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Milan Janosov | |
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Born | 1991 |
Nationality | Hungary |
Education | Eötvös Loránd University, Central European University, Barabási Lab, Bell Labs |
Occupation | Network scientist |
Known for | Network science, data science, geospatial data science, computational social science, NFT trading, data visualization, digital art |
Awards | Scholarship of the Republic of Hungary |
Milan Janosov is a Hungarian data scientist, researcher, entrepreneur, self-published author, and online educator specializing in network science and geospatial data analysis. He is the founder of Geospatial Data Consulting[1].
Education
[edit]Milan Janosov earned his bachelor's degree in physics and biophysics from Eötvös Loránd University and completed his Ph.D.[2] in network and data science at Central European University.[3] in 2020. During his studies, he conducted research at the Barabási Lab[4] in Boston and Bell Labs in Cambridge, focusing on data-driven approaches and network science.
Career
[edit]Milan Janosov is a data scientist and researcher specializing in network science and data science, with a background in physics and biophysics.[5] He earned his PhD in network and data science in 2020, conducting research at institutions including Eötvös Loránd University, Central European University in Budapest, the Barabási Lab in Boston, and Bell Labs in Cambridge.
In 2020, Janosov was named to the Forbes 30 Under 30[6] list and was included in Data Science Connect’s "99 Data Influencers to Follow" list in 2023. His work spans academia, data science, and entrepreneurship. He is the founder of Geospatial Data Consulting and has held roles such as Chief Data Scientist at several startups focused on location intelligence. Janosov has also worked as a research affiliate at Central European University, a research expert for the European Commission, and a senior data scientist at Maven7.
Janosov is an active contributor to data science communities, regularly writing for platforms such as Towards Data Science[7] and the Data Visualization Society[8]. He has authored two books, Geospatial Data Science Essentials[9] and Connecting the Dots[10], both of which are self-published work, available on Amazon. Additionally, he serves as a data science instructor for LinkedIn Learning.[11]
Throughout his career, Janosov has received multiple academic awards, including the Scholarship of the Republic of Hungary[12] three times, and has been recognized at various science competitions. His work has been referenced in various academic journals and media outlets such as Nature Social Science Research[13], New York Times[14], New Scientist[15],Times Higher Education[16], TechXplore[15], The Times, GQ[17], Futurism[18], Gamestar[19], and Phys.org[20].
His career focuses on applying network science, geospatial data, and computational approaches to real-world problems, with his work bridging the gap between cutting-edge research and impactful applications in diverse sectors.
Recent Publications
[edit]Vasan, K., Janosov, M., & Barabási, A. L. (2022). Quantifying NFT-driven networks in crypto art. Scientific reports, 12(1), 2769. [21]
Janosov, M., Battiston, F., & Sinatra, R. (2020). Success and luck in creative careers. EPJ Data Science, 9(1), 9. [22]
Janosov, M., Virágh, C., Vásárhelyi, G., & Vicsek, T. (2017). Group chasing tactics: how to catch a faster prey. New Journal of Physics, 19(5), 053003. [23]
Janosov, M., Musciotto, F., Battiston, F., & Iñiguez, G. (2020). Elites, communities and the limited benefits of mentorship in electronic music. Scientific reports, 10(1), 3136. [24]
Books
[edit]Connecting the Dots: How data, networks, and algorithms shape our world. 2024 November, New York. Self-published on Amazon. [25]
Geospatial Data Science Essentials: 101 Practical Python Tips and Tricks. 2024 July, Budapest. Self-published on Amazon. [26]
DATA - Így hálóznak be az adataid. 2023 August Budapest, published by Open Books [27]
References
[edit]- ^ "Geospatial Data Consulting". geospatialdataconsulting.com. Retrieved 2024-12-05.
- ^ Janosov, Milan (2020). Quantifying the Evolution of Success with Network and Data Science Tools (PDF) (PhD). Central European University. Retrieved 2024-12-05.
- ^ "Milan Janosov". Network and Data Science. Central European University. Retrieved 2024-12-05.
- ^ Vasan, Kaustav; Janosov, Milan; Barabási, Albert-László (2022). "Quantifying NFT-driven networks in crypto art". Scientific Reports. 12 (1): 2769. doi:10.1038/s41598-022-05146-6. PMC 8854720. PMID 35177628.
- ^ "Jánosov Milán – Forbes 30/30". Forbes (in Hungarian). Retrieved 2024-12-05.
- ^ "Milan Janosov: 30 Under 30". Forbes Hungary. 2020. Retrieved 2024-12-05.
- ^ Janosov, M. "Medium Profile". Medium. Retrieved 2024-12-05.
- ^ Janosov, M. "Author Profile". Nightingale DVS. Retrieved 2024-12-05.
- ^ Janosov, M. "Geospatial Data Science Essentials: 101 Practical Python Tips and Tricks". Amazon. Retrieved 2024-12-05.
- ^ Janosov, M. "Connecting the Dots". Connecting the Dots. Retrieved 2024-12-05.
- ^ https://www.linkedin.com/learning/geospatial-data-analytics-essential-training/analyzing-geospatial-data
- ^ "Milan Janosov – Portfolio Speaker". Portfolio.hu. Retrieved 2024-12-05.
- ^ Janosov, M.; Battiston, F.; Sinatra, R. (2020). "Success and luck in creative careers". Scientific Reports. 10 (1): 60055. doi:10.1038/s41598-020-60055-w. PMID 32081912.
- ^ New York Times. "NFTs and the Art Market". The New York Times. Retrieved 2024-12-05.
- ^ a b "Milan Janosov". DeepAI. Retrieved 5 December 2024.
Milan Janosov's work has been featured in media outlets including New Scientist, TechXplore, and others, showcasing his contributions to data science and network science.
- ^ Times Higher Education. "PhD student predicts who will die next in Game of Thrones". Retrieved 2024-12-05.
- ^ "Researcher Just Built an Algorithm to Predict Which Game of Thrones Character Will Die Next". GQ India. 2020-04-27. Retrieved 2024-12-05.
- ^ "A Researcher Just Made an Algorithm to Predict Which "Game of Thrones" Characters Will Die". Futurism. Retrieved 2024-12-05.
- ^ "Rendkívül látványosan ábrázolták a The Witcher szereplőinek kapcsolatait". GSplus. 2020-03-04. Retrieved 2024-12-05.
- ^ "Predators use faster prey and drone tactics to catch their target". Phys.org. 2017-05-09. Retrieved 2024-12-05.
- ^ Vasan, K.; Janosov, M.; Barabási, A. L. (2022). "Quantifying NFT-driven networks in crypto art". Scientific Reports. 12 (1): 2769. doi:10.1038/s41598-022-05146-6. PMC 8854720. PMID 35177628.
- ^ Janosov, M.; Battiston, F.; Sinatra, R. (2020). "Success and luck in creative careers". EPJ Data Science. 9 (1): 9. doi:10.1140/epjds/s13688-020-00227-w.
- ^ Janosov, M.; Virágh, C.; Vásárhelyi, G.; Vicsek, T. (2017). "Group chasing tactics: how to catch a faster prey". New Journal of Physics. 19 (5): 053003. doi:10.1088/1367-2630/aa69e7.
- ^ Janosov, M.; Musciotto, F.; Battiston, F.; Iñiguez, G. (2020). "Elites, communities and the limited benefits of mentorship in electronic music". Scientific Reports. 10 (1): 3136. doi:10.1038/s41598-020-60055-w.
- ^ Janosov, M. (2024). Connecting the Dots: How data, networks, and algorithms shape our world. New York: Self-published.
- ^ Janosov, M. (2024). Geospatial Data Science Essentials: 101 Practical Python Tips and Tricks. Budapest: Self-published.
- ^ Janosov, M. (2023). DATA - Így hálóznak be az adataid. Budapest: Open Books.