October 2017 -George Sugihara gives a talk on “Understanding Nature Holistically (and without equations) at MIT for the C.C. MEI Distinguished Speaker Series.

June 2017 – Dhanurjay “DJ” Patil, former Chief Data Scientist of the United States Office of Science and Technology Policy, stops by the lab to catch up with George Sugihara. During DJ’s undergraduate career at UCSD, he became involved in the Sugihara lab and the data-driven EDM methods we were developing for bettering weather prediction. For more information on the results of those weather prediction methods, read more on PNAS.

March 2017 – George Sugihara gives a talk on “An Equation-free Approach for Understanding Nature” at a seminar hosted by the Salk Institute.

October 2016 – George Sugihara and his team are featured on Science: “‘Messy Math’ from Sardine Studies Could Help Fight Flu Outbreaks.”

A group of researchers led by Sugihara’s postdoctoral researcher Ethan Deyle now has applied their fishy methods to flu, looking at 18 years of data on worldwide influenza outbreaks. They found that humidity is the strongest factor in driving influenza, but that temperature also plays a role, combining in a complex way that past studies were unable to pick up on. Read more on Science.


March 2016 – George Sugihara gives a talk at a seminar hosted by CEINT (Center for the Environmental Implications of NanoTechnology)

Despite the known reality and ubiquity of nonlinear dynamics in nature, and the costs associated with unanticipated threshold phenomena or tipping points, nearly all approaches to understand them have used linear statistical tools—static analytical tools based on a classical linear paradigm. This paradigm based on stable, stationary equilibrium points or cyclic equilibrium dynamics allows systems to be studied piecewise as a decomposable sum of independent parts; a theoretical expedient that applies robustly in designed engineering contexts. Read the abstract and webstream on CEINT.

October 2015 – George Sugihara and his team are featured on Wired: “Is it Foolish to Model Nature’s Complexity with Equations?”

Trying to manage a major fishery with such a primitive understanding of its biology seems like folly to George Sugihara, an ecologist at the Scripps Institution of Oceanography in San Diego. But he and his colleagues now think they have solved the mystery of the Fraser River salmon. Their crucial insight? Throw out the equations. Read more on Wire.

April 2015 – Keynote Address by George Sugihara, MS, PhD on “Correlation and Causation” 

Institute for Systems Biology Presents the 14th Annual International Symposium in Seattle | April 6 & 7, 2015 This year’s topic “Tipping Points in Medicine & Ecology” was aligned with ISB’s focus on personalized medicine and environmental sustainability. The principles of critical phase transitions, early warning signs and, more generally, complex systems dynamics, offer a theoretical framework and analysis tools for understanding and predicting major state transitions in human health and in ecosystems. The Symposium facilitated the translation of these theoretical principles to medicine and ecology.

March 31, 2015 – The Sugihara lab is mentioned in PNAS: “Equation-free Modeling Unravels the Behavior of Complex Ecological Systems”

With the term “equation-free” in the article title, Ye et al. (1) are suggesting broader implications of their approach, considering the centrality of equations in modern science. From the 1700s on, nature has been increasingly described by mathematical equations, with differential or difference equations forming the basic framework for describing dynamics. Read more on PNAS.

24_g-co2-lMarch 30, 2015 – An international group of mathematicians use a method developed by George Sugihara and confirms that carbon dioxide led to higher temperatures in the Past in Forbes.

To develop their conclusions, the team utilized a method to detect causality in complex systems developed by George Sugihara. These methods have been successfully used to determine issues of cause and effect in ecological systems where some variables may be dependent on one another, such as the relationship between sardine and anchovy populations with ocean temperatures in the Pacific Northwest. Read more on Forbes.

March 26, 2015 – The article “New fishery forecasting model ditches equations and assumptions, improves accuracy” from Fishsens Magazine also mentions the Sugihara lab’s accuracy in predicting the sockeye salmon recruitment rates.

The method known as empirical dynamic modeling showed greater accuracy in predicting 2014 sockeye salmon recruitment rates at Lake Shuswap than the fishery’s official, traditional forecasting technique. The paper describing the new method was published in the Proceedings of the National Academy of Sciences. Read more on Fishsens.

March 9, 2015 –The Sugihara lab makes the most accurate prediction on the Fraser River sockeye run mentioned in The Globe and Mail: “Scientists find way to better predict size of salmon runs in Fraser River”

Scientists at the Scripps Institution of Oceanography in California found their new method was more accurate than most preseason forecasts of Fraser River sockeye runs from the past 58 years. In 2014, they predicted the dominant sockeye salmon run would contain between 4.5 and 9.1 million fish, while the Fisheries and Oceans Canada forecast predicted a much broader range of 6.9 to 20 million. The actual run weighed in at about 8.8 million fish. Read more on the Globe and Mail.

January 2014 – “Tomorrow’s Catch – Chaos Theory’s Potential for Fisheries Management” in Science News

A management approach based on chaos theory could help prevent collapses of sardines and other valuable fishes. Read more on Science News.

February 2009 – “Using Chaos Theory to Revitalize Fisheries” in the Scientific American

There are fewer fish in the sea than ever. Complexity theory, argues mathematician George Sugihara, provides a counterintuitive way to revitalize the world’s fisheries Read more on Scientific American. 

Going beyond ecology

gr3December 2014 National Center for Biotechnology Information: “Sugihara Causality Analysis of Scalp EEG for Detection of Early Alzheimer’s Disease.”

Recently, Sugihara proposed an innovative causality concept, which, in contrast to statistical predictability in Granger sense, characterizes underlying deterministic causation of the system. This work exploits Sugihara causality analysis to develop novel EEG biomarkers for discriminating normal aging from mild cognitive impairment (MCI) and early Alzheimer’s disease (AD). Read more on NCBI.

October 2010 – George Sugihara was invited to speak at the 8th annual Global ARC.

Founded in 2002, Global ARC convenes a network of the world’s foremost pension funds, sovereign wealth funds, endowments, foundations and asset managers focused on the intersection of macro-economic developments, capital markets, and alternative investments. Read more about the 8th annual Global ARC.