Speakers

TBA

by Tomas Mikolov | Senior Researcher | Czech Institute of Informatics, Robotics and Cybernetics

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Biography:
Tomáš Mikolov, PhD is a Senior Researcher at the Czech Institute of Informatics, Robotics and Cybernetics in Prague. Before that, he conducted research at John Hopkins University, University of Montreal, and the Brno University of Technology from which he obtained PhD in 2012 for RNN-based language models. Later that year he joined Google Brain where he worked on neural networks applied to natural language processing problems such as representation learning (the word2vec project), neural language modeling and machine translation. During his work at Facebook AI Research, he co-authored fastText – library for text classification and representation learning. In 2020 he moved to Prague, to form a new research group at Czech Technical University focused on evolving mathematical models - the foundation of general AI.

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by Piotr Mirowski | Staff Research Scientist | DeepMind

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Piotr Mirowski is a Staff Research Scientist at DeepMind. He is mainly interested in reinforcement navigation-related research, in scaling up autonomous agents to real-world environments and in weather and climate modeling, but has also investigated the use of AI for artistic human and machine-based co-creation. After studying computer science in France, he obtained his Ph.D. at NYU (Outstanding Dissertation Award) under the supervision of Prof. Yann LeCun. He worked at Schlumberger Research, at the NYU Comprehensive Epilepsy Center, at Bell Labs, and Microsoft Bing on topics like epileptic seizure prediction from EEG, the inference of gene regulation networks, information retrieval and search query autocompletion, WiFi-based geolocalisation, and robotic navigation.

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by David Touretzky | Research Professor | Carnegie Mellon University

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David S. Touretzky is a Research Professor in the Computer Science Department and Neuroscience Institute at Carnegie Mellon University. He received his PhD in Computer Science from Carnegie Mellon in 1984. Dr. Touretzky's research interests include Cognitive Robotics, Computational Neuroscience, and Computer Science Education. He is founder and chair of the AI4K12 Initiative (AI4K12.org), which is developing national guidelines for teaching Artificial Intelligence in K-12. He is also the creator of Calypso, an inteligent robot programming framework that puts real artificial intelligence technology into the hands of children.

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by Monika Podsiadło | Head of Applied Research: Text-To-Speech | Google NYC

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Monika Podsiadło leads Text to Speech Applied Research at Google New York with over 10 years of experience in the field. Her work is centered around managing a team focused on prosody, few-shot learning, and cross-lingual modeling. Before that, together with her team, she launched over 200 TTS voices in 30 languages, productionized WaveNet, and expanded Google Assistant. In 2007 Monika graduated from The University of Edinburgh, defending her master's thesis on Speech and Language Processing. After hours she mentors at BUILD, helping 9th graders to launch a start-up.

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by Ishan Misra | Research Scientist | Facebook AI Research

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Ishan Misra finished his Ph.D. at the Robotics Institute at Carnegie Mellon University in 2018. He has since then been working as a Research Scientist at Facebook AI Research (FAIR). His main research interests are Computer Vision and Unsupervised Learning, having published multiple research papers on Self-Supervised Learning and Visual Representation, together with prominent researchers like Yann LeCun and Martial Hebert. Ishan's works have won multiple awards such as the best paper award at WACV 2014 and best paper nomination at CVPR 2021. Ishan was also a guest on the Lex Fridman Podcast and ML Street Talk.

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by Elif Eyigoz | Researcher | IBM Watson

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Elif Eyigoz, PhD works as a Research Staff Member at IBM Watson NY. She is a member of the Healthcare and Lifesciences research group. Elif has an exceptional multi-disciplinary background in Philosophy (BA), Cognitive Science (MA), Linguistics (MA), and Computer Science (MS and PhD). She joined IBM in 2014. In 2020 she co-authored a study on linguistic markers of Alzheimer’s disease where machine learning is used to detect early signs of progression of the illness.

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by Dumitru Erhan | Staff Research Scientist & TLM | Google Brain

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Dumitru Erhan is a Staff Research Scientist and Tech Lead Manager in the Google Brain team in San Francisco. He received a PhD from University of Montreal (MILA) in 2011 with Yoshua Bengio, where he worked on understanding deep networks. Afterwards, he has done research at the intersection of computer vision and deep learning, notably object detection (SSD), object recognition (GoogLeNet), image captioning (Show & Tell), visual question-answering, unsupervised domain adaptation (PixelDA), active perception and others. Recent work has focused on video prediction and generation, as well as its applicability to model-based reinforcement learning. He aims to build and understand agents that can learn as much as possible to self-supervised interaction with the environment, with applications to the fields of robotics and self-driving cars. Dumitru divides his free time between family, cooking and cycling through the Bay Area!

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by Mateusz Fedoryszak | Data Scientist | Twitter

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Mateusz is an ML Engineer at Twitter. He works on understanding what people are tweeting about: currently by the topic classification, earlier by the automated event detection. Before that he was analysing terabytes of scientific papers, looking for word boundaries in scriptio continua and leveraged data to guess how much milk a cow would produce. Big fan of logistic regression, kNN and pretty charts. Formerly at ICM University of Warsaw, Microsoft and True Knowledge (now Amazon).

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by Vu Nguyen | Machine Learning Scientist | Amazon Adelaide, Australia

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Dr Vu Nguyen is a Machine Learning Scientist at Amazon Research Australia. His research interest includes Bayesian optimisation for optimal decision making under uncertainty. Prior to this appointment, he was a Senior Research Associate in machine learning at University of Oxford working with Prof. Michael Osborne and Prof. Andrew Briggs. Other prior roles include Research Scientist at a research start-up CreditAI and an Associate Research Fellow at Deakin University. Dr Nguyen obtained his PhD at Deakin University in 2015, where he was fortunate to have Professors Dinh Phung and Svetha Venkatesh as his advisors.

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by Marta Stępniewska-Dziubińska | Software Engineer | NVIDIA

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Marta is a Software Engineer at NVIDIA, working on deep learning models for computer vision and drug discovery. She started working with ML during her PhD, for which she built deep neural networks for structure-based drug discovery. Afterwards she decided to turn to industry and used her skill-set for computer vision problems. She was involved in projects aimed at digitizing industry installation documentation, analyzing 3D point clouds and distance maps, and extracting useful information from surveillance videos. Now she is getting back to her roots, working again on deep learning models for rational drug discovery.

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by Jev Gamper | Staff Decision Scientist | Experimentation & Causal Inference | Vinted

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Jev Gamper is a Staff Decision Scientist at Vinted. His role involves leadership across all aspects of experimentation and causal inference, from implementing scientific models underlying the experimentation system to setting up technical roadmap and establishing experimentation culture. Jev did his Msc in Applied Mathematics at Warwick Univeristy, and is a PhD Candidate at Warwick University. His research invovled applications of statistical and machine learning methods to medical imaging, astronomy, remote sensing, and climate modeling. Jev's research articles have been published at venues like CVPR, and Monthly Notices of the Royal Astronomical Society. He is a board member of Lithuanian AI Association and a co-organiser of Eastern European Machine Learning Summer School in 2022, in Vilnius.

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by Karol Żak | Senior Data & Applied Scientist | Microsoft

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Karol Żak is a self-taught Data & Applied Scientist with a strong Software Engineering background. For the last 5 years he worked in Commercial Software Engineering group at Microsoft where he collaborated with some of the biggest organizations worldwide to build ML/DS solutions for their most pressing business problems. His main area of interest is computer vision but throughout the years he worked in a full spectrum of different ML areas.

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by Huma Lodhi | Lead Machine Learning Engineer | Sky UK

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Huma Lodhi, Ph.D. works as a Lead Machine Learning Engineer in Sky UK- Europe's leading media and entertainment company. She is interested in developing machine learning based products and delivering advanced analytics value for complex business problems. She is fascinated by the role that Artificial Intelligence can play in the transformation of industry. Prior to joining Sky UK, she held positions in industries ranging from insurance to health care. After her PhD she has done scientific research with many UK universities for many years. Her research focus has been the development and application of statistical and statistical relational Machine Learning methodologies. Her most cited research work is text classification using string kernels.

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by Stanisław Jastrzębski | Chief Scientific Officer | Molecule one

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Stanisław Jastrzębski serves as a Chief Scientific Officer at Molecule one, where he is helping develop AI for organic chemistry. Prior to that, he was an Assistant Professor at Jagiellonian University (as part of GMUM.net), and a postdoc at New York University. He completed his PhD at Jagiellonian University, advised by Jacek Tabor and Amos Storkey from the University of Edinburgh. His thesis was focused on fundamental aspects of deep learning and was largely based on work done in collaboration with Yoshua Bengio at MILA. He is actively contributing to the machine learning community as an area chair for leading conferences (NeurIPS, ICLR, ICML). His long-term interest is to develop AI and deep learning for discovering novel scientific knowledge.

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by Ioannis Partalas | Principal Machine Learning Scientist | Expedia Group

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Ioannis Partalas works as Principal Machine Learning Scientist at Expedia Group. His current focus is learning representation in the context of recommendation and ranking systems. Previously he worked as a Research Scientist in Viseo Group, France, on Natural Language Processing building scalable approaches for various tasks such as text classification, named-entity recognition and opinion mining. Before that he was an associate researcher in Grenoble-Alpes University working on large-scale/extreme classification systems.

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by Smriti Mishra | Head of AI | Earthbanc

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Smriti Mishra is a Head of Artificial Intelligence at Earthbanc where she implements techniques for remote sensing for verification of carbon sequestration. Hers Bachelor's Thesis was in realm of Computational Neuroscience. It was a study about overlapping sequences in the brain, how thoughts are processed and why people lose memory. Smriti is a Founding Member of AI Guild, which is the go-to community for data and business professionals advancing AI adoption. She is also “Google Women Techmakers” Ambassador in Sweden.

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by Wenwu Wang | Signal Processing & ML Professor | University of Surrey

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Wenwu Wang is a Professor in Signal Processing and Machine Learning, and a CoDirector of the Machine Audition Lab within the Centre for Vision Speech and Signal Processing. His current research interests include signal processing, machine learning and perception, with a focus on audio/speech and multimodal (e.g. audio-visual) data. He has (co)-authored over 250 papers in these areas. He is a (co-)recipient of over 15 awards including the Best Paper Award on ICAUS 2021, Judge's Award on DCASE 2020, the Reproducible System Award on DCASE 2019 and 2020, Best Student Paper Award on LVA/ICA 2018, the Best Oral Presentation on FSDM 2016, Best Student Paper Award finalists on ICASSP 2019 and LVA/ICA 2010, the TVB Europe Award for Best Achievement in Sound in 2016, the Best Solution Award on the Dstl Challenge in 2012, and the 1st place in 2020 DCASE challenge on "Urban Sound Tagging with Spatio-Temporal Context", and the 1st place in the 2017 DCASE Challenge on "Large-scale Weakly Supervised Sound Event Detection for Smart Cars". He is a Senior Area Editor (2019-) for IEEE Transactions on Signal Processing, an Associate Editor (2020-) for IEEE/ACM Transactions on Audio Speech and Language Processing, and an Associate Editor (2019-) for EURASIP Journal on Audio Speech and Music Processing. He is a Specialty Editor in Chief (2021-) of Frontier in Signal Processing, and was an Associate Editor (2014-2018) for IEEE Transactions on Signal Processing. He is elected to Vice Chair (2022-) of IEEE Machine Learning for Signal Processing Technical Committee, a Member (2021-) of the IEEE Signal Processing Theory and Methods Technical Committee, and a Member (2019-) of the International Steering Committee of Latent Variable Analysis and Signal Separation. He was a Publication Co-Chair for ICASSP 2019, Brighton, UK. He is a Satellite Workshop Co-Chair for INTERSPEECH 2022, Incheon, Korea.

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by Victoria Chudinow | Senior Data Scientist | Dixa

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Victoria Chudinov holds a master's degree in Psychology and psychopathology of development from Varna Free University "Chernorizets Hrabar" in Bulgaria. Her degree in cognitive development focused on working memory. In 2015 she received Master of Science in Informational Technologies at the IT University of Copenhagen. During these studies she focused on Modern Artificial Intelligence, Artificial Life, Data Mining and Machine Learning. Currently her work at Dixa is centered around creating machine learning libraries and building NLP models for text generation, completion, classification, etc. She is the winner of the Nordic DAIR Awards 2021 in the Individual Category Machine Learning Professional of the Year.

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by Gianluca Micchi | Machine Learning Researcher | IRIS Audio Technologies

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Gianluca Micchi has a double education: a diploma in music (piano) and a PhD in theoretical physics (on nano-electromechanical systems); so he decided to become a computer scientist. As a machine learning researcher, he has worked both in academia (postdoc at the University of Lille) and in private companies (Skylads, TikTok, and now IRIS audio technologies). His main area of interest nowadays is AI applied to music and audio. He was part of the team that secured fourth place at the first edition of the AI Song contest.

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by Rachel Wities | NLP Researcher | Zebra Medical Vision, Israel

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Rachel Wities is an NLP Researcher, focused on the Healthcare domain. In her previous roles she was an NLP Data Scientist in Zebra Medical and a Research Scientist in PayPal. Rachel is a public speaker addressing Healthcare NLP challenges, and believes that understanding doctors and their needs is the key to successfully implementing AI Healthcare algorithms. Rachel holds an M.Sc. from BIU NLP lab, researching knowledge graph representation of text semantics, and a B.Sc in Physics and Cognitive Science from Hebrew University in Jerusalem. Loves her family, God and Oxford Comma jokes.

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by Aleksander Molak | Innovation Lead / ML Researcher | Lingaro

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Aleksander Molak is an Innovation Lead and Machine Learning Researcher at Data Science and Artificial Intelligence Center of Excellence at Lingaro. Building end-to-end machine learning systems for global companies. He's the author of #SundayAiPapers - a weekly LinkedIn microblog presenting the most recent papers on natural language processing, causal inference and probabilistic modeling. Aleksander loves traveling with together with his wife. Passionate about vegan food, languages and running.

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by Luciano Paz | Principal Data Scientist | PyMC-Labs

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Luciano Paz is a Principal Data Scientist at PyMC-Labs. He studied physics and then transitioned into neuroscience, where his research involved computational techniques such as reinforcement learning, planning, stochastic dynamics and probabilistic programming. He is a core developer of PyMC, a probabilistic programming language in Python. His work in PyMC-Labs is to help companies power their business using bayesian statistics. The projects he has worked on range from marketing studies, such as A/B tests and Media Mix Models, to complex behavioral models.

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by Marcin Mosiolek | AI Architect | SII Poland

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Marcin is an AI Architect with over ten years of experience in a wide range of commercial machine learning projects, mainly related to natural language processing and computer vision. He converts the latest academic research into operating products in his daily job rather than Jupyter Notebooks only. After working hours, Marcin enjoys strong winds and rough seas while kitesurfing.

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by Hubert Ruczyński | Bachelor of Science Student | Warsaw Univeristy of Technology

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I'm on 6th semester of Data Science studies on Faculty of Mathematics and Information Science in Warsaw University of Technology (MiNI PW). Last summer I've been a part of FairPAN project during MI2 DataLab Internship and this talk is an effect of that studies. The aforementioned internship was my first scientific and work experience and I'm really grateful for that possibility.

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