Lionsolver Inc. Board

Lionsolver team is driven by a passion to “measure what is measurable, and make measurable what is not so,” a passion we share with Galileo and other proponents of pragmatic and falsifiable models of business reality, based on experiments and honest interpretation of the data.

We realize software and services for adaptive analytics, Learning and Intelligent OptimizatioN, marketing optimization, "big data" (a recent keyword covering methods created in a seminal form at least two decades ago). Our competitive edge is caused by a unique integration of machine learning and optimization. The founders and collaborators have more than twenty years of experience and a track of successful real-world applications in wide different areas and ... they keep having fun together.

	Drake Pruitt Chief Executive Officer
Drake has an extensive leadership background with rapid growth, high performance industries and cultures. He began his career on Wall Street, working for Lehman Brothers and later for Montgomery Securities on technology IPOs. In 1994, Drake was part of the founding team of OneComm, Inc, a wireless carrier that built the present-day Nextel, Inc. He also served as VP of Sales for Aquantive Inc, the pioneer in massively scalable online ad delivery, now owned by Mircrosoft. From 2002 through 2008, Drake ran marketing, product development and was promoted to CEO of Bocada, Inc, a leader in data protection analytics and reporting. In 2009, Drake joined Liberty spinoff, Ascent Media as SVP of business development to focus on digital strategy and partnerships. In 2011, Drake founded Genius:Group—a Los Angeles venture studio combining financing and operating expertise to launch, grow and build businesses in technology and digital media. Drake graduated with a BA in Economics and Decision Sciences cum laude from the University of Pennsylvania. He is also a member of the Academy of Television Arts and Sciences and serves as board advisor to several technology startups.
	Roberto Battiti Chief Technology Officer and Head of the Scientific Advisory Board
Roberto is best known for his seminal work on Reactive Search Optimization (RSO), a methodology for integrating machine learning and neural network techniques into stochastic local search heuristics for solving complex optimization problems. His methods have been widely used by industry to solve challenging problems like knapsack, quadratic assignment, graph problems related to clustering and partitioning, vehicle routing and dispatching, power distribution, industrial production and delivery, telecommunications, industrial and architectural design, biology. He is a full professor of Computer Science at Dipartimento di Ingegneria e Scienza dell'Informazione Università di Trento, Italy. He is a Fellow of the IEEE.
	Mauro Brunato Chief Software Architect
Mauro is professor at the Department of Information Engineering and Computer Science of the University of Trento (Italy). He received the Ph.D. in Mathematics at the University of Trento in 1999 with a research thesis on optimization techniques for resource allocation. His main research interests are in heuristics, Reactive Search Optimization, data mining and big data, clustering and interactive visualization. Mauro enjoys creating software architectures combining traditional heavy-duty programming languages with the latest software innovations.

Scientific Advisory Board

	Nathan Brixius Nielsen Marketing Analytics Chicago, USA
Nathan Brixius is Vice President - Optimization at Nielsen Marketing Analytics. Previously he led the Microsoft Solver Foundation group. Nathan received his Ph.D. from the University of Iowa, specializing in distributed computing approaches for large combinatorial optimization models. In 2000, Nate won the University of Iowa prize for outstanding dissertation, and was a CGS/UMI (national) Outstanding Dissertation Finalist. In 2002, Nathan and colleagues were awarded the SIAM Activity Group on Optimization Prize for "Solving Large Quadratic Assignment Problems on Computational Grids".
	Youssef Hamadi Constraint Reasoning Group Microsoft Research Cambridge, UK
Youssef is leading the Constraint Reasoning Group in Microsoft Research Cambridge (MSRC) and co-leading the Adaptive Combinatorial Search for e-Science project in the MSR/INRIA joint-lab, near Paris. Additionally, he is co-leading the Optimisation for Sustainable Development project at Ecole Polytechnique. His research interests include combinatorial optimization in alternative frameworks: Parallel, and Distributed architectures. He is also interested in the application of Machine Learning to Search. My current focus is on Autonomous Search, and Parallel Propositional Satisfiability.
	Holger Hoos Computer Science Department University of British Columbia, Canada
Holger H. Hoos is an Associate Professor at the Computer Science Department of the University of British Columbia (Canada). His main research areas span empirical algorithmics, artificial intelligence, bioinformatics and computer music, and he is one of the world's leading experts on stochastic local search methods and on the automated design of high-performance algorithms. He is a co-author of the book "Stochastic Local Search: Foundations and Applications", and his research has been published in numerous book chapters, journals, and at major conferences in artificial intelligence, operations research, molecular biology and computer music. Holger is a Faculty Associate of the Peter Wall Institute for Advanced Studies and currently serves as President of the Canadian Artificial Intelligence Association (CAIAC). (For further information, see Holger's web page at http://www.cs.ubc.ca/~hoos .)
	Pablo Moscato Centre for Bioinformatics, Biomarker discovery and Information-based medicine University of Newcastle, Australia
Pablo's current research interests are Computational Systems Biology in Health and Disease - Reverse Engineering of biological systems - Applied Computer Science - Application and development of state-of-the-art mathematical models and computer algorithms for the most challenging problems in biology and biotechnology research with emphasis on uncovering the molecular basis of different cellular phenotypes and diseases. He pioneered the field of "memetic algorithms", his work in heuristic optimization has translated into a large number of applications in Computer Science, Operations Research (production planning, management science), Finance and Economics, Civil Engineering, Physics and Chemistry, Bioinformatics.
	Pietro Perona California Institute of Technology (Caltech) Pasadena, CA, USA
Pietro is the Allen E. Puckett Professor of Electrical Engineering and Computation and Neural Systems, and Director of the National Science Foundation Engineering Research Center in Neuromorphic Systems Engineering He directs Computation and Neural Systems (www.cns.caltech.edu), a PhD pogram centered on the study of biological brains and intelligent machines. Professor Perona's research centers on vision. He has contributed to the theory of partial differential equations for image processing and boundary formation, and to modeling the early visual system's function. He is currently interested in visual categories and visual recognition. His research interests are: Computer vision: Recognition, Navigation, Human-Computer interfaces, Texture analysis, Multiresolution image analysis, Diffusions. Human vision: Perception of shape-from-shading, perception of texture. Models of early vision.
	Qingfu Zhang School of Computer Science and Electronic Engineering University of Essex, UK
Qingfu is a Professor of Computer Science in University of Essex. His main research interests include evolutionary computation, optimization, neural networks, data analysis, and their applications. MOEA/D, a multi-objective optimization algorithm developed in his group, won the Unconstrained Multiobjective Optimization Algorithm Competition at the Congress of Evolutionary Computation 2009, and was awarded the 2010 IEEE Transactions on Evolutionary Computation Outstanding Paper Award.