StockFink

StockFink is a Spanish Artificial Intelligence Start-Up with a team of experts in A.I., trading and finance, IT, legal, corporate and international relations, design and digital marketing.

At StockFink, we have developed a methodology based on proprietary AI algorithms to help traders & investors make their own unbiased decisions.

We aim to democratize stock trading through AI.

For this, we have created an advisory product that exhaustively scans stocks across different markets in search of good opportunities. This way, we are able to simultaneously save time, increase confidence, maximize the return and minimize the risk of our clients .

We have a strong expertise in predictive models and uncertainty analysis for risk quantification in decision making, pattern recognition, deep learning and machine learning.

Founders

Lucas Fernández Brillet
He holds a PhD in Mathematics and Computer Science from the University of Grenoble Alpes (2020) through an industrial PhD program (CIFRE) in collaboration between STMicroelectronics and Grenoble INP on the design and implementation of Deep Learning systems for object detection and recognition in embedded systems. He previously obtained a Master's degree in Telecommunications from Bordeaux INP (2016) with a specialization in digital image and signal processing. He is the author of a commercial patent and has published in prestigious international conferences and journals on artificial intelligence, deep learning, computer vision and image processing.

His experience in a highly technological and innovative ecosystem at an international level, has led him to the world of Start-ups, where he has driven a series of potentially disruptive projects in the Artificial Intelligence sector. He is co-founder and CEO of StockFink.
Juan Luis Fernández Martínez
Juan Luis Fernández-Martínez received a PhD degree in mining engineering from the University of Oviedo (Spain, 1994). He previously trained as a petroleum engineer in France (Ècole Nationale du Pètrole et des Moteurs, Paris, 1988) and England (Imperial College, Royal School of Mines, London, 1989). After years of working as a computer software engineer in France, he joined the Department of Mathematics at the University of Oviedo in 1994 and where he has held the position of University Professor in Applied Mathematics since 2018. He is also a professor by the French CNU since 2013. During 2008-2010 he was a research professor at UC Berkeley-Lawrence Berkeley Lab and at Stanford University.

His areas of expertise include inverse problems, uncertainty analysis of complex systems, attribute selection and dimension reduction techniques, cooperative global optimization methods, with diverse applications in fields as varied as energy, oil exploration, biometrics, biomedicine and finance.

In biomedicine, he is interested in simplifying genome complexity for medical diagnosis and drug design in diseases for which there is no cure (www.deepbioinsights.com). In the world of AI, he is interested in the design of expert decision support systems (expert robots). In the world of finance he has been a promoter and co-founder of StockFink, where he is also a Scientific Advisor.

He has published more than 220 articles in international journals and has directed and co-directed more than a dozen doctoral theses and numerous final degree and master's theses on these topics, both nationally and internationally. He holds several US patents on uncertainty analysis in complex and high dimensional systems.

Founders

Lucas Fernández Brillet
At the age of 25, he received a Ph.D. in Mathematics and Computer Science from the University of Grenoble Alpes through an industrial doctoral program (CIFRE) in collaboration between STMicroelectronics and Grenoble INP on the design and implementation of Deep Learning systems for the detection and recognition of objects in embedded systems. His experience in a highly technological and innovative ecosystem at an international level, such as Grenoble, has led him to the world of start-ups, and has allowed him to promote a number of potentially revolutionary projects, including StockFink.

He previously obtained a Master's degree in Telecommunications from Bordeaux INP, specializing in digital image and signal processing.

StockFink was born from an internship carried out in 2015 by himself and directed by Juan Luis Fernández Martínez.
Juan Luis Fernández Martínez
Juan Luis Fernández-Martínez received his PhD degree in mining engineering from the University of Oviedo (Spain, 1994). He previously trained as a petroleum engineer in France (Ècole Nationale du Pètrole et des Moteurs, Paris, 1988) and England (Imperial College, Royal School of Mines, London, 1989). After years of working as a computer software engineer in France, he joined the Department of Mathematics at the University of Oviedo in 1994, where he holds the position of Full Professor in Applied Mathematics since 2018. He is also full-professor at the French CNU since 2013. During 2008-2010 he was a visiting professor and researcher at UC Berkeley-Lawrence Berkeley Laboratories and Stanford University.

His areas of expertise include inverse problems, uncertainty analysis of highly complex systems, feature selection and model reduction techniques, cooperative global optimization methods, with application in oil and gas, biometrics, biomedicine and finance.

In biomedicine, he is interested in the simplification of genome complexity for medical diagnosis and de novo drug design and repositioning in diseases for which there is no cure. In the world of AI, he is interested in the design of expert decision systems (expert robots).

In the world of finance, he has been a promoter and co-founder of StockFink, where he is also Scientific Director.

He has published more than 220 articles in international journals and has directed and co-directed more than a dozen doctoral theses and numerous final degree and master's theses on these topics, both nationally and internationally. He holds several US patents on uncertainty analysis in complex and high dimensional systems.