Albert-László Barabási
Barabási at the World Economic Forum Annual Meeting of the New Champions in 2012
Born
Barabási Albert László

(1967-03-30) March 30, 1967
Cârța, Harghita County, Romania
Citizenship
Romanian
Hungarian
American
Alma materUniversity of Bucharest (BS)
Eötvös Loránd University (MS)
Boston University (PhD)
Known forResearch of network science
The concept of scale-free networks
Proposal of Barabási–Albert model
Founder of Network Medicine
Introducing Network controllability
Awards
Scientific career
FieldsPhysics, Network Science, Network Medicine
ThesisGrowth and roughening of non-equilibrium interfaces (1994)
Doctoral advisorH. Eugene Stanley
Doctoral students
Websitebarabasilab.com

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

He is a distinguished university professor and Robert Gray Professor of Network Science at Northeastern University, and holds appointments at the department of medicine, Harvard Medical School and the department of network and data science[1] at Central European University. He is the former Emil T. Hofmann Professor of Physics at the University of Notre Dame and former associate member of the Center of Cancer Systems Biology (CCSB) at the Dana–Farber Cancer Institute, Harvard University.

He discovered in 1999 the concept of scale-free networks and proposed the Barabási–Albert model to explain their widespread emergence in natural, technological and social systems, from the cellular telephone to the World Wide Web or online communities. He is the founding president of the Network Science Society,[2] which sponsors the flagship NetSci Conference series held since 2006.

Birth and education

Barabási was born 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.[3] He attended a high school specializing in science and mathematics; in the tenth grade, he won a local physics olympiad. Between 1986 and 1989, he studied physics and engineering at the University of Bucharest; during that time, he began doing research on chaos theory, publishing three papers.[3]

In 1989, Barabási emigrated to Hungary, together with his father. In 1991, he received a master's degree at Eötvös Loránd University in Budapest, under Tamás Vicsek, before enrolling in the Physics program at Boston University, where he earned a PhD in 1994. His thesis, written under the direction of H. Eugene Stanley,[4] was published by Cambridge University Press under the title Fractal Concepts in Surface Growth.[5][6]

Academic career

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 2005–06 he was a visiting professor at Harvard University. In fall 2007, Barabási left Notre Dame to become the distinguished professor and director of the Center for Network Science at Northeastern University and to take up an appointment in the department of medicine at Harvard Medical School.

As of 2008, Barabási holds Hungarian, Romanian and U.S. citizenship.[7][8][9]

Research and achievements

Barabási has been a major contributor to the development of network science, the statistical physics of complex systems and network medicine.

Scale-Free Networks

He is best know for the discovery of the scale-free networks. He reported the scale-free nature of the WWW in 1999[10] and the same year, in a Science paper with Réka Albert, he proposed the Barabási–Albert model, predicting that growth and preferential attachment are jointly responsible for the emergence of the scale-free property in real networks. According to the review of one of Barabási's books, preferential attachment can be described as follows:

Barabási has found that the websites that form the network (of the WWW) have certain mathematical properties. The conditions for these properties to occur are threefold. The first is that the network has to be expanding, growing. This precondition of growth is very important as the idea of emergence comes with it. It is constantly evolving and adapting. That condition exists markedly with the world wide web. The second is the condition of preferential attachment, that is, nodes (websites) will wish to link themselves to hubs (websites) with the most connections. The third condition is what is termed competitive fitness which in network terms means its rate of attraction.[11]

He subsequently showed that the scale-free property emerges in biological systems, namely in metabolic networks[12] and protein–protein interaction[13] networks. Science celebrated the ten-year anniversary of Barabási’s 1999 discovery by devoting a special issue to Complex Systems and Networks in 2009.[14][15]

Network Robustness

In a 2001 paper with Réka Albert and Hawoong Jeong he demonstrated the Achilles' heel property of scale-free networks, showing that such networks are robust to random failures but fragile to attacks.[16] Specifically, they showed that networks can easily survive the random failure of a very large number of nodesl showing a remarkable robustness to failures. At the same time, networks can quickly collapse under attack, achieved by removing the biggest hubs. The threshold characterizing the breakdown of a network under random failures was linked[17] 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. The calculations also showed that robustness to random failures is not limited to scale-free networks, but it is a general property of most real networks with a wide range of node degrees.

Network Medicine

Barabási is one of the founders of network medicine, a term he coined in an article entitled "Network Medicine – From Obesity to the "Diseasome", published in The New England Journal of Medicine, in 2007.[18] His work introduced the concept of diseasome, or disease network,[19] showing that diseases are connected through shared genes, capturing their common genetic roots. He subsequently pioneered the use of large patient data, linking the roots of disease comorbidity to molecular networks.[20] A key concept of network medicine is Barabási's discovery that genes associated with the same disease are located in the same network neighborhood,[21] which led to the concept of disease module, currently used to aid drug discovery, drug design, and the development of biomarkers, as he outlined in 2012 in a TEDMED talk.[22] Barabási's work has led to the founding of 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,[23] predicting a novel mechanism of action for rosmarinic acid,[24] and novel therapeutic functions of existing drugs (drug repurposing).[25] The products of network medicine have reached the clinic, helping doctors decide if rheumatoid arthritis patients respond to anti-TNF therapy.[26][27] 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.[28][29]

Human Dynamics

Barabási in 2005 discovered the fat tailed nature of the inter event 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. Such bursty patterns have been subsequently discovered in a wide range of processes, from web browsing to email communications. He proposed the Barabási model[30] of human dynamics, 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.[31]


Human Mobility

Barabási laid foundational work in understanding individual human mobility patterns through a series of influential papers. In his 2008 Nature publication,[32] Barabási utilized anonymized mobile phone data to analyze human mobility, challenging the existing random walk models. He discovered that human movements exhibit 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,[33] Barabási explored the predictability of human dynamics by analyzing mobile phone user trajectories. Contrary to expectations, he found a high predictability of 93% in human movements across all users, with individual predictability rarely dropping below 80%. He then introduced two principles underlying human trajectories, leading to the development of a microscopic model for individual mobility.[34] This model, consistent with observed empirical scaling laws, provided analytical insights into key mobility pattern features. Remarkably, a decade before the COVID-19 pandemic, Barabási was able to predict the spreading patterns of a virus transmitted through direct contact.[35]

Network Control

His work on network controllability and observability asked the fundamental question of how large networks control themself. To answer this, he was the first to bring the tools of control theory to network science. His first work proposed a method to identify the nodes through which one can control a complex network, just like a car is controlled through three control points, the steering wheel, gas pedal and brake. He proposed the formalism of network controllability by mapping the control problem, widely studied in physics and engineering since Maxwell, into graph matching, a graph theoretic problem, merging statistical mechanics and control theory.[36] The exact mapping allowed him to develop tools to identify the system's control nodes. He used network control to predict the function of individual neurons in the Caenorhabditis elegans connectome, leading to the discovery of new neurons involved in the control of locomotion, and offering direct falsifiable experimental confirmation of network control principles.[37]

Awards

Barabási was the recipient of the 2023 Julius Edgar Lilienfeld Prize, one of the top prizes of the American Physical Society,[38] "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 Barabási received the EPS Statistical and Nonlinear Physics Prize, 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."

In 2021 Barabási was ranked 2nd in the world in the field of Engineering and Technology.[39]

In 2019 he received The Bolyai Prize from the Hungarian Academy of Sciences and in 2017 he received the Senior Scientific Award of the Complex Systems Society for "setting the basis of what is now modern Network Science".[40]

In 2011 he received the Lagrange Prize and in 2008 he received the C&C Prize, Japan "for stimulating innovative research on networks and discovering that the scale-free property is a common feature of various real-world complex networks"[41] and the Cozzarelli Prize, National Academies of Sciences (USA)[42]

In 2006 he was awarded the John von Neumann Medal by the John von Neumann Computer Society from Hungary, for outstanding achievements in computer-related science and technology.[43]

In 2005, he was awarded the FEBS Anniversary Prize for Systems Biology.

Barabási was elected a Fellow of the American Physical Society in 2003,[44] fellow of AAAS in 2011, Fellow of the Network Science Society in 2021.

In 2004, he was elected as an external member of the Hungarian Academy of Sciences, in 2007, he was inducted into the Academia Europaea, [45] in 2013 he was elected as fellow of the Massachusetts Academy of Sciences, in 2018 he was elected into the European Academy of Arts and Sciences, and in 2018 was elected member of the Romanian Academy of Sciences.[46]

In 2023 he was awarded a Doctor Honoris Causa by Obuda University in Hungary, in 2011 by the Technical University of Madrid,[47] in 2018 by Utrecht University[48] and University of West Timisoara.[49]

Selected publications

  • Barabási, Albert-László, The Formula: The Universal Laws of Success, November 6, 2018; ISBN 0-316-50549-8 (hardcover)
  • Barabási, Albert-László (2018). Network science. Cambridge University Press. ISBN 978-1107076266.
  • 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)
  • Réka Albert, Hawoong Jeong & Barabási, Albert-László (1999). "The Diameter of the WWW". Nature. 401 (6749): 130–31. arXiv:cond-mat/9907038. Bibcode:1999Natur.401..130A. doi:10.1038/43601. 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)

References

  1. ↑ People at Center for Network Science, Central European University website; accessed January 10, 2016.
  2. ↑ "NetSci – the Network Science Society".
  3. 1 2 Keiger, Dale (November 24, 2008). "Looking for the Next Big Thing". Notre Dame Magazine.
  4. ↑ "H. Eugene Stanley: Ph.D. Theses Supervised". Polymer.bu.edu. Retrieved January 11, 2016.
  5. ↑ Albert-László Barabási at the Mathematics Genealogy Project
  6. ↑ Albert-Laszlo Barabasi, Eugene H Stanley (1995). Fractal Concepts in Surface Growth. Cambridge University Press. ISBN 9780511599798.
  7. ↑ "Albert-László Barabási CV" (PDF). Archived from the original (PDF) on March 3, 2016. Retrieved January 10, 2016.
  8. ↑ "ETSI de Telecomunicación: ALBERT LASZLÓ BARABÁSI". www.etsit.upm.es. Retrieved November 15, 2020.
  9. ↑ "Albert-László Barabási – Khoury College of Computer Sciences". Retrieved November 15, 2020.
  10. ↑ Albert, Réka; Jeong, Hawoong; Barabási, Albert-László (September 1999). "Diameter of the World-Wide Web". Nature. 401 (6749): 130–131. arXiv:cond-mat/9907038. Bibcode:1999Natur.401..130A. doi:10.1038/43601. S2CID 4419938.
  11. ↑ Profile Archived March 9, 2005, at the Wayback Machine, sociopranos.com; accessed 10 January 2016.
  12. ↑ Jeong, H.; Tombor, B.; Albert, R.; Oltvai, Z. N.; Barabási, A.-L. (October 2000). "The large-scale organization of metabolic networks". Nature. 407 (6804): 651–654. arXiv:cond-mat/0010278. Bibcode:2000Natur.407..651J. doi:10.1038/35036627. PMID 11034217.
  13. ↑ Jeong, H.; Mason, S. P.; Barabási, A.-L.; Oltvai, Z. N. (May 2001). "Lethality and centrality in protein networks". Nature. 411 (6833): 41–42. arXiv:cond-mat/0105306. Bibcode:2001Natur.411...41J. doi:10.1038/35075138. PMID 11333967.
  14. ↑ Barabási, Albert-László (July 24, 2009). "Scale-Free Networks: A Decade and Beyond". Science. 325 (5939): 412–413. Bibcode:2009Sci...325..412B. doi:10.1126/science.1173299. PMID 19628854. S2CID 43910070.
  15. ↑ Jasny, Barbara R.; Zahn, Laura M.; Marshall, Eliot (July 24, 2009). "Connections". Science. 325 (5939): 405. Bibcode:2009Sci...325..405J. doi:10.1126/science.325_405. PMID 19628849.
  16. ↑ Barabási, Albert-László (2016). Network science. Cambridge, United Kingdom. ISBN 978-1-107-07626-6.{{cite book}}: CS1 maint: location missing publisher (link)
  17. ↑ Cohen, Reuven; Erez, Keren; Ben-Avraham, Daniel; Havlin, Shlomo (2000). "Resilience of the Internet to Random Breakdowns". Physical Review Letters. 85 (21): 4626–4628. arXiv:cond-mat/0007048. Bibcode:2000PhRvL..85.4626C. doi:10.1103/PhysRevLett.85.4626. PMID 11082612. S2CID 15372152.
  18. ↑ Barabási, Albert-László (July 26, 2007). "Network Medicine — From Obesity to the 'Diseasome'". New England Journal of Medicine. 357 (4): 404–407. doi:10.1056/NEJMe078114. PMID 17652657.
  19. ↑ Goh, Kwang-Il; Cusick, Michael E.; Valle, David; Childs, Barton; Vidal, Marc; Barabási, Albert-László (2007). "The human disease network". Proceedings of the National Academy of Sciences. 104 (21): 8685–8690. Bibcode:2007PNAS..104.8685G. doi:10.1073/pnas.0701361104. PMC 1885563. PMID 17502601.
  20. ↑ Barabási, Albert-László; Gulbahce, Natali; Loscalzo, Joseph (January 2011). "Network medicine: a network-based approach to human disease". Nature Reviews Genetics. 12 (1): 56–68. doi:10.1038/nrg2918. PMC 3140052. PMID 21164525.
  21. ↑ Menche, J.; Sharma, A.; Kitsak, M.; Ghiassian, S. D.; Vidal, M.; Loscalzo, J.; Barabasi, A.-L. (February 20, 2015). "Uncovering disease-disease relationships through the incomplete interactome". Science. 347 (6224): 1257601. doi:10.1126/science.1257601. PMC 4435741. PMID 25700523.
  22. ↑ Do your proteins have their own social network?, retrieved November 1, 2022
  23. ↑ Sharma, Amitabh; Menche, Jörg; Huang, C. Chris; Ort, Tatiana; Zhou, Xiaobo; Kitsak, Maksim; Sahni, Nidhi; Thibault, Derek; Voung, Linh; Guo, Feng; Ghiassian, Susan Dina; Gulbahce, Natali; Baribaud, Frédéric; Tocker, Joel; Dobrin, Radu; Barnathan, Elliot; Liu, Hao; Panettieri, Reynold A.; Tantisira, Kelan G.; Qiu, Weiliang; Raby, Benjamin A.; Silverman, Edwin K.; Vidal, Marc; Weiss, Scott T.; Barabási, Albert-László (June 2015). "A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma". Human Molecular Genetics. 24 (11): 3005–3020. doi:10.1093/hmg/ddv001. PMC 4447811. PMID 25586491.
  24. ↑ do Valle, Italo F.; Roweth, Harvey G.; Malloy, Michael W.; Moco, Sofia; Barron, Denis; Battinelli, Elisabeth; Loscalzo, Joseph; Barabási, Albert-László (March 19, 2021). "Network medicine framework shows that proximity of polyphenol targets and disease proteins predicts therapeutic effects of polyphenols". Nature Food. 2 (3): 143–155. doi:10.1038/s43016-021-00243-7. PMID 37117448. S2CID 232317723.
  25. ↑ Cheng, Feixiong; Desai, Rishi J.; Handy, Diane E.; Wang, Ruisheng; Schneeweiss, Sebastian; Barabási, Albert-László; Loscalzo, Joseph (July 12, 2018). "Network-based approach to prediction and population-based validation of in silico drug repurposing". Nature Communications. 9 (1): 2691. Bibcode:2018NatCo...9.2691C. doi:10.1038/s41467-018-05116-5. PMC 6043492. PMID 30002366.
  26. ↑ Cohen, Stanley; Wells, Alvin F.; Curtis, Jeffrey R.; Dhar, Rajat; Mellors, Theodore; Zhang, Lixia; Withers, Johanna B.; Jones, Alex; Ghiassian, Susan D.; Wang, Mengran; Connolly-Strong, Erin; Rapisardo, Sarah; Gatalica, Zoran; Pappas, Dimitrios A.; Kremer, Joel M.; Saleh, Alif; Akmaev, Viatcheslav R. (September 2021). "A Molecular Signature Response Classifier to Predict Inadequate Response to Tumor Necrosis Factor-α Inhibitors: The NETWORK-004 Prospective Observational Study". Rheumatology and Therapy. 8 (3): 1159–1176. doi:10.1007/s40744-021-00330-y. PMC 8214458. PMID 34148193.
  27. ↑ Ghiassian, Susan D; Voitalov, Ivan; Withers, Johanna B; Santolini, Marc; Saleh, Alif; Akmaev, Viatcheslav R (August 2022). "Network-based response module comprised of gene expression biomarkers predicts response to infliximab at treatment initiation in ulcerative colitis". Translational Research. 246: 78–86. doi:10.1016/j.trsl.2022.03.006. PMID 35306220. S2CID 247514416.
  28. ↑ Morselli Gysi, Deisy; do Valle, Ítalo; Zitnik, Marinka; Ameli, Asher; Gan, Xiao; Varol, Onur; Ghiassian, Susan Dina; Patten, J. J.; Davey, Robert A.; Loscalzo, Joseph; Barabási, Albert-László (May 11, 2021). "Network medicine framework for identifying drug-repurposing opportunities for COVID-19". Proceedings of the National Academy of Sciences. 118 (19). arXiv:2004.07229. Bibcode:2021PNAS..11825581M. doi:10.1073/pnas.2025581118. PMC 8126852. PMID 33906951.
  29. ↑ Patten, J.J.; Keiser, Patrick T.; Morselli-Gysi, Deisy; Menichetti, Giulia; Mori, Hiroyuki; Donahue, Callie J.; Gan, Xiao; Valle, Italo do; Geoghegan-Barek, Kathleen; Anantpadma, Manu; Boytz, RuthMabel; Berrigan, Jacob L.; Stubbs, Sarah H.; Ayazika, Tess; O’Leary, Colin (September 2022). "Identification of potent inhibitors of SARS-CoV-2 infection by combined pharmacological evaluation and cellular network prioritization". iScience. 25 (9): 104925. Bibcode:2022iSci...25j4925P. doi:10.1016/j.isci.2022.104925. PMC 9374494. PMID 35992305.
  30. ↑ A.-L. Barabási (2005). "The origin of bursts and heavy tails in human dynamics". Nature. 435 (7039): 207–11. arXiv:cond-mat/0505371. Bibcode:2005Natur.435..207B. doi:10.1038/nature03459. PMID 15889093. S2CID 4419475.
  31. ↑ Barabási, Albert-László (2010). Bursts : the hidden pattern behind everything we do. New York, N.Y.: Dutton. ISBN 978-0-525-95160-5. OCLC 426800811.
  32. ↑ González, Marta C.; Hidalgo, César A.; Barabási, Albert-László (June 2008). "Understanding individual human mobility patterns". Nature. 453 (7196): 779–782. arXiv:0806.1256. Bibcode:2008Natur.453..779G. doi:10.1038/nature06958. PMID 18528393. S2CID 4419468.
  33. ↑ Song, Chaoming; Qu, Zehui; Blumm, Nicholas; Barabási, Albert-László (February 19, 2010). "Limits of Predictability in Human Mobility". Science. 327 (5968): 1018–1021. Bibcode:2010Sci...327.1018S. doi:10.1126/science.1177170. PMID 20167789. S2CID 13847306.
  34. ↑ Song, Chaoming; Koren, Tal; Wang, Pu; Barabási, Albert-László (October 2010). "Modelling the scaling properties of human mobility". Nature Physics. 6 (10): 818–823. arXiv:1010.0436. Bibcode:2010NatPh...6..818S. doi:10.1038/nphys1760.
  35. ↑ Wang, Pu; González, Marta C.; Hidalgo, César A.; Barabási, Albert-László (May 22, 2009). "Understanding the Spreading Patterns of Mobile Phone Viruses". Science. 324 (5930): 1071–1076. arXiv:0906.4567. Bibcode:2009Sci...324.1071W. doi:10.1126/science.1167053. PMID 19342553.
  36. ↑ Liu, Yang-Yu; Slotine, Jean-Jacques; Barabási, Albert-László (2011). "Controllability of complex networks". Nature. 473 (7346): 167–173. Bibcode:2011Natur.473..167L. doi:10.1038/nature10011. PMID 21562557. S2CID 4334171.
  37. ↑ Yan, Gang; Vértes, Petra E.; Towlson, Emma K.; Chew, Yee Lian; Walker, Denise S.; Schafer, William R.; Barabási, Albert-László (October 2017). "Network control principles predict neuron function in the Caenorhabditis elegans connectome". Nature. 550 (7677): 519–523. Bibcode:2017Natur.550..519Y. doi:10.1038/nature24056. PMC 5710776. PMID 29045391.
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  40. ↑ "CSS Awards". cssociety.org. Retrieved April 17, 2019.
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  42. ↑ "PNAS announces 2008 Cozzarelli Prize recipients". EurekAlert!. February 23, 2009. Retrieved January 11, 2016.
  43. ↑ "Barabasi co edits new book and is awarded computing medal". Nd.edu. Archived from the original on March 3, 2016. Retrieved January 11, 2016.
  44. ↑ "APS Fellow Archive". APS. Retrieved September 15, 2020.
  45. ↑ "Northeastern Physicist Albert-László Barabási Receives Prestigious Honor for Exemplary Contributions to Interdisciplinary Science" Archived August 26, 2016, at the Wayback Machine, Northeastern University website; accessed January 10, 2016.
  46. ↑ "Comunicat de presă - Academia Română – AGERPRES".
  47. ↑ Archived January 8, 2012, at the Wayback Machine
  48. ↑ "Honorary doctorate for Prof. Albert-László Barabási". Utrecht University. March 27, 2018. Retrieved April 17, 2019.
  49. ↑ "Scientiarum of God Prof. Dr. ALBERT – LÁSZLÒ BARABÁSI". September 30, 2020.
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