ASEF Podcast

In this special live episode of the ASEF Podcast, recorded at Dragon Days in Celje, we hosted Michael Stucky - a partner at Serpentine Ventures, visiting from Zurich, Switzerland, and Jure Vindišar - Head of Technology Transfer at the National Institute of Biology in Slovenia. We delved into the concept of technology transfer, which is all about creating real-world impact from cutting-edge research. This encompasses things like university spin-outs and licensing intellectual property for the purpose of bringing scientific innovations to the market. Tune in to hear inspiring stories of deep-tech entrepreneurship from Slovenia and Switzerland, the importance of innovation clusters, insights from Mario Draghi’s recent report on the EU's competitiveness, and a broader perspective on what it takes to build a thriving technology transfer ecosystem. The conversation was conducted by ASEF Junior Fellow Frenk Dragar. Timestamps: * 00:00:00 - Introduction and welcome of guests Michael Stucky and Jure Vindišar * 00:01:12 - Definition of technology transfer * 00:02:03 - Jure’s experience in tech transfer at the National Institute of Biology and initiatives in Slovenia * 00:06:11 - Michael’s experiences with university spin-outs and tech transfer * 00:09:46 - Comparison of Slovenian and Swiss tech transfer ecosystems * 00:25:19 - Learning from US tech transfer practices, Slovenian delegation on knowledge transfer to the USA * 00:32:00 - Discussion on the Draghi report and its implications for Europe’s innovation strategy * 00:37:10 - Cultural, financial, educational, legislative aspects of KTT * 00:50:00 - Encouragement for aspiring science-preneurs

In this episode, we host Aljaž Bezjak, an accomplished Slovenian digital artist currently working as a digital nomad while based in London. Aljaž studied photography at the Faculty for Applied Sciences in Ljubljana, graduating in 2018 with a project on the digital colorization of black and white photography, inspired by Stojan Kerbler. Before moving to England in 2016, Aljaž worked as a VFX artist and video editor at Studio Ritem in Ljubljana, and as a professional photographer and filmmaker. He later joined Recom Farmhouse, a prominent CGI and creative retouching studio, where he became Creative Project Lead, Senior Creative Retoucher, and CGI artist. In 2023, Aljaž founded his own creative company and now works on various projects while traveling. Join us as we explore his artistic journey and insights into his digital nomad lifestyle.

In this episode, we dive into computational biology, discussing protein structure prediction and the challenges of mapping the sequence-function relationships of proteins. We also touch on cryptic sites in proteins. Our guest, Peter Cimermančič, talks about his startup TesorAI, and we end with a discussion on reverse aging and our control over our biological destiny.   Peter Cimermančič is a co-founder of TesorAI, and has extensive experience in computational and structural biology, genomics, proteomics, target discovery and modulation Timestamps: 0:50 What initially drew you to the field you are currently in, and what continues to motivate you in your research? 2:41 Early career and how would you compare your experience studying in Slovenia vs. abroad?  5:53 How and why did you decide to transition to the industry? 8:39 What prompted you to start your own business instead of staying in academia / staying in the industry(big tech)? 11:14 Protein structure prediction is arguably one of the most successful applications of deep learning in computational biology - can you tell us why is knowing 3D structure of proteins important? 16:05 Why is mapping the sequence-function of a given protein a challenge? 18:37 What kind of data sets (labeled / unlabeled) are used in modeling and what are some advantages/disadvantages of both? 20:56 Talking about Peter’s publication (Cimermancic P, et al., CryptoSite: Expanding the Druggable Proteome by Characterization and Prediction of Cryptic Binding Sites. J Mol Biol. 2016 Feb 22;  https://doi.org/10.1016/j.jmb.2016.01.029 [https://doi.org/10.1016/j.jmb.2016.01.029] )  What defines a cryptic site in proteins, and how does it differ from traditional binding pockets? 23:10 What methods are employed to identify cryptic sites, both experimentally and computationally? 25:54 What impact did the prediction of cryptic sites have on the "druggable" human proteome? 26:42 What is TesorAI, what is the goal of the products and what are the plans for the future? 33:46 About TesorAI products 35:36 where do you get data to train models 36:32 Data in academic computational biology 37:22 What are the emerging trends and future directions in computational biology that are bound to make a significant impact on healthcare in the coming years?  40:21 Challenges in the field 41:35 How do you see the Slovenian startup space fitting in this field? 42:58 As our understanding of the human genome and proteome grows, what are the ethical considerations surrounding genetic engineering, gene editing, and personalized medicine? How do we balance the potential benefits of such technologies with concerns about privacy, equity, and unintended consequences?  46:00 Reverse aging and biological destiny 49:20/50:50 Book recommendations

In this episode, we discuss computer vision, distinguishing it from computer graphics, and delve into the challenges of 3D computer vision. We also examine the current state of autonomous driving research and discuss deepfakes. We host two experts in the field: * Žan Gojčič a senior research scientist at Nvidia, with a research focus is on 3D deep learning, weakly supervised learning, and domain adaptation. * Aljoša Osep a senior research scientist at Nvidia, working on learning to understand the dynamic world from raw and unlabeled streams of sensory data. Timestamps: 1:30: What initially drew you to the field you are currently in, and what continues to motivate you in your research?  6:35: Studying abroad 14:38: Why did you decide to go into industry instead of staying in academia? 20:02: What is computer vision (and the difference between computer vision and computer graphics) and what are some common applications of computer vision in today's world? 24:10: 3D computer vision and What needs to be “synthesized” to create a realistic scene? 27:09: Challenges in the filed 20:31: Current state of research in autonomous driving and challenges  42:50: Deepfakes 49:34: Emerging trends, open problems 56:18: Book recommendations and closing words

In this episode, we dive into another part of the technology transfer and entrepreneurship ecosystem - venture capital (VC) and business angels. We discuss the different VC funds in Slovenia, how startups should approach funding, opportunities and challenges in the local area, as well as success stories in the region, and perspectives abroad. We host three experts from the Slovenian venture capital scene: * Nina Dremelj, Managing Partner at Vesna deep-tech Fund, President of Slovenian Business Angels, and Board Member of the European Business Angels Network * Gregor Rebolj, serial entrepreneur and investor, co-founder of Klika, Sportradar, and 1Home, as well as founding partner of Silicon Gardens * Rok Habinc, partner at Pan-Adria Partners, previously partner at STH Ventures Fund, and active business angel and Board member at Business Angels of Slovenia. Timestamps: * Venture Capital 101: What is VC and how does it support startups? (1:30) * VC landscape in Slovenia: Insights into Slovenian funds and their focus areas. (06:03) * Differences between VC funds: What should startups look for? (18:05) * Accelerators and Incubators: Early entrepreneurial education and wider ecosystem (27:33) * Scaling and foreign capital: How does a local startup scale and seek funding abroad (37:25) * Challenges in Slovenia: policy, legislation, and culture (47:40) * Opportunities and success stories: what the region is good at and achievements (1:03:30) * Global perspectives: Practical examples and best practices to learn from. (1:12:10) * Advice for young founders: Insights on fundraising, mentorship, and determining investment readiness. (1:18:52)