Machine Learning and AI in Life Sciences

Hello Data & AI Enthusiasts,

Machine Learning and AI are rapidly transforming life sciences—from drug discovery to personalized medicine, healthcare delivery and medical imaging.
Because of the breath of the topic we decided to invite three speakers who will give amazing talks and participate in a round table afterwards. As always there will be plenty of time for open discussions on how these technologies are shaping the future of medicine and supporting smarter data-driven decision making in healthcare.
A big thanks to INiTS | Vienna's High-Tech Incubator for their collaboration and support with the location, as well as to EuroCC for providing food and drinks! Together with INiTS, EuroCC Austria (National Competence Centre for Supercomputing, Big Data and Artificial Intelligence) supports researchers and companies in accessing advanced computing know-how and infrastructure for applications in life sciences among other scientific domains.

Machine Learning in Medical Imaging: Science and Clinical Impact
Georg Langs, Professor of Machine Learning in Medical Imaging at Medical University of Vienna

The talk will show examples of how machine learning can deliver decision support in medicine. It will show models that can detect markers of disease, predict disease progression or treatment response, and identify possible future treatment targets. By now ML has entered clinical practice, and I will show examples of this path from research to clinical application.

Georg Langs is Full Professor of Machine Learning in Medical Imaging at the Department of Biomedical Imaging and Image-guided Therapy at the Medical University of Vienna since 2021, having been member of the faculty since 2011. He is head of the Section “Computational Imaging Research Lab (CIR)”, an interdisciplinary research unit with more than 20 researchers from Machine Learning, Radiology, Mathematics, and Computer Science. G. Langs was a Research Scientist at the Computer Science and Artificial Intelligence Lab at MIT (2009 - 2011) where he remains a Research Affiliate (Boston, US), and was a post-doctoral researcher at the Applied Mathematics Laboratory at the Ecole Centrale de Paris (Paris, France). He finished his PhD in Computer Science at the Graz University of Technology in 2007, and his Master of Science in Mathematics at the Vienna University of Technology (2003). Since 2016 he is co-founder and Chief Scientist of contextflow GmbH, a spin-off of the department that is developing deep learning software to support radiologists, with an international staff of currently more than 35. G. Langs research is at the interface of machine learning and biomedical imaging. He has co-authored more than 220 peer reviewed papers cited more than 18.000 times (h-factor=51), and holds 2 granted patents in the area of medical imaging and predictive modelling. Code (co-)developed by CIR has been download more than 10.000 times. He is member of the Scientific Advisory Board of the European Institute of Biomedical Imaging Research, an Associate Faculty at the Complexity Science Hub Vienna, advisor to the IAEA and WHO led Zoonic Disease Integrated Action (ZODIAC), and Co-Coordinator for “Infrastructure and Technology” in the Austrian Platform for Personalized Medicine and has served as Area Chair at the 2021 IEEE Computer Vision and Pattern Recognition Conference.

AI in clinical practice and research: rapid tissue characterization during brain tumor surgery
Georg Wiedalm, Associate Professor, Neurosurgery at Medical University of Vienna

The talk will introduce a novel laser-based technique that is capable to create rapid digital images of tissue features directly in the operating room. By additional use of newly developed AI approaches, specific tumor characteristics can be automatically detected with high accuracy within few minutes during brain tumor surgery. In this talk, this new technique will be explained and novel AI approaches for clinical use and recently developed within research studies will be presented.

Georg Widhalm is Associate Professor at the Department of Neurosurgery at the Medical University of Vienna. He is Head of the Section for Neurosurgical Oncology and Director of the interdisciplinary neurooncological tumor board at the Comprehensive Cancer Center (CCC) at the Medical University of Vienna. Since 2014, he is also the Chair of the Section for Neurosurgical Oncology (ANCO) of the Austrian Neurosurgical Oncology Society (ÖGNC). In 2012, he received the Venia Docendi for Neurosurgery at the Medical University of Vienna. In 2013, he finished his PhD in Clinical Neuroscience. Between 2016 and 2017 he completed a research stay at the Department of Neurosurgery at the University of California, San Francisco. He is leader of multiple research groups at the Medical University Vienna and his research focus is neurosurgical oncology, fluorescence-guided procedures and AI based techniques in neurosurgery. He has co-authored more than 200 peer reviewed papers cited approximately 10.000 times (h-factor=52). Moreover, he is Board member of the Austrian Science Fund (FWF) and serves as advisor for Neuroscience. Furthermore, he is member of the Section for Neurosurgery at the European Organization for Research and Treatment of Cancer (EORTC) and Scientific Committee of the European Association of Neuro-Oncology (EANO).

Tomorrow Trustworthy AI in Healthcare is made today
Yudan Lin, Data Science Associate Director at Takeda

Yudan Lin is the Data Science Associate Director at Takeda, where she leads the company's focus on realizing the promise of Digital Transformation and AI pipeline. She plays a key role in fostering partnerships and building connections within the AI network, as well as with educational institutions and digital communities.
With more than 12 years of experience in Data Science and AI across multiple industries, Yudan possesses expertise in agile program management, innovation management, design thinking, and entrepreneurship. She is also the founder of the Unexpected Data podcast, where she embodies a leadership philosophy centered on motivating individuals through distinct and captivating episodes. Her ambition is to serve as an authentic leader, valuing open and honest feedback, empowering teams, making crisp decisions, and being a role model of the values she advocates.
Through her venture Gini-X, Yudan helps organizations transform privacy regulations into new avenues for data-driven innovations and human-centric disruptors, promoting the concept of Human Business for Human Profit.

! Note that admission is based on an RSVP list. Please make sure that you RSVP and that you have a human-like name set up on [[Meetup.com](http://meetup.com/)](http://meetup.com/) :)

Important: As we will have limited seats available, please be aware that VDSG members will be prioritized!

🎤🎤 Open Mic
We are going to open up the stage after the talks for community announcements. If you'd like to announce something, open this slide deck, make sure you are signed in with a google account, and click "View Only" -> "Request Edit Access". Explain in the text box what you want to announce, and we'll give you edit access to the slide deck.
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Also, please note that during the event, photos might be made and later posted on VDSG's social media page. Please notify us if you do not agree.
Attention attendees with food allergies. Please be aware that the food and drinks provided may contain or come into contact with common allergens, such as dairy, eggs, wheat, soybeans, tree nuts, peanuts, fish, shellfish, or wheat.
Best,
The Organizer Team