A study of 19 metro-area bus systems worldwide, serving 4 billion yearly riders, shows mathematically similar solutions across cities for setting bus frequency given different levels of demand for different routes and resource constraints. In PNAS: https://t.co/kGDAHzyreV
Postdoc openings at Kellogg/Northwestern!
We’re a purposefully multidisciplinary group working at the intersection of science-of-science, innovation, AI, networks, and complexity. We’re looking for postdocs who want to ask bold new questions, with rigorous data, theory, and computation.
Candidates from all disciplines are welcome. This year we’re especially excited about candidates interested in one or more of the following areas:
- LLMs & AI agents
- Political science (science, policy & governance)
- Technological progress + societal impacts of science
- Nonequilibrium statistical physics
Review begins Feb 15 (rolling until filled).
Apply / details:https://t.co/tmIoh1ypLU
Please share with great candidates! Thank you!
Join us!!!
Now hiring postdoc scholars🚀 Interested in candidates whose work aligns with
• LLMs & AI agents
• Science, policy & governance
• Technological progress & societal impact
• Nonequilibrium statistical physics
Review begins Feb 15 (rolling).
Apply: https://t.co/lm5j9FcDPw
Kellogg is launching the Northwestern Innovation Institute with a $25M gift from Pin Ni and Future Wanxiang Foundation! The institute will examine how innovation occurs across science, technology, and business. Learn more in the full news story: https://t.co/IwsMmi2m5g
Today in @Nature, I laid out our vision of using AI to help universities maximize their research impacts.
Key Q: Can we use data and AI tools to help a university locate key ideas and personnel to maximize its impact and accelerate progress?
https://t.co/s8ITQsC9jS
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Excited to share our latest work, "Symmetry breaking in optimal transport networks," just out in @Naturecomms! 🚀 This was a fantastic collaboration with @filrad, @santo, @siragerkol, and Marc. Here's a short thread summarizing our main findings! 1/8
.@Sid_Patwardhan_@filrad@santo_fortunato@siragerkol propose analytical and computational frameworks to analyze sharp transitions from symmetric to asymmetric shapes in optimal networks. https://t.co/Lv7kuX4Nr5
The best subway line that one can build with a fixed budget could be one serving only half of the population! Check out our paper just out in @NatureComms. @filrad@Sid_Patwardhan_@siragerkol@IULuddy https://t.co/pPZMIMyHzR
Seeking exceptional post-doctoral fellow candidates 🚀 We have a broadly defined research agenda, exploring diverse topics related to the science of science, innovation, AI, computational social science and network science. Apply now at https://t.co/aEWJhU23dd
Proud of my first publication with @DanKaiser37 and @Sid_Patwardhan_ Phys. Rev. E 107, 024309 (2023) - Multiplex reconstruction with partial information https://t.co/ugEjaElf1H
Have fun with our portal (https://t.co/GqNXqdbq1d), a tool to compute metrics of individual scientific excellence, including our own E-index. Find in which percentile of your field(s) you are. Compare yourself with someone else!
@filrad @satyaki30 @siragerkol@IULuddy@IUNetSci
Our @OSoMe_IU team just launched the US #Midterm#Elections 2022 #dashboard. See the top websites, hashtags, images, & accounts disseminating election content across Twitter, Facebook, and Instagram (more platforms to be added later). Check it out at https://t.co/olK6GSMvez
We propose E-index, a measure to quantify the high-quality production consistency of scientists. E-index works best at finding scientists with successful careers.
The secret of successful careers in science is consistency! Take a look at our paper and at the E-index, an indicator of excellence in science!
https://t.co/rtafVdpScs @filrad @satyaki30 @siragerkol
Our work with @filrad analyzing the submodularity property in the context of influence maximization on temporal networks is out in @PhysRevE
https://t.co/S2233KxRi6
Comparing to exact solutions, greedy algorithm proves to be an effective method for influence maximization on temporal networks even though the influence function is not submodular.