Albert-László Barabási

{{Short description|Hungarian-American physicist (born 1967)}} {{western name order|Barabási Albert-László}} {{Use mdy dates|date=April 2016}} {{Infobox scientist | name = Albert-László Barabási | image = Albert-Laszlo Barabasi - Annual Meeting of the New Champions 2012.jpg | caption = Barabási at the World Economic Forum Annual Meeting of the New Champions in 2012 | birth_name = Barabási Albert László | birth_date = {{Birth date and age|1967|3|30}} | birth_place = Cârța, Harghita County, SR Romania | death_date = | death_place = | education = University of Bucharest <br />Eötvös Loránd University <small>(MS)</small><br />Boston University <small>(PhD)</small> | thesis_title = Growth and roughening of non-equilibrium interfaces | thesis_url = https://ui.adsabs.harvard.edu/abs/1994PhDT........80B/abstract | thesis_year = 1994 | doctoral_advisor = H. Eugene Stanley | academic_advisors = | fields = Physics, Network Science, Network Medicine | known_for = Research of network science <br /> The concept of scale-free networks<br />Proposal of Barabási–Albert model <br /> Founder of Network Medicine <br /> Introducing Network controllability | doctoral_students = {{Plainlist| * Ginestra Bianconi * Reka Albert * César Hidalgo * Dashun Wang }} | notable_students = | influences = | influenced = | awards = {{Plainlist| * Gothenburg Lise Meitner Award (2024) * Lilienfeld Prize, APS (2023) *EPS Statistical and Nonlinear Physics Prize (2021) * Lagrange Prize (2011) * C&C Prize, NEC, Japan (2008) }} | spouse = | partner = | children = | signature = | signature_alt = | website = {{URL|https://barabasilab.com}} | footnotes = }}

'''Albert-László Barabási''' (born March 30, 1967) is a Romanian-born Hungarian-American physicist, renowned for his pioneering discoveries in network science and network medicine.

He is a distinguished university professor and Robert Gray Professor of Network Science at Northeastern University, holding additional appointments at the Department of Medicine, Harvard Medical School and the Department of Network and Data Science<ref>[https://cns.ceu.edu/people People at Center for Network Science], Central European University website; accessed January 10, 2016.</ref> at Central European University. Barabási previously served as the former Emil T. Hofmann Professor of Physics at the University of Notre Dame and was an associate member of the Center of Cancer Systems Biology at the Dana–Farber Cancer Institute, Harvard University.

In 1999 Barabási discovered the concept of scale-free networks and proposed the Barabási–Albert model, which explains the widespread emergence of such networks in natural, technological and social systems, including the World Wide Web and online communities. Barabási is the founding president of the Network Science Society,<ref>{{Cite web | url=http://netscisociety.net/ |title = NetSci – the Network Science Society}}</ref> which sponsors the flagship NetSci Conference established in 2006.

==Birth and education== Barabási was born on March 30, 1967 to an ethnic Hungarian family in Cârța, Harghita County, Romania. His father, László Barabási, was a historian, museum director and writer, while his mother, Katalin Keresztes, taught literature, and later became director of a children's theater.<ref name="Keiger">{{cite news |last1=Keiger |first1=Dale |title=Looking for the Next Big Thing |work=Notre Dame Magazine |date=24 November 2008 |url=https://magazine.nd.edu/stories/looking-for-the-next-big-thing/ }}</ref> He attended a high school specializing in science and mathematics; where he won a local physics olympiad in the 9th and 12th grade. Between 1986 and 1989, he studied physics and engineering at the University of Bucharest; during which time he began researching chaos theory and published three papers.<ref name="Keiger"/>

In 1989, Barabási emigrated to Hungary, together with his father. He received a master's degree in 1991 at Eötvös Loránd University in Budapest, under the supervision of Tamás Vicsek. Barabási then enrolled in the Physics program at Boston University, where he earned his PhD in 1994. His doctoral thesis, conducted under the direction of H. Eugene Stanley,<ref>{{cite web|url=http://polymer.bu.edu/hes/gradstudents.html|title=H. Eugene Stanley: Ph.D. Theses Supervised|website=Polymer.bu.edu|access-date=2016-01-11}}</ref> was published by Cambridge University Press under the title ''Fractal Concepts in Surface Growth''.<ref>{{MathGenealogy|id=288366}}</ref><ref>{{Cite book |last=Albert-Laszlo Barabasi |first=Eugene H Stanley |title=Fractal Concepts in Surface Growth |publisher=Cambridge University Press |year=1995 |isbn=978-0-511-59979-8 |language=English}}</ref>

==Academic career== {{BLP sources section|date=January 2016}} After a one-year postdoc at the IBM Thomas J. Watson Research Center, Barabási joined the faculty at the University of Notre Dame in 1995. In 2000, at the age of 32, he was named the Emil T. Hofman Professor of Physics, becoming the youngest endowed professor. In 2004 he founded the Center for Complex Network Research.

In 2005–6 he was a visiting professor at Harvard University. In fall 2007, Barabási left Notre Dame to become a Distinguished University Professor and director of the Center for Network Science at Northeastern University. Concurrently, he took up an appointment in the Department of Medicine at Harvard Medical School.

As of 2008, Barabási holds Hungarian, Romanian and U.S. citizenship.<ref>{{cite web|url=http://www.barabasi.com/01-AL_Barabasi_Curriculum_Vitae-FINAL-Sept-2008.pdf|title=Albert-László Barabási CV|access-date=January 10, 2016|archive-url=https://web.archive.org/web/20160303210855/http://www.barabasi.com/01-AL_Barabasi_Curriculum_Vitae-FINAL-Sept-2008.pdf|archive-date=March 3, 2016}}</ref><ref>{{Cite web|title=ETSI de Telecomunicación: ALBERT LASZLÓ BARABÁSI|url=https://www.etsit.upm.es/de/school/about-etsit/honoris-causa/albert-laszlo-barabasi.html|access-date=2020-11-15|website=www.etsit.upm.es}}</ref><ref>{{Cite web|title=Albert-László Barabási – Khoury College of Computer Sciences|date=February 16, 2016 |url=https://www.khoury.northeastern.edu/people/albert-laszlo-barabasi/|access-date=2020-11-15|language=en-US}}</ref>

==Research and achievements== Barabási's contributions to network science and network medicine have fundamentally changed the study of complex systems.

=== Scale-free networks === Barabási's work challenged the prevailing notion that complex networks could be adequately modeled as random networks. He is particularly renowned for his 1999 discovery of ''scale-free networks.'' In 1999 he created a map of the World Wide Web<ref>{{cite journal |last1=Albert |first1=Réka |last2=Jeong |first2=Hawoong |last3=Barabási |first3=Albert-László |title=Diameter of the World-Wide Web |journal=Nature |date=September 1999 |volume=401 |issue=6749 |pages=130–131 |doi=10.1038/43601 |arxiv=cond-mat/9907038 |bibcode=1999Natur.401..130A |s2cid=4419938 }}</ref> and found that its degree distribution does not follow the Poisson distribution expected for random networks, but instead it is best approximated by a power law. Collaborating with his student, Réka Albert, he introduced the Barabási–Albert model,<ref>{{Cite journal |last=Barabási, Albert-László and Réka Albert |title=Emergence of scaling in random networks |journal=Science |volume=283 |pages=509–512}}</ref> which proposed that growth and preferential attachment are jointly responsible for the emergence of the scale-free property in real-world networks. The following year, Barabási demonstrated that the power law degree distribution is not limited to the World Wide Web, but also appear in metabolic networks<ref>{{cite journal |last1=Jeong |first1=H. |last2=Tombor |first2=B. |last3=Albert |first3=R. |last4=Oltvai |first4=Z. N. |last5=Barabási |first5=A.-L. |title=The large-scale organization of metabolic networks |journal=Nature |date=October 2000 |volume=407 |issue=6804 |pages=651–654 |doi=10.1038/35036627 |pmid=11034217 |arxiv=cond-mat/0010278 |bibcode=2000Natur.407..651J }}</ref> and protein–protein interaction<ref>{{cite journal |last1=Jeong |first1=H. |last2=Mason |first2=S. P. |last3=Barabási |first3=A.-L. |last4=Oltvai |first4=Z. N. |title=Lethality and centrality in protein networks |journal=Nature |date=May 2001 |volume=411 |issue=6833 |pages=41–42 |doi=10.1038/35075138 |pmid=11333967 |arxiv=cond-mat/0105306 |bibcode=2001Natur.411...41J }}</ref> networks, demonstrating the universality of the scale-free property. In 2009 ''Science'' celebrated the ten-year anniversary of Barabási's groundbreaking discovery by dedicating a special issue to Complex Systems and Networks,<ref>{{cite journal |last1=Barabási |first1=Albert-László |title=Scale-Free Networks: A Decade and Beyond |journal=Science |date=24 July 2009 |volume=325 |issue=5939 |pages=412–413 |doi=10.1126/science.1173299 |pmid=19628854 |bibcode=2009Sci...325..412B |s2cid=43910070 }}</ref><ref>{{cite journal |last1=Jasny |first1=Barbara R. |last2=Zahn |first2=Laura M. |last3=Marshall |first3=Eliot |title=Connections |journal=Science |date=24 July 2009 |volume=325 |issue=5939 |page=405 |doi=10.1126/science.325_405 |pmid=19628849 |bibcode=2009Sci...325..405J }}</ref> recognizing his paper as one of the most cited in the journal's history.{{Citation needed|date=July 2025}}

=== Network robustness and resilience === In a 2001 paper with Réka Albert and Hawoong Jeong, Barabási demonstrated that networks exhibit robustness to random failures but are highly vulnerable to targeted attacks,<ref>{{cite book |last1=Barabási |first1=Albert-László |title=Network science |date=2016 |isbn=978-1-107-07626-6 |location=Cambridge, United Kingdom}}{{page needed|date=January 2024}}</ref> a characteristic known as the Achilles' heel property. Specifically, networks can easily withstand the random failure of a large number of nodes, highlighting their significant robustness. However, they are prone to rapid collapse when the most connected hubs are deliberately removed. The breakdown threshold of a network was analytically linked <ref>{{Cite journal |date=2000 |title=Resilience of the Internet to Random Breakdowns |journal=Physical Review Letters |volume=85 |issue=21 |pages=4626–4628|doi=10.1103/PhysRevLett.85.4626 |pmid=11082612 |arxiv=cond-mat/0007048 |bibcode=2000PhRvL..85.4626C |s2cid=15372152 |last1=Cohen |first1=Reuven |last2=Erez |first2=Keren |last3=Ben-Avraham |first3=Daniel |last4=Havlin |first4=Shlomo }}</ref> to the second moment of the degree distribution, whose convergence to zero for large networks explain why heterogenous networks can survive the failure of a large fraction of their nodes. In 2016, Barabási extended these concepts to network resilience,<ref>{{Cite journal |last=J. Gao, B. Barzel, A.-L. Barabasi |date=2016 |title=Universal resilience patterns in complex networks |url=https://www.nature.com/articles/nature16948 |journal=Nature |volume=530 |issue= 7590|pages=307–312|doi= 10.1038/nature16948|pmid= 26887493|bibcode=2016Natur.530..307G |url-access=subscription }}</ref> demonstrating that the network structure determines a system's capacity for resilience. While robustness refers to the system's ability to carry out its basic functions despite the loss of some nodes and links, resilience involved the system's ability to adapt to internal and external disturbances by modifying its mode of operation without losing functionality. Therefore, resilience is a dynamical property that requires a fundamental shift in the system's core activities.

=== Network medicine === Barabási is recognized as one of the founders of network medicine,<ref>{{Cite web |title=History of Network Medicine |url=https://www.network-medicine.org/history |access-date=2024-12-19 |website=Network Medicine Institute and Alliance |language=en-US}}</ref> a term he introduced in his 2007 article entitled "Network Medicine – From Obesity to the "Diseasome"", published in The New England Journal of Medicine.<ref>{{cite journal |last1=Barabási |first1=Albert-László |title=Network Medicine — From Obesity to the 'Diseasome' |journal=New England Journal of Medicine |date=26 July 2007 |volume=357 |issue=4 |pages=404–407 |doi=10.1056/NEJMe078114 |pmid=17652657 }}</ref> His work established the concept of diseasome, or disease network,<ref>{{Cite journal |date=2007 |title=The human disease network |journal=Proceedings of the National Academy of Sciences |volume=104 |issue=21 |pages=8685–8690|doi=10.1073/pnas.0701361104 |pmid=17502601 |pmc=1885563 |bibcode=2007PNAS..104.8685G |doi-access=free |last1=Goh |first1=Kwang-Il |last2=Cusick |first2=Michael E. |last3=Valle |first3=David |last4=Childs |first4=Barton |last5=Vidal |first5=Marc |last6=Barabási |first6=Albert-László }}</ref> which illustrates how diseases are interconnected through shared genetic factors, highlighting their common genetic roots. He subsequently pioneered the use of large patient data, linking the roots of disease comorbidity to molecular networks.<ref>{{cite journal |last1=Barabási |first1=Albert-László |last2=Gulbahce |first2=Natali |last3=Loscalzo |first3=Joseph |title=Network medicine: a network-based approach to human disease |journal=Nature Reviews Genetics |date=January 2011 |volume=12 |issue=1 |pages=56–68 |doi=10.1038/nrg2918|pmid=21164525 |pmc=3140052 }}</ref> A key concept of network medicine is Barabási's discovery that genes associated with the same disease are located in the same network neighborhood,<ref>{{cite journal |last1=Menche |first1=J. |last2=Sharma |first2=A. |last3=Kitsak |first3=M. |last4=Ghiassian |first4=S. D. |last5=Vidal |first5=M. |last6=Loscalzo |first6=J. |last7=Barabasi |first7=A.-L. |title=Uncovering disease-disease relationships through the incomplete interactome |journal=Science |date=20 February 2015 |volume=347 |issue=6224 |article-number=1257601 |doi=10.1126/science.1257601 |pmid=25700523 |pmc=4435741 }}</ref> which led to the concept of disease module, which is currently employed to facilitate drug discovery, drug design, and the development of biomarkers. He elaborated on these concepts in his a 2012 TEDMED talk,<ref>{{Citation |title=Do your proteins have their own social network? | date=May 31, 2012 |url=https://www.youtube.com/watch?v=10oQMHadGos |language=en |access-date=2022-11-01}}</ref> emphasizing their significance in medical research and treatment strategies.

His contributions have been instrumental in establishing the Channing Division of Network Medicine at Harvard Medical School and the Network Medicine Institute, representing 33 universities and institutions around the world committed to advancing the field. Barabási's work in network medicine has led to multiple experimentally falsifiable predictions, helping identify experimentally validated novel pathways in asthma,<ref>{{cite journal |last1=Sharma |first1=Amitabh |last2=Menche |first2=Jörg |last3=Huang |first3=C. Chris |last4=Ort |first4=Tatiana |last5=Zhou |first5=Xiaobo |last6=Kitsak |first6=Maksim |last7=Sahni |first7=Nidhi |last8=Thibault |first8=Derek |last9=Voung |first9=Linh |last10=Guo |first10=Feng |last11=Ghiassian |first11=Susan Dina |last12=Gulbahce |first12=Natali |last13=Baribaud |first13=Frédéric |last14=Tocker |first14=Joel |last15=Dobrin |first15=Radu |last16=Barnathan |first16=Elliot |last17=Liu |first17=Hao |last18=Panettieri |first18=Reynold A. |last19=Tantisira |first19=Kelan G. |last20=Qiu |first20=Weiliang |last21=Raby |first21=Benjamin A. |last22=Silverman |first22=Edwin K. |last23=Vidal |first23=Marc |last24=Weiss |first24=Scott T. |last25=Barabási |first25=Albert-László |title=A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma |journal=Human Molecular Genetics |date=June 2015 |volume=24 |issue=11 |pages=3005–3020 |doi=10.1093/hmg/ddv001 |pmc=4447811 |pmid=25586491 }}</ref> the prediction of new mechanism of action for compounds such as rosmarinic acid,<ref>{{cite journal |last1=do Valle |first1=Italo F. |last2=Roweth |first2=Harvey G. |last3=Malloy |first3=Michael W. |last4=Moco |first4=Sofia |last5=Barron |first5=Denis |last6=Battinelli |first6=Elisabeth |last7=Loscalzo |first7=Joseph |last8=Barabási |first8=Albert-László |title=Network medicine framework shows that proximity of polyphenol targets and disease proteins predicts therapeutic effects of polyphenols |journal=Nature Food |date=19 March 2021 |volume=2 |issue=3 |pages=143–155 |doi=10.1038/s43016-021-00243-7 |pmid=37117448 |s2cid=232317723 |hdl=1871.1/f3838307-b0e0-4c44-91e0-0aca528010c1 |url=https://research.vu.nl/en/publications/f3838307-b0e0-4c44-91e0-0aca528010c1 |hdl-access=free }}</ref> and the repurposing of existing drugs for new therapeutic functions (drug repurposing).<ref>{{cite journal |last1=Cheng |first1=Feixiong |last2=Desai |first2=Rishi J. |last3=Handy |first3=Diane E. |last4=Wang |first4=Ruisheng |last5=Schneeweiss |first5=Sebastian |last6=Barabási |first6=Albert-László |last7=Loscalzo |first7=Joseph |title=Network-based approach to prediction and population-based validation of in silico drug repurposing |journal=Nature Communications |date=12 July 2018 |volume=9 |issue=1 |page=2691 |doi=10.1038/s41467-018-05116-5 |pmc=6043492 |pmid=30002366 |bibcode=2018NatCo...9.2691C }}</ref>

The practical applications of network medicine have made significant impacts in clinical settings. For example, his research aids physicians in determining whether rheumatoid arthritis patients will respond to anti-TNF therapy.<ref>{{cite journal |last1=Cohen |first1=Stanley |last2=Wells |first2=Alvin F. |last3=Curtis |first3=Jeffrey R. |last4=Dhar |first4=Rajat |last5=Mellors |first5=Theodore |last6=Zhang |first6=Lixia |last7=Withers |first7=Johanna B. |last8=Jones |first8=Alex |last9=Ghiassian |first9=Susan D. |last10=Wang |first10=Mengran |last11=Connolly-Strong |first11=Erin |last12=Rapisardo |first12=Sarah |last13=Gatalica |first13=Zoran |last14=Pappas |first14=Dimitrios A. |last15=Kremer |first15=Joel M. |last16=Saleh |first16=Alif |last17=Akmaev |first17=Viatcheslav R. |title=A Molecular Signature Response Classifier to Predict Inadequate Response to Tumor Necrosis Factor-α Inhibitors: The NETWORK-004 Prospective Observational Study |journal=Rheumatology and Therapy |date=September 2021 |volume=8 |issue=3 |pages=1159–1176 |doi=10.1007/s40744-021-00330-y |pmc=8214458 |pmid=34148193 }}</ref><ref>{{Cite journal |last1=Ghiassian |first1=Susan D |last2=Voitalov |first2=Ivan |last3=Withers |first3=Johanna B |last4=Santolini |first4=Marc |last5=Saleh |first5=Alif |last6=Akmaev |first6=Viatcheslav R |date=August 2022 |title=Network-based response module {{sic|comprised |hide=y|of}} gene expression biomarkers predicts response to infliximab at treatment initiation in ulcerative colitis |journal=Translational Research |language=en |volume=246 |pages=78–86 |doi=10.1016/j.trsl.2022.03.006|pmid=35306220 |s2cid=247514416 |doi-access=free }}</ref> During COVID Barabási led a major collaboration involving researchers from Harvard University, Boston University and The Broad Institute, to predict and experimentally test the efficacy for COVID patients of 6,000 approved drugs.<ref>{{cite journal |last1=Morselli Gysi |first1=Deisy |last2=do Valle |first2=Ítalo |last3=Zitnik |first3=Marinka |last4=Ameli |first4=Asher |last5=Gan |first5=Xiao |last6=Varol |first6=Onur |last7=Ghiassian |first7=Susan Dina |last8=Patten |first8=J. J. |last9=Davey |first9=Robert A. |last10=Loscalzo |first10=Joseph |last11=Barabási |first11=Albert-László |title=Network medicine framework for identifying drug-repurposing opportunities for COVID-19 |journal=Proceedings of the National Academy of Sciences |date=11 May 2021 |volume=118 |issue=19 |article-number=e2025581118 |doi=10.1073/pnas.2025581118 |pmid=33906951 |pmc=8126852 |arxiv=2004.07229 |bibcode=2021PNAS..11825581M |doi-access=free }}</ref><ref>{{Cite journal |last1=Patten |first1=J.J. |last2=Keiser |first2=Patrick T. |last3=Morselli-Gysi |first3=Deisy |last4=Menichetti |first4=Giulia |last5=Mori |first5=Hiroyuki |last6=Donahue |first6=Callie J. |last7=Gan |first7=Xiao |last8=Valle |first8=Italo do |last9=Geoghegan-Barek |first9=Kathleen |last10=Anantpadma |first10=Manu |last11=Boytz |first11=RuthMabel |last12=Berrigan |first12=Jacob L. |last13=Stubbs |first13=Sarah H. |last14=Ayazika |first14=Tess |last15=O'Leary |first15=Colin |date=September 2022 |title=Identification of potent inhibitors of SARS-CoV-2 infection by combined pharmacological evaluation and cellular network prioritization |journal=iScience |language=en |volume=25 |issue=9 |article-number=104925 |doi=10.1016/j.isci.2022.104925 |pmc=9374494 |pmid=35992305|bibcode=2022iSci...25j4925P }}</ref>

=== Dark matter of nutrition and food complexity === Barabási's work on nutritional dark matter and food composition, in collaboration with Giulia Menichetti, has fundamentally reshaped our understanding of diet as a complex system and its implication for health. In his 2019 study,<ref>{{Cite journal |first1=Albert-László |last1=Barabási |first2=Giulia |last2=Menichetti |first3=Joseph |last3=Loscalzo |date=2019 |title=THhe Unmapped Chemical Complexity of Our Diet |url=https://www.nature.com/articles/s43016-019-0005-1 |journal=Nature Food |volume=1 |pages=31–37 |doi=10.1038/s43016-019-0005-1 |url-access=subscription }}</ref> he revealed that conventional nutritional databases track only a minuscule fraction of the over 26,000 biochemicals present in food, coining the term "nutritional dark matter," work that inspired the [https://www.rockefellerfoundation.org/initiatives/periodic-table-of-food/ Periodic Table of Food Initiative] by the Rockefeller Foundation and the [https://newsroom.heart.org/news/new-scientific-resources-map-food-components-to-improve-human-and-environmental-health#:~:text=DALLAS%2C%20April%2024%2C%202024%20%E2%80%94,data%2C%20and%20training%20aimed%20at American Heart Association]. In 2021, he extended network medicine approaches to elucidate the health implications<ref>{{Cite journal |first1=Italo F. |last1=Do Valle |first2=Harvey G. |last2=Roweth |first3=Michael W. |last3=Malloy |first4=Sofia |last4=Moco |first5=Denis |last5=Barron |first6=Elisabeth |last6=Battinelli |first7=Joseph |last7=Loscalzo |first8=Albert-László |last8=Barabási |date=2021 |title=Network Medicine Framework Shows That Proximity of Polyphenol Targets and Disease Proteins Predicts Therapeutic Effects of Polyphenols |url=https://www.nature.com/articles/s43016-021-00243-7 |journal=Nature Food |volume=2 |issue=3 |pages=143–155 |doi=10.1038/s43016-021-00243-7 }}</ref> of polyphenols, demonstrating how intricate molecular networks connect dietary compounds to health outcomes.<ref>{{Cite journal |first1=Giulia |last1=Menichetti |first2=Albert-László |last2=Barabási |first3=Joseph |last3=Loscalzo |date=2024 |title=Decoding the Foodome: Molecular Networks Connecting Diet and Health |journal=Annual Review of Nutrition |volume=44 |issue=1 |pages=257–288 |doi=10.1146/annurev-nutr-062322-030557 |pmid=39207880 |pmc=11610447 }}</ref> His research on food processing led to the development of the first AI tool to predict the degree of food processing for any food,<ref>{{Cite journal |first1=Giulia |last1=Menichetti |first2=Babak |last2=Ravandi |first3=Dariush |last3=Mozaffarian |first4=4lbert-László |last4=Barabási |date=2023 |title=Machine Learning Prediction of the Degree of Food Processing |journal=Nature Communications |volume=14 |issue=1 |page=2312 |doi=10.1038/s41467-023-37457-1 |pmid=37085506 |pmc=10121643 |bibcode=2023NatCo..14.2312M }}</ref> and showed that over 73% of the US food supply is ultra-processed and correlating processing levels with adverse health markers. Barabási's efforts culminated in the 2025 release of GroceryDB<ref>{{Cite journal |first1=Albert |last1=Mehler |first2=Albert-László |last2=Barabási |first3=Giulia |last3=Menichetti |date=2025 |title=Prevalence of Processed Foods in Major US Grocery Stores |url=https://www.nature.com/articles/s43016-024-01095-7 |journal=Nature Food |volume=6 |issue=3 |pages=296–308 |doi=10.1038/s43016-024-01095-7 |pmid=39806219 |url-access=subscription }}</ref> and the [https://www.truefood.tech/ TrueFood database], that is used by millions on a daily basis, as it reveals the processing levels of foods in US supermarkets.

=== Human dynamics === Barabási in 2005 discovered the fat-tailed nature of the interevent times in human activity patterns. The pattern indicated that human activity is bursty - short periods of intensive activity are followed by long periods that lack detectable activity. Bursty patterns have been subsequently discovered in a wide range of processes, from web browsing to email communications and gene expression patterns. He proposed the Barabási model<ref name="Barabasi05-1">{{cite journal|author=A.-L. Barabási|year=2005|title=The origin of bursts and heavy tails in human dynamics|journal=Nature|volume=435|pages=207–11|pmid=15889093|issue=7039|doi=10.1038/nature03459|arxiv = cond-mat/0505371|bibcode=2005Natur.435..207B|s2cid=4419475}}</ref> of human dynamics, to explain the phenomena, demonstrating that a queuing model can explain the bursty nature of human activity, a topic is covered by his book ''Bursts: The Hidden Pattern Behind Everything We Do''.<ref>{{Cite book |last=Barabási |first=Albert-László |title=Bursts: the hidden pattern behind everything we do |date=2010 |publisher=Dutton |isbn=978-0-525-95160-5 |location=New York, N.Y. |oclc=426800811 }}{{page needed|date=January 2024}}</ref>

=== Human mobility === Barabási laid foundational work in understanding individual human mobility patterns through a series of influential papers. In his 2008 Nature publication,<ref>{{cite journal |last1=González |first1=Marta C. |last2=Hidalgo |first2=César A. |last3=Barabási |first3=Albert-László |title=Understanding individual human mobility patterns |journal=Nature |date=June 2008 |volume=453 |issue=7196 |pages=779–782 |doi=10.1038/nature06958 |pmid=18528393 |arxiv=0806.1256 |bibcode=2008Natur.453..779G |s2cid=4419468 }}</ref> Barabási utilized anonymized mobile phone data to analyze human mobility, discovering that human movement exhibits a high degree of regularity in time and space, with individuals showing consistent travel distances and a tendency to return to frequently visited locations. In a subsequent 2010 Science paper,<ref>{{cite journal |last1=Song |first1=Chaoming |last2=Qu |first2=Zehui |last3=Blumm |first3=Nicholas |last4=Barabási |first4=Albert-László |title=Limits of Predictability in Human Mobility |journal=Science |date=19 February 2010 |volume=327 |issue=5968 |pages=1018–1021 |doi=10.1126/science.1177170 |pmid=20167789 |bibcode=2010Sci...327.1018S |s2cid=13847306 }}</ref> he explored the predictability of human dynamics by analyzing mobile phone user trajectories. Contrary to expectations, he found a 93% predictability of in human movements across all users. He introduced two principles governing human trajectories, leading to the development of the widely used model for individual mobility.<ref>{{cite journal |last1=Song |first1=Chaoming |last2=Koren |first2=Tal |last3=Wang |first3=Pu |last4=Barabási |first4=Albert-László |title=Modelling the scaling properties of human mobility |journal=Nature Physics |date=October 2010 |volume=6 |issue=10 |pages=818–823 |doi=10.1038/nphys1760 |arxiv=1010.0436 |bibcode=2010NatPh...6..818S }}</ref> Using this modeling framework, a decade before the COVID-19 pandemic, Barabási predicted the spreading patterns of a virus transmitted through direct contact.<ref>{{cite journal |last1=Wang |first1=Pu |last2=González |first2=Marta C. |last3=Hidalgo |first3=César A. |last4=Barabási |first4=Albert-László |title=Understanding the Spreading Patterns of Mobile Phone Viruses |journal=Science |date=22 May 2009 |volume=324 |issue=5930 |pages=1071–1076 |doi=10.1126/science.1167053 |pmid=19342553 |arxiv=0906.4567 |bibcode=2009Sci...324.1071W }}</ref>

=== Network control === Barabási has made significant contributions to the understanding of network controllability and observability, addressing the fundamental question of how large networks regulate and manage their own behavior. He was the first to apply the tools of control theory to network science, bridging disciplines that had traditionally been studied separately. He proposed a method to identify the nodes through which one can control a complex network, by mapping the control problem, widely studied in physics and engineering since Maxwell, into graph matching, merging statistical mechanics and control theory.<ref>{{Cite journal |date=2011 |title=Controllability of complex networks |journal=Nature |volume=473 |issue=7346 |pages=167–173|doi=10.1038/nature10011 |pmid=21562557 |bibcode=2011Natur.473..167L |s2cid=4334171 |last1=Liu |first1=Yang-Yu |last2=Slotine |first2=Jean-Jacques |last3=Barabási |first3=Albert-László }}</ref>

Barabási utilized network control principles to predict the functions of individual neurons within the Caenorhabditis elegans connectome. This application provided direct experimental confirmation of network control theories by successfully identifying new neurons involved in the organism's locomotion, and experimentally confirming the validity of the predictions.<ref>{{cite journal |last1=Yan |first1=Gang |last2=Vértes |first2=Petra E. |last3=Towlson |first3=Emma K. |last4=Chew |first4=Yee Lian |last5=Walker |first5=Denise S. |last6=Schafer |first6=William R. |last7=Barabási |first7=Albert-László |title=Network control principles predict neuron function in the Caenorhabditis elegans connectome |journal=Nature |date=October 2017 |volume=550 |issue=7677 |pages=519–523 |doi=10.1038/nature24056 |pmid=29045391 |pmc=5710776 |bibcode=2017Natur.550..519Y }}</ref> His work demonstrated the practical utility of network control methods in biological systems, highlighting their potential for uncovering previously unknown functional components within complex networks.<ref>{{Cite journal |last=Yang-Yu Liu and Albert-László Barabási |date=2016 |title=Control principles of complex systems |url=https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.88.035006 |journal=Rev. Mod. Phys. |volume=88 |issue=3 |article-number=035006 |doi=10.1103/RevModPhys.88.035006 |arxiv=1508.05384 |bibcode=2016RvMP...88c5006L }}</ref>

==Awards==

Barabási was the recipient of the 2024 Gothenburg Lise Meitner Award;<ref>{{Cite web |date=2023-01-30 |title=Gothenburg Lise Meitner Award |url=https://www.chalmers.se/en/departments/physics/resources-and-collaborations/gpc/gothenburg-lise-meitner-award/#laureate-of-the-gothenburg-lise-meitner-award-2024:-albert-laszlo-barabasi |access-date=2024-12-19 |website=www.chalmers.se |language=en}}</ref> he has also been the recipient of the 2023 Julius Edgar Lilienfeld Prize, the top prize of the American Physical Society,<ref>{{Cite web |title=2023 Julius Edgar Lilienfeld Prize Recipient |url=https://www.aps.org/programs/honors/prizes/prizerecipient.cfm?last_nm=Barabasi&first_nm=Albert&year=2023 |publisher=APS}}</ref> "for pioneering work on the statistical physics of networks that transformed the study of complex systems, and for lasting contributions in communicating the significance of this rapidly developing field to a broad range of audiences." In 2021 he received the EPS Statistical and Nonlinear Physics Prize, awarded by the European Physical Society for "his pioneering contributions to the development of complex network science, in particular for his seminal work on scale-free networks, the preferential attachment model, error and attack tolerance in complex networks, controllability of complex networks, the physics of social ties, communities, and human mobility patterns, genetic, metabolic, and biochemical networks, as well as applications in network biology and network medicine."

Barabási has been elected to the US National Academy of Sciences,<ref>{{Cite web |first=Noah |last=Lloyd |date=May 6, 2024 |title=Northeastern network science professor Albert-László Barabási elected to National Academy of Sciences |url=https://news.northeastern.edu/2024/05/06/professor-elected-to-national-academy-of-sciences/ |access-date=2024-05-21 |website=Northeastern Global News |language=en-US}}</ref> Austrian Academy of Sciences (2024), Hungarian Academy of Sciences (2004), Academia Europaea (2007),<ref>[http://www.research.neu.edu/news/?id=62 "Northeastern Physicist Albert-László Barabási Receives Prestigious Honor for Exemplary Contributions to Interdisciplinary Science"] {{Webarchive|url=https://web.archive.org/web/20160826130409/http://www.research.neu.edu/news/?id=62|date=August 26, 2016}}, Northeastern University website; accessed January 10, 2016.</ref> European Academy of Sciences and Art (2018), Romanian Academy of Sciences<ref>{{Cite web |title=Comunicat de presă - Academia Română – AGERPRES |url=https://www1.agerpres.ro/comunicate/2018/06/28/comunicat-de-presa-academia-romana-12-47-00}}</ref> (2018) and the Massachusetts Academy of Sciences (2013). He was elected Fellow of the American Physical Society (2003),<ref>{{cite web |title=APS Fellow Archive |url=https://www.aps.org/programs/honors/fellowships/archive-all.cfm?initial=&year=2003&unit_id=&institution= |access-date=15 September 2020 |publisher=APS}}</ref> of the American Association for the Advancement of Science (2011), of the [https://netscisociety.net/home Network Science Society] (2021). He was awarded a Doctor Honoris Causa by Obuda University (2023) in Hungary, the Technical University of Madrid<ref>[http://www.etsit.upm.es/arbol-de-noticias.html?tx_ttnews%5Btt_news%5D=499] {{webarchive|url=https://web.archive.org/web/20120108150116/http://www.etsit.upm.es/arbol-de-noticias.html?tx_ttnews%5Btt_news%5D=499|date=January 8, 2012}}</ref> (2011), Utrecht University<ref>{{Cite web |date=2018-03-27 |title=Honorary doctorate for Prof. Albert-László Barabási |url=https://www.uu.nl/en/news/honorary-doctorate-for-prof-albert-laszlo-barabasi |access-date=2019-04-17 |website=Utrecht University |language=en}}</ref> (2018) and West University of Timișoara (2020).<ref>{{Cite web |date=September 30, 2020 |title=Scientiarum of God Prof. Dr. Albert – Lászlò Barabási |url=https://www.uvt.ro/en/doctor-honoris-causa/scientiarum-domnului-prof-dr-albert-laszlo-barabasi/}}</ref>

He received the Bolyai Prize from the Hungarian Academy of Sciences (2019), the [https://cssociety.org/community/awards/senior-scientific-award Senior Scientific Award] of the [https://cssociety.org/home Complex Systems Society] (2017) for "setting the basis of what is now modern Network Science",<ref>{{Cite web |title=CSS Awards |url=https://cssociety.org/community/css-awards |access-date=2019-04-17 |website=cssociety.org}}</ref> the Lagrange Prize (2011) C&C Prize (2008) Japan "for stimulating innovative research on networks and discovering that the scale-free property is a common feature of various real-world complex networks"<ref>{{cite web |title=NEC C&C Foundation |url=http://www.candc.or.jp/en/2008/ceremony.html |access-date=2016-01-11 |website=Candc.or.jp}}</ref> and the Cozzarelli Prize, National Academies of Sciences (USA),<ref>{{cite web |date=February 23, 2009 |title=PNAS announces 2008 Cozzarelli Prize recipients |url=http://www.eurekalert.org/pub_releases/2009-02/potn-pa2022309.php |access-date=2016-01-11 |work=EurekAlert! |archive-date=April 3, 2016 |archive-url=https://web.archive.org/web/20160403020621/http://www.eurekalert.org/pub_releases/2009-02/potn-pa2022309.php |url-status=dead }}</ref> John von Neumann Medal (2006) awarded by the John von Neumann Computer Society from Hungary, for outstanding achievements in computer-related science and technology<ref>{{cite web |title=Barabasi co edits new book and is awarded computing medal |url=http://www.nd.edu/~lumen/2006_09/Barabasicoeditsnewbookandisawardedcomputingmedal.shtml |archive-url=https://web.archive.org/web/20160303170710/http://www3.nd.edu/~lumen/2006_09/Barabasicoeditsnewbookandisawardedcomputingmedal.shtml |archive-date=March 3, 2016 |access-date=January 11, 2016 |website=Nd.edu |df=mdy-all}}</ref> and the FEBS Anniversary Prize for Systems Biology (2005).

In 2021, Barabási was ranked 2nd in the world in a ranking of the world's best engineering and technology scientists, based on their h-index.<ref>{{Cite web |title=Research.com - Leading Academic Research Portal |url=https://research.com/scientists-rankings/engineering-and-technology |access-date=2022-03-30 |website=Research.com |language=en}}</ref>

==Selected publications== * Barabási, Albert-László, ''The Formula: The Universal Laws of Success'', November 6, 2018; {{ISBN|0-316-50549-8}} (hardcover) *{{Cite book|title=Network science|last=Barabási|first=Albert-László|publisher=Cambridge University Press|year=2018|isbn=978-1-107-07626-6}} * Barabási, Albert-László, ''Bursts: The Hidden Pattern Behind Everything We Do'', April 29, 2010; {{ISBN|0-525-95160-1}} (hardcover) * Barabási, Albert-László, ''Linked: The New Science of Networks'', 2002. {{ISBN|0-452-28439-2}} (pbk) * Barabási, Albert-László and Réka Albert, "Emergence of scaling in random networks", ''Science'', 286:509–512, October 15, 1999 * Barabási, Albert-László and Zoltán Oltvai, "Network Biology", ''Nature Reviews Genetics'' 5, 101–113 (2004) * Barabási, Albert-László, Mark Newman and Duncan J. Watts, ''The Structure and Dynamics of Networks'', 2006; {{ISBN|0-691-11357-2}} * Barabási, Albert-László, Natali Gulbahce, and Joseph Loscalzo, "Network Medicine", ''Nature Reviews Genetics'' 12, 56–68 (2011) * {{Cite journal|author1=Réka Albert, Hawoong Jeong |author2=Barabási, Albert-László |name-list-style=amp |title=The Diameter of the WWW|journal=Nature|volume=401|issue=6749|pages=130–31|year=1999|arxiv=cond-mat/9907038|doi=10.1038/43601|bibcode=1999Natur.401..130A|s2cid=4419938 }} *Y.-Y. Liu, J.-J. Slotine, A.-L. Barabási, "Controllability of complex networks", ''Nature'' 473, 167–173 (2011) *Y.-Y. Liu, J.-J. Slotine, A.-L. Barabási, "Observability of complex systems", ''Proceedings of the National Academy of Sciences'' 110, 1–6 (2013) *Baruch Barzel and A.-L. Barabási, "Universality in Network Dynamics", ''Nature Physics'' 9, 673–681 (2013) *Baruch Barzel and A.-L. Barabási, "Network link prediction by global silencing of indirect correlations", ''Nature Biotechnology'' 31, 720–725 (2013) *B. Barzel Y.-Y. Liu and A.-L. Barabási, "Constructing minimal models for complex system dynamics", ''Nature Communications'' 6, 7186 (2015). *J. Gao, B. Barzel, A.-L, Barabási, "Universal resilience patterns in complex networks". ''Nature'' 530(7590):307-12 (2016).

==References== {{Reflist}}

==External links== *[http://barabasilab.com Albert-László Barabási professional website] *[https://scholar.google.com/citations?user=vsj2slIAAAAJ&hl=en&oi=ao Research Publications] *[http://www.barabasilab.com Profile], Center for Complex Network Research *[https://web.archive.org/web/20071030200237/http://www.physics.neu.edu/Department/Vtwo/faculty/barabasi.htm Profile], Northeastern University website *[http://ccsb.dfci.harvard.edu Profile] {{Webarchive|url=https://web.archive.org/web/20110728013835/http://ccsb.dfci.harvard.edu/ |date=July 28, 2011 }}, Center for Cancer Systems Biology website *[https://web.archive.org/web/20050304041427/http://www.nd.edu/~alb/ Profile], University of Notre Dame website *{{Google Scholar id|vsj2slIAAAAJ&hl}}

{{Authority control}}

{{DEFAULTSORT:Barabasi, Albert-Laszlo}} Category:1967 births Category:Living people Category:American people of Hungarian-Romanian descent Category:21st-century American physicists Category:21st-century Hungarian physicists Category:Romanian physicists Category:Members of the Hungarian Academy of Sciences Category:Complex systems scientists Category:Northeastern University faculty Category:University of Notre Dame faculty Category:Boston University Graduate School of Arts & Sciences alumni Category:University of Bucharest alumni Category:Romanian people of Hungarian descent Category:People from Harghita County Category:Members of Academia Europaea Category:Probability theorists Category:Harvard Medical School faculty Category:Fellows of the American Physical Society Category:Network scientists Category:Statistical physicists Category:Hungarian physicists