Advanced Network Laboratory (ANL) at Shanghai Jiao Tong University was established in the spring of 2011 with 5 active faculty advisors, currently having 24 graduated doctorates or masters and more than 40 postgraduates. The mission of the lab is to conduct original research in various communication networks with an emphasis on research contributions and impact. Along this goal, we have identified a few exciting research topics from theoretical hardcore problems to real-word applications including distributed network and data processing, wireless network structure and optimization, wireless networks and mobile computing, the Internet of Things and sensor networks, game theory algorithms and applications. Current research projects have been funded by many sponsors including the National Science Foundation (NSF) of China, the Ministry of Education in China, the Ministry of Science Technology in China, and Shanghai Municipal Government. During the six years since the establishment, we have published hundreds of papers in well-known international journals and have won the best paper awards from many influential conferences such as ICNP, DASFAA and ICPADS. Because of our excellent contributions, we have won the first prize of natural science of Ministry of Education.
The Grid P2P Sensor (GPS) is a research group belonging to State Key Laboratory for Novel Software Technology and the Department of Computer Science and Technology at Nanjing University led by distinguished Prof. Guihai Chen. Our research interests are centered around distributed computing, Internet of things, mobile computing, data mining and data centers, with the larger goal of making current and future networks easier to design, understand and operate. We are currently active in multiple areas including wireless charging, smartphone, routing and network update. Most of our projects are inherently tend to involve recent advances in approximation algorithm, combinatorial optimization, convex optimization and probability analysis. We published more than 300 papers in peer reviewed journals such as ACM/IEEE Transactions on Networks, IEEE Journal on Selected Areas in Communications, IEEE Transactions on Services Computing, IEEE Transactions on Parallel & Distributed Systems, IEEE Transactions on Mobile Computing, IEEE Transactions onKnowledge and Data Engineering, ACM Transactions on Sensor Networks, etc., and well known conference proceedings such as SIGMETRICS, VLDB, MOBIHOC, INFOCOM, ICPP, ICDCS, ICNP, IPSN, AAAI, HPCA, etc. We received the best paper award from MOBICOM 2009, ICCS2014, AAMAS 2014, ICNP 2015, ICPADS 2016, CloudComp 2016, DSAFA 2017, INFOCOM 2017.
Aiming to facilitate interdisciplinary communication and development as well as foster top interdisciplinary talents, the Research Institute for Interdisciplinary Sciences (RIIS) is born. RIIS has an outstanding faculty team, with more than ten Ph.D.'s from renowned Chinese and international universities, such as Stanford University. RIIS is an umbrella institute hosting five research organizations, namely Research Center for Management Science and Information Analytics, The LEAVES International Parallel Computing Optimization Lab(LEAVES), Research Center for FinTech, Research Center for Artificial Intelligence, and Research Center for Sharing Economy. In addition, RIIS plans to launch a MD-PhD joint program with University of Minnesota. Together with School of Information Management and Engineering, RIIS will start a pilot project, and will be devoted to top-talent cultivation.
Cardinal Operations is a unique big-data decision company in China. Founded by five Stanford professor and PhDs, and with a team of world-class decision making experts and data scientists, Cardinal Operations aims at using big data to provide solutions for firms under complex decision scenarios. Different from many other "big data" companies, we try to close the loop in the decision chain in the era of big data - from data collection, pattern analysis, all the way to the final decision. Particularly, with the decision making experts and the state-of-the-art models and algorithms, we fill the gap of translating the results from data analysis to executable decision, making the most use of data to create value for companies.
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