Keynote Speaker

Carlos Gershenson, PhD

professor of computer science at Universidad Nacional Autonoma De Mexico

Carlos leads the Self-organizing Systems Lab. He has been an active researcher since 1997 and has 150 scientific publications in books, journals, and conference proceedings, which have been cited more than 4,500 times. He has given more than 250 presentations at conferences and research group seminars. He has a wide variety of academic interests, including complex systems, self-organization, urbanism, artificial life, evolution, cognition, artificial societies, and philosophy. Carlos is also Editor-in-Chief of Complexity Digest, Associate Editor for the journals Complexity and Frontiers in Robotics and AI, and member of the Board of Advisors for Scientific American.

Check out Complexity Explained by Prof. Gershenson and collaborators.

Facilitators

Facilitators will move between teams during the conference, supplying Complexity Science references, impactful connections, problem-solving frameworks, tooling, and relevant data sets. Their mission is to guide the "how" to enable each team to reach their highest potential and accomplish their initial goals, whether that be a research proposal, a business plan, or another outcome.

Michael Zargham, PhD

Founder and CEO at BlockScience; Visiting Researcher at WU Vienna (Cryptoeconomics Institute) 

Python • Systems Engineering • Economics • Governance • Blockchain • Data Science

Zargham is the founder and CEO of BlockScience, an engineering, research, and analytics firm focused on design and analysis of complex networks. Dr. Zargham holds a PhD in systems engineering from the University of Pennsylvania, where he studied optimization and control of decentralized networks. He is currently affiliated with the WU Vienna's Interdisciplinary Research Institute for Cryptoeconomics.

Ariadna Venegas-Li

PhD Candidate at UC Davis (Complexity Sciences Center)

Physics • Information Theory • Discrete Stochastic Processes • Quantum Information

Ariadna is pursuing a PhD in physics. Her research is focused on advancing the understanding of quantum stochastic processes by adapting tools from dynamical systems and information theory to characterize them. She is generally interested in applying these and other quantitative tools to systems with many interacting agents.

Jared Thompson, PhD

Senior Machine Learning Engineer at ATOMWISE

Python • R • Computational/Theoretical Chemistry • Control Theory • Information Theory • Deep Learning 

Jared is a “full-stack data scientist” interested in control theory and optimization, information theory, and intelligent (AI) systems of all sorts. His background is in computational and theoretical biophysics. He is currently working with the wonderful team at Atomwise, where he works on deep learning model development. This work aims to predict biological activity of a drug molecule from its X-ray crystal structure.

Sudebi Thakurata

Faculty Member at Srishti Institute of Art, Design & Technology; Co-founder at Depicentre Consulting

Research • Complex Systems Thinking • Design-led Innovation • Regenerative Leadership • Futurism

Sudebi is a meta-facilitator, futurist, educator and a designer of learning, narratives and regenerative leadership.  She designs experiences, engagement and environment that allow people to design their own solutions and narratives using different modes and media. A Creative Facilitator of SEAΔ, a trans-national cross-cultural leadership program, Sudebi has co-founded a design collective, Depicentre, and started a unique pedagogy, art and design-led trans-local initiative, “The Archival City- a site of learning”.

Justine Schott

Data analytics manager at Education Super highway; Data AMbassador at Datakind SF

Python • Education • Technology • Data Analysis • Business Insights • Modeling

In the past six years at EducationSuperHighway, Justine improved data transparency at the FCC by using school broadband data to create new, insightful metrics that had been otherwise impossible to calculate. As a data manager, she blends the stories told by the data with the organization’s expertise to create insights that power change. At DataKind SF, Justine manages a team of 5 data volunteers.

Diamantis Sellis, PhD

Complex System Modeler at CosmoTech

Complex Systems Modeling • Population Genomics • Bioinformatics

Diamantis Sellis is complex systems modeler at CosmoTech. He has more than 10 years of research experience in bioinformatics, genome complexity and population genetics. He has studied biology and holds an MS in Bioinformatics from Athens University, Greece, and a PhD in evolutionary biology from Stanford University, US.

Rose Sagun

The Asia Foundation; Co-chair, Harvard Alumni for Education; Instructor, General Assembly

Global Education Policy • Learning Innovations

Rose works in the international development space, particularly in education and learning across socio-cultural and political contexts. She is currently helping to develop initiatives across 15 countries in Asia.

Alexandra (Sasha) Mikhailova

PhD Candidate at UC Davis (Neuroscience Program)

Neuroscience • Microscopy • Education • Collaborative Drawing 

Alexandra has a background in translational neuroscience studying brain injury in early development. She is now pursuing a PhD examining how immune molecules regulate the proper establishment of connections in the brain. Her research is inherently interdisciplinary, and she hopes to bridge even more fields through Free Energy thinking and collaborative drawing.

Prahlad Menon, PhD

adjunct professor of bioengineering at university of pittsburgh; CEO and chief data scientist at QUANTMD

R • Biostatistics • Disease Modeling • Biomedical Imaging • Computational Fluid Dynamics

Dr. Menon's research is focused on artificial intelligence and data science applied to modeling imaging and time-series data in a variety of areas. He runs the MeDCaVE Lab, which is focused on robust algorithmic analysis of biomedical imaging data augmented with quantitative, physics‐based modeling of cardiovascular mechanics & hemodynamics. He has authored over 75 peer-reviewed publications and abstracts, and has served as a research adviser to dozens of undergraduate and graduate student researchers.

Glenn Magerman, PhD

assistant professor of economics at ECARES; Team Lead at learning from the curve

Economics • Statistics • Networks • Data Science

Glenn is an assistant professor of Economics (tenured) at ECARES, ULB. His research agenda focuses on social and economic networks, firm-to-firm relationships, and pricing mechanisms. He is also the founder of Magma, a firm providing data science solutions and strategic consulting to various industries.

Marek Laskowski, PhD

Senior Research Scientist at Block Science; Cofounder at Blockchain Lab at York University

Agent-based Modeling • Epidemiological Modeling • Simulation

Marek Laskowski earned his Ph.D. in Computer Engineering at the University of Manitoba in 2011 where he developed novel multi-agent simulation frameworks for modeling complex healthcare systems. His work in this field has been cited by the Centers for Disease Control (CDC) in Atlanta, Georgia. Since then, Marek co-founded the Blockchain Lab at the Schulich School of Business (at York University).

Jason Larkin, PhD

research scientist at cmu's Emerging Technology Center; Cofounder at PhD Mentors

Python • Multi-scale Modeling • Research and Publishing Process • Researcher Mental Health

Jason’s background is in multi-scale modeling, in particular the combination of quantum-scale Density Functional Theory with Molecular Dynamics simulations. He seeks to understand general principles behind emergent behavior in complex systems, and has recently focused his attention on understanding the immediate impact of quantum computing systems.

V. Bleu Knight

Senior Data Scientist at SavantX

Python • PCR • Neuroscience • Bioinformatics • Optimization • Data Science

Bleu works with a talented team at SavantX that implements augmented intelligence and quantum computing to solve energy reduction problems at scale. Their current focus is global shipping and the industrial supply chain. Her PhD research leveraged RNA sequencing and bioinformatics to explore biological identity, focusing on neural cell types.

Monica Kang

Founder & CEO at InnovatorsBox

Entrepreneurship • Creativity & Innovation • Mental Health • Diversity • Education

Monica Kang, Founder and CEO of InnovatorsBox®, is an educator at heart, transforming workplaces and communities with the power of creativity. Using innovative services and products, she works with industries worldwide including Fortune 500 companies, higher education, government, and nonprofits. Monica is the author of 'ReThink Creativity', has organized for Startup Weekend over the past 5 years, and previously worked in nuclear nonproliferation. 

Jenn Huff, PhD

Self-employed Science Writer; Curatorial Associate at Burke Museum of Natural History and Culture

Human Evolution • Human-Environment Interaction • Technology Change • Cooperation

Dr. Jenn Huff is an archaeologist with an interest in deep time questions about human evolution, human migrations into new landscapes, exchange networks, technology change, and human-environment interactions. She is currently working on a book that looks at human evolution and recent cultural perspectives to explore how humans cooperate.

Stéphanie Heckman

Creative Professional; Visual Facilitator; Singer-Songwriter

Psychology • Theories of Change • Sustainable Development

Stéphanie approaches the field of complexity from a social science angle, through her background in systems change, sustainable development, and human process design. With a MSc. in Strategic Leadership towards Sustainability, she works as visual facilitator supporting collective thought processes at conferences and meetings by translating them into sweeping illustrated ‘shared mental landscapes’.

Will Hamilton, PhD

Assistant Professor of Computer Science at McGill University

Python • Machine Learning • Network Analysis • Natural Language Processing

Will Hamilton is an Assistant Professor at McGill University and a Canada CIFAR AI Chair. His research focuses on the development of machine learning models for network-structured data. His work has been featured in numerous media outlets, including Wired, The New York Times, and The BBC.

Sean Griffin

Chief Executive Officer at Disaster Tech

Decision Science • Incident Management • Data Science • HPC

Sean is the CEO of Disaster Tech, a public benefit company applying data science for decision making before, during, and after disasters. Sean has served as Director for Incident Management Integration Policy on the White House National Security Council and is an U.S. Navy veteran.

Richard J. Cordés

Agency Point-of-Contact at COGSEC; Partner at Remoter Consulting Group

Open-source Intelligence • Systems Warfare • Distributed Teams

R.J. spends his time infusing complexity science into military and intelligence research to generate best practice for remote teams, civilian or otherwise. He is a serial contributor within the Defense Community, working with complexity-oriented organizations on DARPA grants, research, and inter-agency collaborations. He currently represents Remotor and COGSEC in the information warfare subdivision of a working group on expeditionary warfare in addition to sitting on several other committees and working groups in the IEEE, Department of Defense, and Private Sector.

Probal Banerjee

Co-founder & CEO at Depicentre Consulting

Design-led Innovation • Transformative and Emergent Leadership • Executive Coaching • Entrepreneurship

Probal is the co-founder and CEO of the design-led collective, Depicentre Consulting. He works on the interfaces of business, learning, design, analytics, innovation and storytelling. With leadership experience across seven countries strengthening his ability to manage cross-cultural & cross-functional virtual teams in complex matrix organisations, he has a passion for driving content & culture driven organisations making economic, social, ecological and educational impact.

Chenling Xu Antelope

PhD candidate at UC BErkeley (Computational Biology program)

R • Computational Biology • Data Analysis • Genetics

Chenling has a background in evolutionary genetics and is now pursuing a PhD in applying both simulation and machine learning techniques to single-cell RNA sequencing data. Her current project is focused on the immunological changes in Multiple Sclerosis patients. Through her wandering across different fields of biology, she finds Bayesian statistical thinking and a free imagination to be the common language of discoveries in complex biological systems.