GHOST Day: Applied Machine Learning Conference

About Conference

Experience GHOST Day yet again in 2022!

Last year’s overwhelmingly positive feedback surprised us all, and we’re happy to be bringing increasingly more machine learning experts and fans together!

We are more than happy to officially announce, that the Conference date is 24-26 March 2022. During these three days, the wisest minds from the field will deliver wonderful and inspiring lectures. Attending GHOST Day keeps you up to date with the newest advancements in many fields of Machine Learning, ranging from Cybersecurity AI to Deep Learning NLP. We are successively revealing this edition's speakers, so be sure to check them below!

There is still a lot to do in the AI domain, and many fields seek breakthroughs. We think that you are likely to make one! If you agree with us, we highly encourage you to respond to our Call for Speakers down below and share your projects with the AI community.

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Conference Date

24-26 March 2022

Our Speakers

Who’s speaking

Tomas Mikolov

Senior Researcher | Czech Institute of Informatics, Robotics and Cybernetics

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.

Piotr Mirowski

Staff Research Scientist | DeepMind

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.

David Touretzky

Research Professor | Carnegie Mellon University

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.

Monika Podsiadło

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

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.

Elif Eyigoz

Researcher | IBM

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.

Ishan Misra

Research Scientist | Facebook AI Research

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.

Participate

Call For Contributions

Join "GHOST Day: AMLC" community and help us with making this event even more fascinating with your own contribution! Presenting your project or giving a talk on "GHOST Day: AMLC" is a great opportunity to show your work to experts from both industry and academia. It's a chance to discuss with them your ideas, to get constructive feedback and to make useful connections! One of our goals is to create an event with an affordable entrance where everyone interested in machine learning is welcome. However, this is not possible without the generous support of our sponsors!

Speakers

We are looking for captivating talks from machine learning practitioners. If you are interested in giving a talk:

Let us know!

GHOST Day

Applied Machine Learning Conference