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Eden is an equal partner at Aleph, an early stage venture capital fund with $344 million under management, focused on serving Israeli entrepreneurs who want to build big, scalable, global businesses.

Prior to founding Aleph, Eden was a general partner at Genesis where he focused on seed-stage investments and was a co-founder of face.com, the world leader in massive, web-scale face recognition in social networks, acquired by Facebook. He also co-founded and was the CTO of Aternity, acquired by Riverbed, where he led the strategic product direction for its dominant user-experience monitoring platform.

Entrepreneurship is a passion for Eden, who started The Junction that was voted as the #1 startup program in Israel. He is one of the organizers of the annual Geekcon geeks conference and also teaches at the IDC (Herzliya interdisciplinary center) Zell entrepreneurship program.

Ira is the chief data scientist at Anodot, working on learning algorithms for analyzing time series signals at large scale — from anomaly detection, clustering and forecasting.

Prior to Anodot, Ira was Chief Data Scientist at HP Software, defining and developing machine learning & big data initiatives. Before that Ira was a senior researcher at HP Labs, leading R&D in machine learning and data mining for analyzing large scale event streams.

He is the author of numerous patents and publications and holds a PhD in Electrical and Computer Engineering from the University of Illinois at Urbana Champaign.

Dr. Kira Radinsky is a chairman and CTO of Diagnostic Robotics where the most advanced technologies in the field of artificial intelligence are harnessed to make healthcare better, cheaper, and more widely available. She also co-founded SalesPredict, acquired by eBay in 2016, that was the leader in the field of predictive marketing building solutions leveraging large-scale data mining to predict sales conversions.

One of the up-and-coming voices in the data science community, she is pioneering the field of medical data mining. Dr. Radinsky gained international recognition for her work at Microsoft Research, where she developed predictive algorithms that recognized the early warning signs of globally impactful events, including political riots and disease epidemics. In 2013, she was named to the MIT Technology Review’s 35 Young Innovators Under 35, in 2015 as Forbes 30 under 30 rising stars in enterprise technology, and in 2016 selected as "woman of the year" by Globes.

She is a frequent presenter at global tech events, including TEDx, Wired, Strata Data Science, Techcrunch and academic conferences, and she publishes in the Harvard Business Review.

Radinsky serves is a board member in: Israel Security Authorities, Maccabi Research Institute, and technology board of HSBC bank.

Dr. Radinsky also serves as visiting professor at the Technion, Israel’s leading science and technology institute, where she focuses on the application of predictive data mining in medicine.

Lior Rokach is a data scientist and a Full Professor of Information Systems and Software Engineering. He currently serves as the chair of the Department of Software and Information System Engineering at the Ben-Gurion University of the Negev. His research interests lie in the areas of Data Science, Machine Learning, Big Data, Deep Learning and Data Mining.

Prof. Rokach received a B.Sc. (summa cum laude, 1998), M.Sc. (cum laude, 1999) and PhD (2004) from Tel Aviv University. Since 2005 he has been a faculty member at Ben-Gurion University. In addition, he has had several visiting positions - the most recent at the College of Information Sciences and Technology at the Pennsylvania State University, University Park, PA.

Prof. Rokach is the author of over 300 peer reviewed papers in leading journals, conference proceedings, patents, and book chapters. He has established the machine learning lab and the big data lab which promote innovative adaptations of machine learning and data science methods to create the next generation of intelligent systems.

Dr. Daniel Nevo is a Senior Lecturer at the Department of Statistics and Operations Research at Tel Aviv University since 2018. Dr. Nevo’s research focuses on causal inference in widespread domains, and specifically on developing and implementing causal inference methods for real-life problems.

Dr. Daniel Nevo is a Senior Lecturer at the Department of Statistics and Operations Research at Tel Aviv University since 2018. Before that he was a postdoctoral fellow at Harvard Departments of Biostatistics and Epidemiology (2016-2018). Daniel received his BA (Statistics and Economics, 2009) and MA (Statistics, 2011), both Magna Cum Laude, from the Hebrew University of Jerusalem. He received his PhD in Statistics from the Hebrew University of Jerusalem (2016).

Daniel’s research focuses on causal inference in widespread domains, and specifically on developing and implementing causal inference methods for real-life problems. As of 2022, he published 35 peer-reviewed papers.

Daniel has been collaborating with clinicians, epidemiologists, economists, and computer scientists in academia and health organizations to reach conclusions about causal effects from rich datasets.

Guy Shtar holds a Ph.D in Machine learning as well as an M.Sc. degree in Software and Information Systems Engineering from the Ben-Gurion University of the Negev in 2016.

His research interests include machine learning and deep learning in the medical and cybersecurity fields, as well as geographical information systems.

Inbar has just finished her PhD at the Hebrew University of Jerusalem, her research is focused on image processing and machine learning.

Inbar received her Ms.c in computer science from the Hebrew University and her Bs.c in applied mathematics from Bar-Ilan University, both graduated cum laude. She published several papers in computer vision top-tier conferences.

During her PhD studies, she was titled best teacher assistant.

Karin Brisker is a data scientist at Microsoft, with a background in NLP and machine learning. She began her journey developing AI-driven solutions for the healthcare domain, and now focuses on cybersecurity, building data-driven tools to enhance organizational protection. Karin holds an M.Sc. from the NLP Lab at Bar-Ilan University.

Kosta holds a B.Sc and M.Sc. in Industrial Engineering and Management from Ben Gurion Universirty (Summa Cum Laude both). He won several academic awards and scholarships, and has published multiple research papers in academic journals, including best paper of 2018 in IEEE Transactions on Semiconductor Manufacturing. Kosta is also a Certified Scrum Master and Project Management Professional (PMP).

In his role as Product Analytics Lead at Waze, Kosta uses data to improve every aspect of Waze - one of most popular navigation apps in the world.

Before joining Waze, Kosta worked as a Data Scientist at Intel and as a Lecturer at Ben Gurion University.

Lior has years of experience and works closely with companies to improve their product and operations using data science.

He co-founded Braincast to help product managers to make impactful decisions by explaining causality in meaningful events.

Lior holds BSc and MSc in software and information engineering department from Ben Gurion University, where he researched the appliance of deep learning, embedding, and adversarial learning in the fraud and cybersecurity domains.

Niv Haim is a computer vision and machine learning researcher at the Weizmann Institute of Science, where he earned his PhD under the guidance of Prof. Michal Irani.

Niv's research focuses on developing algorithms and models to analyze and interpret visual data, with a particular interest in understanding memorization in neural networks and the intersection of theory and practice in deep learning. His works were published in top-tier machine learning conferences, including NeurIPS, ICML, ICCV, and ECCV.

Prior to his PhD studies, Niv received an MSc in theoretical astrophysics under the guidance of Prof. Boaz Katz and worked with Prof. Yaron Lipman on Geometric Deep Learning. Niv holds a BSc in computer science and physics from the Technion, where he was a member of the Lapidim excellence program.

Noa is a Data Scientist, currently working as Director of Data Science at Fido. Formerly worked as a researcher at NASA, at Diagnostic Robotics, Amazon, Elbit and IAI. Her main topics of specialisation and focus are NLP, healthcare and space.

Noa is an AI leader, social entrepreneur, lecturer and space enthusiast.

Volunteering as CTO at Tod’aers - combining AI and space research for sustainable technological developments.

Previously worked as Machine Learning Team Lead at Diagnostic Robotics, at Amazon, NASA, Elbit Systems and the Israeli Aerospace Industry.

Computer Science Master's degree, Bar-Ilan University (Magna Cum Laude), NLP thesis advised by Prof. Yoav Goldberg.

Electrical Engineering Bachelor's degree, Technion (Summa Cum Laude).

Dr. Omri Allouche heads the Research department at Gong.io, helping sales organizations improve their performance by providing actionable, data-driven insights using machine learning. He also teaches Applied Data Science at Bar Ilan University.

Omri holds a Ph.D. in Computational Ecology from the Hebrew University (cum laude). He won several academic awards and scholarships, including the Clore fund, and his research papers had been cited over 2,000 times.

Rachel is a statistician in the IBD Epidemiology Research group at Shaare Zedek Hospital. She uses advanced methods in survival analysis and causal inference to gain a deeper knowledge about inflammatory bowel diseases (Crohn's disease and ulcerative colitis).

Rachel holds an MA Cum Laude in Statistics and Operations Research from the Hebrew University. In her thesis, she focused on statistical methodology for estimating hospital-acquired infections.

During her Master’s, she taught multiple courses ranging from basic probability and linear algebra to statistical inference and advanced probability, for which she received an award for outstanding TA.
Rachel has also worked for the Bank of Israel, doing statistical research and benchmarking for consumer goods across the retail industry.

Segev Arbiv is a Data Scientist with expertise in the fields of Machine Learning and Computer Vision. He has a BSc. in Electrical Engineering from the Technion, and pursuing an MSc in these fields.

During the last few years, Segev is working at SimilarWeb in which he applies Deep Learning techniques and various statistical inference tools to overcome day to day challenges, such as NLP and estimations.

Prior to that, he was a researcher in the Image Processing\Computer Vision fields at AOL. Segev is passionate about everything related to numbers, lecturing and interacting with other passionate personas.

Shuki Cohen is a Data Scientist at AI21 Labs, focusing on advanced NLP algorithms to develop writing and reading AI technologies. Prior to that, Shuki worked at SimilarWeb, applying machine learning and statistical algorithms to predict and estimate users behavior. Shuki holds an M.Sc. degree in IE majoring in Data Science from Tel Aviv University.

Yuval is a Developer Advocate at AI21 Labs, deeply involved in advancing the frontiers of Natural Language Processing.

He holds an MSc in Computer Science from the Weizmann Institute of Science, underscoring his firm grounding in the field. Prior to his role at AI21 Labs, he served as a Chip Designer at Amazon, honing his ability to deliver efficient, impactful solutions.

Yuval’s professional passion lies in the realm of generative AI. He actively contributes to making this intricate field more comprehensible and accessible to diverse audiences. With an engaging style and in-depth expertise, he navigates the complexities of AI, bringing clarity and insight to both peers and newcomers in the field.

Tomer is passionate about learning new domains and techniques, from building scalable data pipelines and algorithmic solutions for mapping and automotive apps to data modeling and analysis for financial risk assessment. As a self-learner with multidisciplinary R&D experience, he specialises at tackling hard problems in new domains and working on innovative engineering solutions for products at scale.

Dr. Tomer Gazit is a machine learning and AI researcher, manager, and consultant specializing in the medical domain. He helps organizations develop tailored data science solutions to clinical and operational challenges. He currently leads the Clinical Data Science team at Hello Heart, where he develops predictive models for heart-related diagnoses, integrating tabular data, time series and generative AI.

Previously, he led the Brain Informatics and Imaging Research Lab at Tel Aviv Sourasky Medical Center (Ichilov) where his work focused on time series and neuroimaging tools for neurological diagnosis and translational neuroscience.

Tomer holds a PhD in Neuroscience from Bar-Ilan University and a BSc in Mathematics and Psychology from the Hebrew University of Jerusalem.

Serj Smorodinsky is a data science team lead with deep expertise in NLP, AI evaluation, and agentic workflows. He specializes in building intelligent systems combining Deep learning, LLMs, retrieval architectures, and interpretable rule-based models. Serj brings strong software engineering skills and a production-focused mindset, ensuring scalable, testable, and maintainable AI solutions. His approach bridges experimental research with real-world deployment, emphasizing reliability and continuous evaluation.

Shir Chorev is the co-founder and CTO of Deepchecks, a startup for evaluation and continuous validation of AI-based applications. Previously, Shir worked at the Prime Minister’s Office and at Unit 8200, leading research in various Machine Learning and Cyber related problems. Shir has a B.Sc. in Physics from the Hebrew University, which she obtained as part of the Talpiot excellence program, and an M.Sc. in Electrical Engineering from Tel Aviv University. Shir was a featured honoree in the Forbes Europe 30 Under 30 list.

Dr. Nataly Kuritz is an AI strategist, researcher, and innovation leader with a Ph.D. in Deep Learning for Quantum Chemistry. With over a decade of experience bridging academia and industry, she specializes in building trustworthy AI systems, designing explainable models, and guiding companies through GenAI transformation. Nataly is also a passionate educator and speaker, known for making complex AI concepts accessible and actionable.

Dr. Liat Antwarg Friedman, with a Ph.D. in Information Systems Engineering, specializing in Explainable AI. A proven track record in leading research and applied machine learning projects—spanning fraud detection, NLP, and data quality improvement—I’ve worked with organizations such as eBay, Audi, Leumi and KBC Bank, both as a researcher and consultant. I bring a deep understanding of translating business needs into data-driven solutions.