALT2020).

Latest news

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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.