People

Matthew Michalewicz, Chief Executive Officer

Matthew has more than 20 years of experience in starting and running high-growth tech companies, especially in the areas of predictive analytics and optimisation. He is currently the CEO of Complexica, a provider of Artificial Intelligence software for optimising sales & marketing activities, and a director of several ASX-listed companies, including Prophecy International (ASX: PRO), ComOps (ASX: COM), and LBT Innovations (ASX: LBT). He is also the author of several books, including Life in Half a Second, Winning Credibility, Puzzle-Based Learning, and Adaptive Business Intelligence. 

From 2005 – 2012, Matthew was the co-founder and CEO of SolveIT Software, a supply chain optimisation business he grew from zero to almost 180 employees and $20 million in revenue before selling the business to Schneider Electric. Under his leadership, SolveIT Software became the 3rd fastest-growing company in Australia in 2012, as ranked by Deloitte. The company won numerous awards, and counted among its customers some of the largest corporations in the world, including Rio Tinto, BHP Billiton, and Xstrata.

From 1999 - 2003, Matthew was the co-founder and CEO of NuTech Solutions in the USA, where he raised more than US$15 million in venture capital and grew the business to almost 200 employees in six international offices. Matthew established an “A-list” board of directors, which included former President of Poland and Nobel Peace Prize winner, Lech Walesa, former Bank of America Chairman and CEO, Hugh McColl Jr., world-renowned fraud expert and subject of Steven Spielberg's blockbuster "Catch Me if You Can," Frank Abagnale, and former National Security Advisor to the President of the United States, Zbigniew Brzezinski. NuTech Solutions was acquired by Netezza Corporation, which was subsequently acquired by IBM Global Services.

From 1994 – 1999, Matthew was the founder and operator of Fitness Forever, a personal training business, and later, the co-founder of CFG Investments, a money management and financial planning company with more than $150 million under management.

Matthew is also a Limited Partner in Blackbird Ventures, an Australian early-stage venture capital fund, and from 2005 - 2016 he held the position of Visiting Fellow at the University of Adelaide where he lectured on the subject of technology commercialisation for graduate students.

Matthew’s business achievements have been featured in numerous television shows and publications, including Time Magazine, Newsweek, and Forbes. He was named the Pearcey Foundation "Entrepreneur of the Year", Business Journal "40 under 40" list of accomplished business leaders, and Ernst and Young "Entrepreneur of the Year" finalist.

Matthew holds a Bachelor of Science degree in Corporate Finance from the University of North Carolina in Charlotte, where he was later named "Alumnus of Year."

Constantin Chiriac, M.Sc., Chief Software Architect

Constantin is an expert in the design and development of commercial software systems with more than 15 years of experience developing enterprise software applications based on the latest advances in Artificial Intelligence. These applications were used by numerous Global 1000 companies to create measurable improvements in revenue and bottom-line profits.

In 2005, Constantin co-founded SolveIT Software, an Australian software company specialising in supply chain optimisation. Constantin was a member of the Board of Directors of SolveIT Software and its Chief Software Architect. The company grew from 0 to more than 150 employees from 2005 to 2012 before being sold to Schneider Electric in August 2012. SolveIT Software became the 3rd fastest-growing company in Australia in 2012, as ranked by Deloitte.

Dr. Zbigniew "Mike" Michalewicz, Ph.D., Chief Scientist

Internationally renowned Artificial Intelligence expert, Zbigniew Michalewicz has published over 300 articles and 25 books on the subject of predictive analytics, optimisation, and self-learning systems, which have been cited by other 10,000 authors. These include the ground breaking Adaptive Business Intelligence and How to Solve It: Modern Heuristics. Zbigniew is the Chief Scientist at Complexica and Emeritus Professor at the University of Adelaide (where he held the position of Chair of Artificial Intelligence).

Zbigniew has over 35 years of academic and industry experience, and possesses expert knowledge of numerous Artificial Intelligence technologies. He was the co-founder and Chief Scientist of NuTech Solutions, (which was acquired by Netezza, and subsequently by IBM), and the co-founder and Chief Scientist of SolveIT Software (which was acquired by Schneider Electric after becoming the 3rd fastest growing company in Australia). Both companies grew to approximately 200 employees before being acquired.

During his time in the corporate world, Zbigniew led numerous large-scale predictive analytics and optimization projects for major corporations, including Ford Motor Company, BHP Billiton, U.S. Department of Defence, and Bank of America. Zbigniew Michalewicz also served as the Chairman of the Technical Committee on Evolutionary Computation, and later as the Executive Vice President of IEEE Neural Network Council.

Zbigniew Michalewicz received this Ph.D. degree in Computer Science from the Polish Academy of Science; and his Doctor of Science (Habilitation) degree in Computer Science from the Polish Academy of Science. His research interests include Artificial Intelligence, data mining, predictive modelling, optimisation, logistics, big-data analytics, genetic algorithms, neural networks, fuzzy logic, and optimization.

In December 2013, the President of Poland, Mr. Bronislaw Komorowski, awarded Zbigniew the Order of the Rebirth of Polish Polonia Restituta, which is the second highest Polish state award for a civilian (after the Order of the White Eagle ), awarded for outstanding achievements in the field of education, science, sports, culture, arts, economy, national defense, social activities, the civil service and the development of good relations with other countries.

Doug Misener, Corporate Strategy Advisor

An innovative and strategic thinker with more than 30 years experience in the liquor industry, Doug is Complexica's strategic advisor on product development and go-to-market strategy in the fast-moving-consumer-goods (FMCG) sector.

Before joining Complexica, Doug was the CEO of Liquor Marketing Group, which is one of Australia’s leading alcohol marketing groups with more than 1,400 retail outlets that turnover in excess of $1 billion annually. During his tenure at LMG from 2005 – 2016, Doug transformed the business by divesting its wholesaling division, overhauling its systems & processes, and achieving a debt-free position. His initiatives led to improved relationships with key suppliers, more effective marketing programs, and greater service levels to the retail outlets. 

Prior to LMG, Doug spent almost 15 years with Lion Nathan in a variety of roles, initially in Pepsi Cola Australia (Lion owned), and subsequently in the domestic beer business where Doug led the entire Australian National Sales function. He finished his tenure with Lion as Managing Director of Lion International with direct responsibility for markets in the USA, Canada, the UK, Italy and Japan.

Mike Costa, Director, Customer Engagement

Mike Costa is a business leader with over 25 years of IT experience in project and program management, operational management and customer service excellence.
 
Mike’s varied experience spans a range of industry sectors including defence, utilities, telecommunications, manufacturing, oil and gas. Mike has always maintained a strong focus on delivering projects on-time and in an effective manner. Further, he has a strong operational background and has managed the delivery of mission critical applications for external customers.

Prior to joining Complexica, Mike held senior roles at IBM, Schneider Electric, and RACV in Victoria. He also holds a Bachelor of Arts from Monash University and a Graduate Diploma in Applied Information Systems from RMIT University.

Kalyan Avvaru, M.Sc., Chief Technology Officer

Kalyan Avvaru is the Chief Technology Officer at Complexica, and has over a decade of experience in building and supporting high traffic, high volume transactional systems. Kalyan works closely with Complexica customers and internal technical teams to deliver product management, planning, solution scoping, software development and infrastructure management. Prior to Complexica, Kalyan worked in various across a variety of domains - including compliance management, human resources, and logistics - delivering B2B SaaS-based applications. In previous roles Kalyan worked with major companies across Australia in the construction and health care industries doing  pre-sales and technical consulting, advising technical teams on large scale application integration. He also has specialized knowledge and experience in full-stack application performance engineering to scale applications for large user bases.

Kalyan moved to Adelaide, Australia in 2004 from India to do his Masters in Computer & Information Science from the University of South Australia, and prior to that, he received an Engineering Bachelors degree in Computer Science. He currently lives in Adelaide with his wife Min.

Murad Mekhtiev, Manager, Business and Data Analysis

Aditya Khaire, M.Sc., Business & Data Analyst

Larisa Stamova, M.B.A., Marketing Manager

Larisa is a marketing professional with a passion for digital marketing, in particular PPC, social media, and search engine optimisation. She holds a Masters degree in Business Administration/Marketing from the University of Adelaide. Prior to joining Complexica, Larisa was the Marketing Manager at SolveIT Software, an Australian company specialising in supply chain optimisation. The company grew from zero to almost 180 employees during the period 2005 - 2012, before being acquired by Schneider Electric. Due to Larisa's leadership in marketing, the company won numerous awards, including the National iAward for e-Logistics and Supply Chain Management and the Australian Business Awards for Product Excellence, and added some of the largest corporations in the world as customers, including Rio Tinto, BHP Billiton, and Xstrata.

Xiang Li, M.Sc., Machine Learning Scientist

Dr. Riky Tan, Ph.D. , Technical Project Manager/Product Owner

Dr. Riky Tan has more than 10 years of experience in software development, architecture, and technical design. Prior to joining Complexica, Riky was a software team lead for Schneider Electric, where he led large scale software implementation projects for global companies such as BHP Billiton, Roy Hill, and Treasury Wine Estates.

From 2005 to 2011, Riky was a lecturer at the University of Ballarat and the International Institute of Business Information & Technology in Adelaide, delivering IT courses specialising in programming, software engineering, and database management. Before this, he held various positions as IT Manager and System Analyst for various Universities around South East Asia.

Riky holds a Ph.D. degree in Information Technology & Computing from the University of South Australia, along with a Masters of Computer Science and a Bachelor of Computer Science. Riky has carried out research and developed software in the areas of Artificial Intelligence, data mining, and information visualisation and retrieval.

Lukasz Olech, M.Sc., Machine Learning Scientist

Jon Lee, B.Sc., Technical Project Manager/Product Owner

Dr. Ali Shemshadi, Ph.D., Machine Learning Scientist

Ali Shemshadi received his Ph.D. from the University of Adelaide, where he worked on the practical applications of searching and analysing big data from emerging paradigms such as the Internet of Things. During his academic career, Ali published more than 20 scientific papers in leading journals, conference proceedings, and book chapters, spanning a variety of fields such as Internet of Things, Supply Chain Management, Analytical Decision Making, and Machine Learning. He has also served on various conference committees and international journals in roles ranging from Committee Member and Reviewer, through to Program Chair. His teaching roles also include Associate Lecturer and Course Coordinator for a number of advanced courses at the University of Adelaide. 

Prior to joining Complexica, Ali specialised in developing complex analytical/machine learning software for multi-national organisations. In particular, he successfully deliver a number of software projects in various industry sectors, including manufacturing, financial services, education, transport, and media, which are still in production use today. Furthermore, throughout his academic and business career, many of his projects have been recognised with national and international awards for innovation.

Luiza Michalewicz, M.B.A., Manager, Customer Experience

Luiza has a background in marketing and consumer psychology, and holds a Masters degree in Business Administration from the University of Adelaide. Prior to joining Complexica, Luiza was a Customer Experience Analyst at SolveIT Software, an software provider of supply chain optimisation software. As the company grew from zero to almost 180 employees during the period 2005 - 2012, Luiza's team engaged with largest corporations in the world, including Rio Tinto, BHP Billiton, and Xstrata.

Prior to SolveIT Software, Luiza worked in the United States in various marketing and customer experience roles, most notably at NuTech Solutions and Excavio Systems, which were later acquired by Netezza and IBM global services.

Hugh Lam, Customer Experience Analyst

Hugh is a designer motivated by creating delightful user interfaces and ensuring they meet exceed customer expectations. At Complexica, he gathers customer experience data to analyse user feedback, determine satisfaction, interpret results to senior management, and develop solutions to customer service challenges.

Prior to joining Complexica he was the Technical Writing Lead for Schneider Electric, where he developed end-user training materials for the mining industry. The exposure from working directly with customers using the product formalised his interests in devising better user experiences and implementing solutions.

Hugh holds a Bachelor of Information Technology from Flinders University and has strong interests in mechanical design. He spends his spare time in his own workshop where he restores and rebuilds cars.

Polish-Japanese Academy
of Information Technology, Research Partner

The Polish-Japanese Academy of Information Technology was set up in 1994 between the governments of Poland and Japan. Today, the Academy is a leading institute in Poland, taking the 2^nd position in the Wprost ranking list of the best non-state schools in 2014, and 5^th position among all academic institutions (state and non-state). The main campus of the Polish-Japanese Academy of Information Technology is located in Warsaw, Poland.

Complexica cooperates with the Polish-Japanese Academy of Information Technology on social informatics – in particular, on issues related to the relationships that occur between society and information systems. The changes in social structures are examined that are under the influence of modern information technology, especially in the context of systems such as GitHub or Wikipedia. Also, research issues include investigations on how social mechanisms can improve the quality of information systems, such as reputational systems within an e-commerce context. The interdisciplinary team within the Polish-Japanese Academy of Information Technology has considerable expertise in social network analysis, natural language processing, social simulations, and machine learning.

RMIT University, Research Partner

Based in Melbourne, Australia, RMIT University was founded in 1887 and today has an enrollment of over 80,000 students across vocational, undergraduate and postgraduate levels.

Complexica cooperates with the Evolutionary Computing and Machine Learning (ECML) group at RMIT on nature-inspired computational models and algorithms, especially in the areas of evolutionary computation and machine learning. The research takes an inter-disciplinary approach drawing on inspirations from mathematical programming, meta-heuristics, and operations research. Some current research topics include reinforcement learning, deep learning, multi-objective optimization, data mining and analytics, computer vision, time series analysis, evolutionary art, journey planning, and swarm intelligence.

University of Adelaide, Research Partner

The University of Adelaide was established in 1874 and it is the third oldest university in Australia. It is consistently ranked in the top 1% of universities worldwide.

Complexica cooperates with the School of Computer Science at the University of Adelaide on research topics related to data mining and analytics. These include research on various heuristic methods – how these methods work and how they are able to deal with different types of data problems. The research aims to build up a theory of heuristic methods including evolutionary algorithms and ant colony optimisation that helps to develop new effective approaches based on theoretical insights. Also, problems in the area of social choice are investigated to develop new approaches for dealing with game-theory problems. Other research topics relate to Platforms for People as a Service (PeaaS), evolving critical systems, and cyber security and privacy.

Institute of Data and Analytics, Research Partner

Founded by a group of ex-University of Technology Sydney (UTS) Ph.D.s, the International Institute of Data and Analytics aims to bridge the gap between academia and business and to build a platform for interactions and collaborations between outstanding researchers, practitioners, and educators.

Complexica cooperates with the Institute in the areas of data science, big data analytics technology, algorithms and models for cracking challenges in complex data and behaviors. The research topics include community analysis, sentiment understanding, behavior analytics, social analytics, and online analytics in evolving data with complex networking behaviors and relationships in a mixed, interconnected and/or changing environment.

Dr. Kenneth De Jong, Ph.D., Scientific Advisor

Kenneth De Jong received his Ph.D. degree in computer science from the University of Michigan in 1975. He joined George Mason University in 1984 and is currently a Professor of Computer Science, head of the Evolutionary Computation Laboratory, and Interim Director of the Krasnov Institute.

Kenneth’s research interests include genetic algorithms, evolutionary computation, machine learning, and adaptive systems. He is currently involved in research projects involving the development of new evolutionary algorithm (EA) theory, the use of EAs as heuristics for NP-hard problems, and the application of EAs to the problem of learning task programs in domains such as robot navigation and game playing. He is an active member of the Evolutionary Computation research community, including the founding Editor-in-Chief of the journal Evolutionary Computation (MIT Press), and a member of the board of ACM SIGEVO. He is also the recipient of an IEEE Pioneer Award in the field of Evolutionary Computation and the Lifetime Achievement Award from the Evolutionary Programming Society.

Dr. Frank Neumann, Ph.D., Scientific Advisor

Frank Neumann received his Ph.D. degree from the Christian-Albrechts-University of Kiel in 2006. Currently, he is an Associate Professor at the University of Adelaide and the leader of the Optimisation and Logistics Group within the School of Computer Science. Frank organised the ACM FOGA 2013 in Adelaide with Kenneth De Jong, and co-authored the textbook Bioinspired Computation in Combinatorial Optimization - Algorithms and Their Computational Complexity (Springer) with Carsten Witt.

Frank is an Associate Editor of the Journal of Evolutionary Computation (MIT Press) and Vice-Chair of IEEE Task Force on Theoretical Foundations of Bio-inspired Computation. In his work, he considers algorithmic approaches for combinatorial and multi-objective optimization problems and focuses on the theoretical aspects of evolutionary computation, as well as applications in the areas of renewable energy, logistics, and sports.

Dr. Xiaodong Li, Ph.D., Scientific Advisor

Xiaodong Li received his Ph.D. degree in information science from the University of Otago in New Zealand, and is currently an Associate Professor at the School of Computer Science and Information Technology at RMIT University. His research interests include evolutionary computation, machine learning, complex systems, multi-objective optimization, and swarm intelligence, and he serves as an Associate Editor of the IEEE Transactions on Evolutionary Computation, the journal of Swarm Intelligence, and International Journal of Swarm Intelligence Research.

Dr. Kalyanmoy Deb, Ph.D., Scientific Advisor

Kalyanmoy Deb holds the Endowed Chair in the Department of Electrical and Computing Engineering at Michigan State University. Prior to this position, he held the positions of Endowed Chair in the Department of Mechanical Engineering at the Indian Institute of Technology in India.

Kalyanmoy established the Kanpur Genetic Algorithms Laboratory at the Indian Institute of Technology in 1997 and the Computational Optimization and Innovation (COIN) Laboratory at Michigan State University in 2013. He is the author of Multi-Objective Optimization using Evolutionary Algorithms, published by Wiley as part of its series on "Systems and Optimization". In an analysis of authors in the field of evolutionary computation, Kalyanmoy was identified as one of the most central authors in the community and designated as a "sociometric superstar" of the field. Kalyanmoy has several honors to his credit, which include the:

• Shanti Swarup Bhatnagar Award in engineering sciences;
• Thomson Citation Laureate Award for highly cited research in computer science; and
• MCDM Edgeworth-Pareto Award for creativity in the field

Kalyanmoy’s interests lie in the development and application of multi-criterion optimization methods for solving problems in the area of design, modeling, process control, scheduling, resource allocation and machine learning, as well as large-scale and non-linear problems for which customized optimization methods are most suitable.

Dr. Raymond Chiong, Ph.D., Scientific Advisor

Raymond Chiong received his Ph.D. degree from the University of Melbourne in Australia, and has taught a variety of computer science and information systems courses at Swinburne University of Technology before joining the University of Newcastle in early 2013. Besides teaching, he conducts research related to evolutionary game theory, optimisation, data analytics, and modelling of complex adaptive systems.

Raymond was the Editor-in-Chief of the Interdisciplinary Journal of Information, Knowledge, and Management from 2011 to 2014, and is currently an Editor for the Journal Engineering Applications of Artificial Intelligence and an Associate Editor for the IEEE Computational Intelligence Magazine. He has also served as Guest Editor for a number of reputable international journals, such as the International Journal of Production Economics and the European Journal of Operational Research. He is a Senior Member of IEEE, and one of the Founding Co-Chairs of the IEEE Symposium on Computational Intelligence in Production and Logistics Systems. To date, he has produced/co-authored over 100 refereed publications in the form of books, book chapters, journal articles and conference papers.

Dr. Adam Wierzbicki, Ph.D., Scientific Advisor

Adam Wierzbicki received his Ph.D. degree from the Warsaw University of Technology and a habilitation title from the Institute of Systems Research of the Polish Academy of Sciences. He is currently a Professor and Vice-President at the Polish-Japanese Institute for Information Technology in Poland.

Adam is an expert in big data, data mining, and machine learning, and has considerable experience in simulation and multi-agent systems. His current research interests focus on social informatics, in particular on credibility, trust management, collective intelligence and fairness in distributed systems. He has published several papers on trust management and on applications of the theory of equity to provide fairness in open distributed systems, and is the author of a Springer book titled Trust and Fairness in Open, Distributed Systems. He is also interested in open collaboration, particularly using Wiki technology, and in Crowdsourcing, with an emphasis on new algorithms for evaluating and managing Crowdsourcing workers. In 2011-2015 Adam headed the Reconcile Project, which developed tools for the evaluation of Web content credibility.

Dr. Reza Bonyadi, Ph.D., Scientific Advisor

Reza Bonyadi received his Ph.D. in computer science from the University of Adelaide, where he focused on the theoretical aspects of continuous space optimization algorithms such as stability, convergence, and transformation invariance. During his academic career he published more than 35 articles in top international journals, conferences, and chapter of books in the field of optimization, pattern recognition, and machine learning. He has been involved as a committee member in many international journals and conferences in the field of optimization and machine learning.

Apart from his academic activities, Reza has significant experience in designing software solutions for complex analytical/machine learning problems for large organisations. His expertise lies in designing decision support systems, stochastic simulators, pattern recognition and data clustering algorithms, and trend prediction/learning methods for complex real-world problems.

Dr. Thomas Weise, Ph.D., Scientific Advisor

Thomas Weise received his Ph.D. degree from the University of Kassel and a Diplom-Informatiker from the Chemnitz' University of Technology in Germany. He joined the University of Science and Technology of China (USTC) in 2009 and became Associate Professor in 2011. In 2016, he became Full Professor at Hefei University (HFUU). He is the director of the Institute of Applied Optimization.

Thomas has made significant contributions to the fields of optimization, logistic planning, and Evolutionary Computation, and has authored/co-authored more than 90 publications. He is also the developer of an open source optimization and machine learning benchmarking tool, which mines performance information from large data sets to support researchers and practitioners in developing efficient computational intelligence solutions.

Dr. Markus Wagner, Ph.D., Scientific Advisor

Markus Wagner received his Ph.D. degree from the University of Adelaide, and is an active researcher at their Optimisation and Logistics Group. His research interests include heuristic optimisation and software engineering, and he is the recipient of the:

• University Doctoral Research Medal for his work on Theory and Applications of Bio-Inspired Algorithms; and
• Best Paper Award for his work on Evolving Pacing Strategies for Team Pursuit Track Cycling.

Markus has been awarded grants from the Australian Research Council (ARC) and Google Australia, and he is the Founding Chair of the IEEE CIS Task Force on "Computational Intelligence in the Energy Domain" and Chair of IEEE CIS Education Subcommittees. To date, he has co-authored over 50 refereed publications in the form of book chapters, journal articles, and conference papers.

Dr. Masoud Mohammadian, Ph.D., Scientific Advisor

Masoud Mohammadian received his Ph.D. degree from the University of Central Queensland, before joining the University of Canberra in 1998. Besides teaching various undergraduate and graduate courses, his research interests include neural networks, fuzzy logic, evolutionary computing, optimisation, data analytics, and modelling of complex adaptive systems, as well as the application of computational intelligence techniques for learning and adaptation of intelligent agents, and web-based information filtering and data mining. Masoud has successfully completed many industry projects related to real-time data processing, planning, and decision-making.

Masoud has edited over 20 books and conference proceedings in the area of Computational Intelligence and Intelligent Agents, and authored more than 130 peer-reviewed publications in the form of books, book chapters, journal articles and conference papers. He has also chaired and co-chaired over 14 international conferences in the area of Computational Intelligence and Intelligent Agents.

Dr. Mengjie Zhang, Ph.D., Scientific Advisor

Mengjie Zhang received his Ph.D. degree from RMIT University, and since 2000, has been teaching a wide range of computer science courses at Victoria University of Wellington in New Zealand. He conducts research related to evolutionary computation, particularly genetic programming and evolutionary computer vision, evolutionary feature selection and big dimensionality reduction and evolutionary scheduling and combinatorial optimisation, as well as data mining and machine learning. He is currently an Associate Editor or an Editorial Board Member for seven international journals, including:

• IEEE Transactions on Evolutionary Computation;
• Evolutionary Computation Journal (MIT Press); and
• Genetic Programming and Evolvable Machines.

Mengjie is also a:

• Senior Member of IEEE;
• Chair of IEEE CIS Evolutionary Computation Technical Committee;
• Vice-Chair of IEEE CIS Task Force on Evolutionary Computer Vision and Image Processing;
• Member of the IEEE Task Force on Evolutionary Feature Selection and Construction;
• Member of the IEEE CIS Intelligent System Applications Technical Committee; and
• Founding Chair of IEEE Chapter on Computational Intelligence in New Zealand.

To date, Mengjie has produced/co-authored over 350 refereed publications in the form of book chapters, journal articles and conference papers.

Dr. Zbigniew Raś, Ph.D., Scientific Advisor

Zbigniew Ras received his Ph.D. degree from the University of Warsaw in Poland, and his D.Sc. degree from the Institute of Computer Science at the Polish Academy of Sciences. He was also awarded the National Professorship title by the President of Poland, and is currently a Professor of computer science at the University of North Carolina in Charlotte.

Zbigniew’s areas of specialization include knowledge discovery, recommendation systems, health informatics, active knowledge mining, music information retrieval, flexible query answering, and sentiment analysis, and he currently serves as the:

• Editor-in-Chief of the Journal of Intelligent Information Systems (Springer);
• Editor-in Chief of the International Journal of Social Network Mining (IJSNM);
• Senior Editor of International Journal of Data Mining, Modelling and Management (InderScience Publishers); and
• Member of Editorial Board of Fundamenta Informaticae Journal (IOS Press).

Zbigniew is the author of more than 300 publications and the editor of more than 40 books published by Springer and North Holland. He has received many awards including the Harshini V. de Silva Graduate Mentor Award, the COIT Graduate Faculty Excellence in Teaching Award, and the Alcoa Foundation Outstanding Faculty Award. Zbigniew has also received numerous competitive grants and industry contracts, and has graduated 15 PhD students.

Dr. A.E. Eiben, Ph.D., Scientific Advisor

A.E. Eiben received his Ph.D. degree from the Eindhoven University of Technology in the Netherlands. He is one of Europe’s “early birds” of Evolutionary Computing, with his first paper dating back to 1989. Since then, he’s became one of Europe’s leading Evolutionary Computing researchers, actively pursuing research related to evolutionary operators, constraint handling, parameter calibration, and most recently evolutionary robotics.

A.E. Eiben has published over 200 research papers, and co-authored the first comprehensive book on evolutionary computing (Introduction to Evolutionary Computing published by Springer). He has been an organizing committee member of practically all major international evolutionary conferences (CEC, EP, EuroGP, EvoStar, FOGA, GECCO, PPSN), and is the specialty Chief Editor of Evolutionary Robotics for Frontiers Journal on Robotics and Artificial Intelligence. His other appointments include:

• Editorial Board Member of five international journals (including JEC, IEEE TEC, GPEH);
• Series Editor for Springer’s book series on Natural Computing;
• Steering Committee Member for the Parallel Problem Solving from Nature (PPSN) conference series; and
• Advisor and Proposal Evaluator for the European Commission’s IST funding program.

Dr. Carlos Coello, Ph.D., Scientific Advisor

Carlos Coello received his Ph.D. degree in Computer Science from Tulane University in the United States, and is now a Professor at the Computer Science Department of CINVESTAV-IPN (located in Mexico City). His research has focused on the design of new meta-heuristic algorithms and techniques for solving single and multi-objective optimization problems (both constrained and unconstrained). He is also the:

• Associate Editor of the IEEE Transactions on Evolutionary Computation, Applied Soft Computing, Computational Optimization and Applications, Pattern Analysis and Applications and Journal of Heuristics;
• IEEE Fellow; and
• General Chair of the 2013 IEEE Congress on Evolutionary Computation.

Carlos has received several awards, including the 2012 National Medal of Science and Arts in the area of Physical, Mathematical and Natural Sciences (the highest award that a scientist can receive in Mexico) and the prestigious 2013 IEEE Kiyo Tomiyasu Award "for pioneering contributions to single- and multi-objective optimization techniques using bio-inspired meta-heuristics". He has produced/co-authored over 450 refereed publications in the form of books, book chapters, journal articles and conference papers.

Dr. Ernesto Costa, Ph.D., Scientific Advisor

Ernesto Costa received his Ph.D. degree from the University of Coimbra in Portugal, where he currently serves as Professor at the Department of Informatics Engineering. Besides teaching, Ernesto has been doing research in the areas of evolutionary computation, artificial life, complex systems, machine learning, cognition and computational biology. He is currently the Associate Editor of the International Journal of Natural Computing Research, and was the recipient of the 2009 EvoStar Award for “Outstanding Contributions to the Field of Evolutionary Computation.” Ernesto has organized several international scientific events and has published over 150 refereed publications in books, book chapters, journals and proceedings of conferences. Since December 2012, he is a member of the General Council of the University of Coimbra, a governing board of the university.

Dr. Pablo Moscato, Ph.D., Scientific Advisor

Pablo Moscato is an Australian Research Council Future Fellow (2012-16) and a Professor of Computer Science at The University of Newcastle.  At the California Institute of Technology (1988-89) he developed a methodology called memetic algorithms, which is now widely used around the world in Artificial Intelligence, Data Science, and Business and Consumer Analytics. Pablo is Founding Director of the Priority Research Centre for Bioinformatics, Biomarker Discovery and Information-based Medicine (2007-2015), and the Funding Director of Newcastle Bioinformatics Initiative (2002-2006) of The University of Newcastle. His expertise in Data Science was essential for a large number of applied projects.

Pablo has been working in Applied Mathematics for 30 years, and in heuristic methods for Operations Research problems since 1985. His work and ideas have been highly influential in a large number of scientific and technological fields and his manuscripts have been widely cited. The journal "Memetic Computing" is largely dedicated to a methodology he championed. Every 48 hours a new published paper describes a novel application of these techniques. Due this work and his other contributions in the areas of classification and machine learning, Pablo Moscato is very well-respected in the global academia and industry and has become one of Australia's most cited and influential computer scientists.

Dr. Vic Ciesielski, Ph.D., Scientific Advisor

Vic Ciesielski received his Ph.D. from Rutgers University in New Jersey. He is currently an Associate Professor in the School of Computer Science and Information Technology at RMIT University where he heads the Evolutionary Computation and Machine Learning Group. His research interests include genetic programming, data mining, evolutionary computer vision, deep learning and evolutionary art.

Vic has a record of successful application of Artificial Intelligence techniques to industrial problems. He has provided the scientific direction for over 20 industry projects of various sizes, which have involved the application of Artificial Intelligence techniques. These include an insurance underwriting system based on expert system technologies, an obstacle avoidance system for autonomous mining vehicles operating in tunnels, which uses machine learning and computer vision techniques, and a malt quality analysis system based on machine learning and texture analysis. Most recently he is responsible for the data mining behind the realas.com.au house price prediction app.

Dr. Łukasz Brocki, Ph.D., Scientific Advisor

Łukasz Brocki received his Ph.D. degree from the Polish-Japanese Academy of Information Technology. His research was focused on using recurrent neural networks for acoustic and language modeling for speech recognition. Łukasz took part in several European scientific projects including Luna, EU-Bridge or Clarin. His current research interests focus on deep learning, stacked LSTM neural networks, extreme learning machines and evolutionary computation. He has published several papers on using neural networks in language technology and prediction tasks.

Łukasz gathered experience while working in IBM Deutschland Entwicklung GmbH, Voice Department, where he was a member of international group working with the world's longest commercially developed speech recognition system – IBM ViaVoice. Łukasz founded Primespeech, the first Polish company that specializes in developing speech and language technology. Primespeech also produces optimization and prediction software that apply deep learning algorithms. The company's customers include key organizations in Poland such as PZU, City of Warsaw and the Polish Bank Association.

Dr. Longbing Cao, Ph.D., Scientific Advisor

Longbing Cao is a professor of information technology at the University of Technology in Sydney, Australia. As the founding Director of the university’s research institute: Advanced Analytics Institute, he created a few successful showcases that have been widely recognized, such as the only Australian group specially mentioned in the Australian government papers on big data, and the ATO annual reports and OECD reports on taxation analytics. Motivated by focusing on both high quality research and high impact development, he proposed several new concepts and supporting theories and tools, including non-IIDness learning, behaviour informatics, domain-driven data mining, and agent mining. He has also been leading many large analytical projects for the federal and state governments and large businesses in both Australia and China.

Longbing has been a key driver of several global initiatives in data science and analytics. He initiated the globally first research degrees in analytics: PhD Analytics and Master of Analytics (Research) in 2011 at UTS. He is the chair of the IEEE Task Force on Data Science and Advanced Analytics and the IEEE Task Force on Behavioral, Economic, and Socio-cultural Computing, and the chair of the ACM SIGKDD Australia and New Zealand Chapter. He also founded the IEEE International Conference on Data Science and Advanced Analytics, and is the Editor-in-Chief of the International Journal of Data Science and Analytics and the book series editor of the Data Analytics book series with Springer.