天美传媒

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James Hendler is the Director of the Future of Computing Institute; Tetherless World Professor of Computer, Web and Cognitive Sciences; and Director of the RPI-IBM Artificial Intelligence Research Collaboration. Hendler is a data scientist with specific interests in open government and scientific data, data science for healthcare, AI and machine learning, semantic data integration, and the use of data in government. One of the originators of the Semantic Web, he has authored over 450 books, technical papers, and articles in the areas of Open Data, the Semantic Web, artificial intelligence, and data policy and governance. He is also the former Chief Scientist of the Information Systems Office at the US Defense Advanced Research Projects Agency (DARPA) and was awarded a US Air Force Exceptional Civilian Service Medal in 2002. He is the first computer scientist ever to have served on the Board of Reviewing editors for Science. In 2010, Hendler was selected as an “Internet Web Expert” by the US government and helped in the development and launch of the US data.gov open data website. In 2013, he was appointed as the Open Data Advisor to New York State and in 2015 appointed a member of the US Homeland Security Science and Technology Advisory Committee. In 2016, became a member of the National Academies Board on Research Data and Information, in 2017 a member of the Director’s Advisory Committee of the National Security Directorate of PNNL, and in 2021 became chair of the ACM’s global Technology Policy Council. Hendler is a Fellow of the US National Academy of Public Administration, the AAAI, AAAS, ACM, BCS and IEEE.

Larry Fulton is an Associate Professor of Health Administration at Texas State University, San Marcos. He earned his Doctorate of Philosophy / Masters of Science in Statistics from the University of Texas at Austin, his Master of Health Administration from Baylor, and three other graduate degrees. Dr. Fulton is a Fellow of the American College of Healthcare Executives (FACHE) and maintains the credentials of Chartered Scientist and Chartered Statistician (CStat CSci) as a Fellow in the Royal Statistical Society. He is a Certified Analytics Professional (CAP) of the Institute for Operations Research & Management Science, a Certified Quality Engineer and Certified Six Sigma Black Belt (CQE CSSBB) of the American Society for Quality and a Professional Statistician (PStat) of the American Statistical Association.

Dr. Mark Esposito is recognized internationally as a top global thought leader in matters relating to The Fourth Industrial Revolution, the changes and opportunities that technology will bring to industry.

Mark has held numerous senior positions at prestigious Institutes. He has been a member of the teaching faculty at Harvard University鈥檚 Division of Continuing Education where he has taught Economic Strategy and Competitiveness. He also has served as a Co-Leader at the Institutes Council for the Microeconomics of Competitiveness program (MOC) at Harvard Business School. 

Besides being a Professor at Thunderbird/ASU, Mark has been a Professor of Business & Economics at Hult International Business School, globally. 

He is an appointed Research Fellow in the Circular Economy Center, at the University of Cambridge's Judge Business School.

He is also a Fellow for the Mohammed Bin Rashid School of Government in Dubai.

Mark is the Co-Founder and Chief Learning Officer of Nexus Frontier Tech, an AI Studio, dedicated to the productions of AI solutions. 

He is a prolific author and his articles can be found on ResearchGate and his books on Amazon.

Mark serves as a global expert for the World Economic Forum.
He is the co-author of the best seller Understanding How the Future Unfolds: Using DRIVE to Harness the Power of Today's Megatrends. The framework contained therein was nominated for the CK Prahalad Breakthrough Idea Award by Thinkers50, the most prestigious award in business thought leadership.  His latest book, The AI Republic (2019) explores the nexus between humans and intelligent automation under the dome of the 4IR.

Mark holds a Ph.D. in Business and Economics from the International School of Management in Paris/ New York and an Executive Doctorate in Business Administration from Ecole des Ponts ParisTech in Paris. 

Areas of Expertise:
Fourth Industrial Revolution
Megatrends
Artificial Intelligence/Digital
Leading change
Competitiveness
Economic Strategy
Growth and Competitive Strategy

Languages of Instruction:
English
French
German
Italian
Spanish

Education
Executive Doctorate of Business Administration, Ecole des Ponts Paris Tech
PhD in Business and Economics, International School of Management, Paris/New York
B.A and M.A in Social Sciences, University of Turin, Italy

P. K. Kannan is the Dean鈥檚 Chair in Marketing Science at the Robert H. Smith School of Business at the University of Maryland. His research expertise is on marketing modeling, applying statistical,  econometric, machine learning, and AI methods to marketing data. His current research stream focuses on digital marketing - mobile marketing, attribution modeling, media mix modeling, new product/service development and customer relationship management (CRM).

He has received several grants from National Science Foundation (NSF), Mellon Foundation, SAIC, and PricewaterhouseCoopers for his work in this area and research papers have been published in Marketing Science, Management Science, Journal of Marketing Research, Journal of Marketing, and International Journal of Research in Marketing. His research has also won the prestigious John Little Best Paper Award (2008) and the INFORMS Society for Marketing Science Practice Prize Award (2007). His research has also been selected as a finalist for the Paul Green Award twice (2008, 2014) and he has won the AMA/MSI Paul Root Award twice (2014, 2016).

Dr. Kannan is the Editor-in-Chief of the International Journal of Research in Marketing, an Associate Editor for Journal of Marketing Research, and serves on the editorial boards of Marketing Science, Journal of Marketing, Journal of Service Research. Dr. Kannan has served as the Chair for the American Marketing Association SIG on Marketing Research and has chaired the INFORMS Service Science section.

His teaching interests include marketing modeling, digital marketing, customer relationship management, and pricing. He has taught these courses in executive programs for Black & Decker, Home Depot, ARINC, McCormick, and Northrup Grumman. He has corporate experience with Tata Engineering and Ingersoll-Rand and has consulted for companies such as Frito-Lay, Pepsi Co, Giant Food, Black and Decker, SAIC, Fannie Mae, and IBM.

Dr. Bridges is Physician-in-Chief and Chair of the Department of Medicine at Hospital for Special Surgery, as well as Chief of the Division of Rheumatology at both HSS and NewYork-Presbyterian/Weill Cornell Medical Center. He is the Franchellie M. Cadwell Professor of Medicine at HSS and the Joseph P. Routh Professor of Rheumatic Diseases in Medicine at Weill Cornell Medicine. Dr. Bridges leads 75 full-time physicians, including 38 adult and 5 pediatric rheumatologists. They collectively provide outstanding care to patients across the full spectrum of autoimmune and inflammatory rheumatic diseases and deliver perioperative medical care to patients undergoing surgical procedures at HSS. Dr. Bridges’ academic and research career has centered on understanding the cellular, molecular, and genetic molecular mechanisms that underlie rheumatoid arthritis, its clinical manifestations, and response to treatment. In particular, he has focused on the role of B lymphocytes and autoantibodies in RA, as well as genetic influences on RA in African Americans. He and his colleagues have defined genetic differences in the MHC and non-MHC genes on susceptibility to RA and on the degree of joint damage between African Americans with RA compared to European and Asian ancestries. More recently, his research program has involved crowdsourcing to facilitate machine learning and big data approaches to answer important clinical questions in RA. In addition to his leadership roles at HSS and NYPH/WCMC, Dr. Bridges is President of the Rheumatology Research Foundation and has a concurrent role as a member of the American College of Rheumatology Executive Committee.

Like many scientists, invested teachers became powerful mentors in Noah’s life, and helped define his career. As an undergraduate student, he started working in the lab of Dr. Jim Carrington at Oregon State University. “Before I started working in the lab, I hadn’t thought about working with plants. I became really interested in the research they were doing in the Carrington Lab, so I decided to go to graduate school and work in the lab as a PhD student,” explains Noah. At the same time, Noah began pursuing a career in plant science, a new technology was emerging in the scientific community: high-throughput DNA sequencing. “We went from sequencing a few hundred DNA molecules at a time to doing millions at a time.” A year into grad school, the lab was collecting so much data that he began learning how to program and do data analysis with a computer. “I shifted pretty hard away from lab work at that point.” He hasn’t looked back since. Today, Noah leads the Data Science Facility. His team builds computational tools that help other scientists solve big data problems. These custom tools could be anything from an algorithm, to a program, to the infrastructure that houses a particular suite of software tools. “A lot of times in science, you can’t just ask a question and use a tool that comes out of the box,” says Noah. As a result, he has made it his team’s mission to be a collaborative hub at the Danforth Center that creates tools that help bridge different areas of expertise.

Eric Wang is the Senior Director of Machine Intelligence at Turnitin, focusing on leveraging AI to improve learning experiences and promote academic integrity around the world. Eric is a leader in developing applications of AI for academia, government laboratories and industry, and he specializes in developing and deploying AI that emphasizes fairness, accessibility and transparency. He holds a BS and a PhD in Electrical and Computer engineering from The Ohio State University and Duke University, respectively. 

Dragan Boscovic is an expert in machine learning, cognitive networks and symbiotic relations. He is the director of ASU’s Blockchain Research Lab and is the technical director of ASU’s Center for Assured and Scalable Data Engineering. Boscovic, a research professor in the School of Computer Information and Decision Systems Engineering, has experience in numerical electromagnetics, wireless systems and IP networks, hardware and software architectures, blockchain data structures and data analytics. He the CEO of VizLore, LLC, an information technology and services company focusing on smart cities, smart energy/grid and smart health applications. He served as a Motorola research director for nearly 20 years. A Motorola research director for nearly 20 years, Boscovic has amassed 22 patents and published papers on diverse topics, such as data analytics for mobile services, consumer-centric mHealth and eHealth solutions and autonomic information and communications technology networks.

Dr. Eman El-Sheikh is Associate Vice President at the University of West Florida. She leads the Center for Cybersecurity and is also a Professor of Computer Science at UWF. Eman has extensive expertise in cybersecurity education, research, and workforce development. She received several awards related to cybersecurity education and diversity and was recognized among the 2020 Women Leaders in Cybersecurity by Security Magazine. 

Dr. El-Sheikh leads several national and regional initiatives, including the National Cybersecurity Workforce Development Program and the Southeast Regional Hub for the National Centers of Academic Excellence in Cybersecurity. Eman received numerous grants to enhance cybersecurity education, workforce development, and capacity building. She launched the Cybersecurity for All庐 Program to enhance competencies and hands-on skills for evolving cybersecurity work roles. The program was recognized among the 2020 Innovations in Cybersecurity Education. 

Dr. El-Sheikh teaches and conducts research related to the development and evaluation of Artificial Intelligence and Machine Learning for cybersecurity. She has published several books, including most recently, Computer and Network Security Essentials by Springer Publishing, over 75 peer-reviewed articles and given over 100 invited talks and presentations. 

Eman also co-founded the Florida Women in Cybersecurity Affiliate. She holds an M.S. and Ph.D. in Computer Science from Michigan State University.

Dr. Guillermo A. Francia, III joined the University of West Florida Center for Cybersecurity in 2018. Previously, Dr. Francia served as the Director of the Center for Information Security and Assurance and held a Distinguished Professor position at Jacksonville State University. Dr. Francia is a recipient of numerous cybersecurity research and curriculum development grants. His projects have been funded by prestigious institutions such as the National Science Foundation, Eisenhower Foundation, Department of Education, Department of Defense, and Microsoft Corporation. 

His scholarly interests include critical infrastructure security, connected vehicle security, security standards, and regulatory compliance and audit, radio frequency signal security, industrial control systems (ICS) security, machine learning (ML) for security, and digital badging for learning and employment records (LERs). In 1996, Dr. Francia received one of the five national awards for Innovators in Higher Education from Microsoft Corporation. 

He served as a Fulbright scholar to Malta in 2007 and a US-UK Fulbright Cybersecurity research scholar to Imperial College London in the United Kingdom in 2017. Dr. Francia is the recipient of the 2018 National CyberWatch Center Innovations in Cyber Security Education 鈥� Faculty Development Category Award.

Director of Graduate Studies, Computer Science and Engineering My research is in machine learning, network science, and social media. Generally speaking, I am interested in uncovering how humans consume and curate information. Web and Social Media Disinformation & fake news Data mining Machine learning Education: Ph.D., Computer Science, University of Illinois at Urbana-Champaign, 2013

Annie Chechitelli has spent the past two decades innovating with educators to expand access to education, meet the quickly changing needs of learners, and empower students to do their best, original work. As the Chief Product Officer at Turnitin, Annie oversees the Turnitin suite of applications which includes academic integrity, grading and feedback, and assessment capabilities.Prior to joining Turnitin, Annie spent over five years at Amazon where she led Kindle Content for School, Work, and Government and launched the AWS EdTech Growth Advisory team, advising education technology companies on how to grow their product and go-to-market strategies with AWS.Annie began her career in EdTech at Wimba where she launched a live collaboration platform for education which was ultimately acquired by Blackboard in 2010. At Blackboard she led platform management, focused on transitioning Blackboard Learn to the cloud.Annie holds a B.S. from Columbia University and an M.B.A. and M.S. from Claremont Graduate University. She lives in Seattle, Washington with her husband and three children and is an avid tennis player.

Hala Nelson is a professor of mathematics at James Madison University and the author of Essential Math for AI (O'Reilly 2023), and AI Powered Digital Twins (Wiley 2026). She specializes in mathematical modeling, AI and data strategy, digital twins, and consults for the Departments of Defense, State, and emergency and infrastructure services in the public sector. Nelson’s expertise lies at the intersection of mathematical modeling, data, AI, Digital Twins, real world industrial and military applications, and AI and data strategy and governance..
Nelson grew up in Lebanon during its brutal civil war. She lost her hair at a very young age in a missile explosion. This event, and many that followed, shaped her interests in human behavior, the nature of intelligence and artificial intelligence (AI). Her dad taught her math, at home and in French, until she graduated high school. Her favorite quote from her dad about math is, “It is the one clean science”.
Nelson earned a bachelor's degree in mathematics at Beirut Arab University, a master's degree in mathematics at American University of Beirut and a doctorate in mathematics at New York University.

 is a  and a  at the University of Illinois Urbana-Champaign. He is the William L. Everitt Faculty Scholar in ECE and holds affiliations in the Department of Speech and Hearing Science, Coordinated Science Lab, , and Department of Computer Science. He also leads the , a new research initiative to make voice recognition technology more useful for people with a range of diverse speech patterns and disabilities. 
Hasegawa-Johnson has been on the faculty at the University of Illinois since 1999. His research addresses automatic speech recognition with a focus on the mathematization of linguistic concepts. His group has developed mathematical models of concepts from linguistics including a rudimentary model of pre-conscious speech perception (the landmark-based speech recognizer), a model that interprets pronunciation variability by figuring out how the talker planned his or her speech movements (tracking of tract variables from acoustics, and of gestures from tract variables), and a model that uses the stress and rhythm of natural language (prosody) to disambiguate confusable sentences. Applications of his research include:

Speech recognition for talkers with cerebral palsy. The automatic system, suitably constrained, outperforms a human listener.

Provably correct unsupervised ASR, or ASR that can be trained using speech that has no associated text transcripts.


Equal Accuracy Ratio regularization: Methods that reduce the error rate gaps caused by gender, race, dialect, age, education, disability and/or socioeconomic class.


Automatic analysis of the social interactions between infant, father, mother, and older sibling during the first eighteen months of life.


Hasegawa-Johnson is currently Senior Area Editor of the journal IEEE Transactions on Audio, Speech and Language and a member of the ISCA Diversity Committee. He has published 308 peer-reviewed journal articles, patents, and conference papers in the general area of automatic speech analysis, including machine learning models of articulatory and acoustic phonetics, prosody, dysarthria, non-speech acoustic events, audio source separation, and under-resourced languages.
Education

Postdoctoral fellow, University of California at Los Angeles, 1996-1999

Ph.D., Massachusetts of Technology, 1996

M.S., Massachusetts Institute of Technology, 1989

Honors

2023: Fellow of the International Speech Communication Association for contributions to knowledge-constrained signal generation

2020: Fellow of the IEEE, for contributions to speech processing of under-resourced languages


2011: Fellow of the Acoustical Society of America, for contributions to vocal tract and speech modeling


2009: Senior Member of the Association for Computing Machinery


2004: Member, Articulograph International Steering Committee; CLSP Workshop leader, "Landmark-Based Speech Recognition”, Invited paper


2004: NAACL workshop on Linguistic and Higher-Level Knowledge Sources in Speech Recognition and Understanding


2003: List of faculty rated as excellent by their students


2002: NSF CAREER award


1998: NIH National Research Service Award


Personal website: 
CV: 

Prof. Wang received his Ph.D. in Applied Mathematics from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences (CAS), and won the Special Prize of President Scholarship and Excellent Ph.D. thesis Award of CAS. Between 2011 and 2015, he was a Postdoctoral Research Scientist at Columbia University. In 2015, he was named as the Precision Medicine Fellow and promoted to Associate Research Scientist. He established the Wang Genomics Laboratory @HKUST in 2016, focusing on the application of data science in biology and medicine. He has made substantial contributions to (1) characterization, modeling, and prediction of cancer evolution from genomics (Nat Genet 2016; Nat Genet 2017; Nat Commun 2021); (2) discovery, elucidation, and clinical application of MGMT fusion (Nat Genet 2016; Nat Commun 2020) and METex14 in adult gliomas (Nat Genet 2018; Cell 2018); (3) discovery of MAP3K3-I441M in CCM (AJHG 2021) and elucidation of EndMT in bAVM (Circ Res 2021); (4) reconstruction of RNA Exosome-regulated non-coding transcriptomes (Nature 2014; Cell 2015). He won the Excellent Young Scientist Award of NSFC (2019), the School of Engineering Young Investigator Research Award (2019), the School of Science Research Award (2021), and the Zhong Nanshan Youth Science and Technology Innovation Award (2021).


 


Research Question


 


Recent advances in next-generation sequencing are revolutionizing numerous areas in life science and medicine. Prof. Wang's research is focused on discovering and elucidating functional genomic alterations in complex human diseases, such as intracranial cancers and vascular malformations, by developing and/or applying computational methods based on multi-omics integration, statistics, and machine learning, aiming to bridge the gaps among data, bench, and bedside. More specifically, Prof. Wang's team has been mainly working on the following two scientific questions.


 


Question 1: How does clonal evolution drive cancer progression that leads to malignant transformation and therapeutic resistance?


 


Clonal evolution of cancer is a major challenge leading to treatment failure, but the molecular mechanisms of how cancer cells evolve and gain the capability of surviving intensive chemo- and/or radio- therapies remain elusive. Therefore, it is critically important to characterize the spatial and temporal dynamics of cancer cells and thereby mathematically modelling this process via big data integration. We have been working on diffuse gliomas, the most common and aggressive forms of primary tumors in adult brain whose treatment outcome is still very poor. Current therapies inevitably lead to tumor recurrence and the recurrent gliomas commonly become treatment resistance and incurable. Analyzing longitudinal and single-cell multi-omics data on this disease, our team aims to address the following questions: a) why cancer cells always display complex patterns of intratumoral heterogeneity; b) what is the temporal order of multiple somatic mutations detected in various cancer clones; c) how to predict the evolutionary path and clinical response of cancer cells under a certain therapy based on the sign seen earlier; and d) what are the key factors in tumor and its microenvironment that shape cancer evolution and determine cancer cell response under clinical intervention. In the process of addressing these questions, we will be able to unravel the mysteries of cancer evolution and it might provide a theoretical foundation for designing new means of treatment or diagnostics for better precision cancer medicine via targeting cancer dynamics.


 


Question 2: What is the role of genetic interaction between germline variants and somatic mutations in initializing and regulating the development of cancer and other genetic disorders?


 


Somatic genomic and epigenomic mutations are regarded as the direct drivers of cancer initialization and evolution, whereas de novo and inherited germline alterations could predispose the cancer risk and regulate population-specific disease incidence and treatment response. However, the underlying genetic interactions between germline variants and somatic mutations remain unclear, and the biological and medical implications of these interactions have not been extensively explored. New technologies of genomic sequencing allow low-cost profiling of somatic and germline mutations in not only case-unaffected-parental trios but also disease lesions at a high resolution, providing a unique opportunity to systematically investigate disease-relevant genomes by uncovering the joint contribution of the germline variants and somatic mutations in the process of disease development. Understanding whether and how the germline risk alleles interact with somatic mutations in terms of pathway activation and/or cellular interaction will help us to better understand disease etiology for the purpose of developing novel methods for genome-guided disease risk evaluation and personalized clinical intervention.


 


Representative Publications


 




Biaobin Jiang, Quanhua Mu, Fufang Qiu, Xuefeng Li, Weiqi Xu, Jun Yu, Weilun Fu, Yong Cao, Jiguang Wang#. Machine learning of genomic features in organotropic metastases stratifies progression risk of primary tumors. Nature Communications 12, Article number: 6692, 2021.


 


Hao Li*, Yoonhee Nam*, Ran Huo*, Weilun Fu*, Biaobin Jiang, Qiuxia Zhou, Dong Song, Yingxi Yang, Yuming Jiao, Jiancong Weng, Zihan Yan, Lin Di, Jie Li, Jie Wang, Hongyuan Xu, Shuo Wang, JiZong Zhao, Zilong Wen, Jiguang Wang#, Yong Cao#. De Novo Germline and Somatic Variants Convergently Promote Endothelial-to-Mesenchymal Transition in Simplex Brain Arteriovenous Malformation. Circulation Research, 129(9), 825–839, 2021.


 


Jiancong Weng*, Yingxi Yang*†, Dong Song*†, Ran Huo*, Hao Li, Yoonhee Nam†, Yiyun Chen†, Qiuxia Zhou, Yuming Jiao, Weilun Fu, Zihan Yan, Jie Wang, Hongyuan Xu, Lin Di, Jie Li, Shuo Wang, Jizong Zhao, Jiguang Wang#, Yong Cao#. Somatic MAP3K3 Mutation Defines a Subclass of Cerebral Cavernous Malformation. American Journal of Human Genetics 108(5):942-950, 2021.


 


Barbara Oldrini*, Nuria Vaquero-Siguero*, Quanhua Mu*†, Paula Kroon, Ying Zhang, Marcos Galán-Ganga, Zhaoshi Bao‡, Zheng Wang, Hanjie Liu, Jason Sa, Junfei Zhao, Hoon Kim, Sandra Rodriguez-Perales, Do-Hyun Nam, Roel Verhaak, Raul Rabadan§, Tao Jiang#, Jiguang Wang#, and Massimo Squatrito#. MGMT genomic rearrangements contribute to chemotherapy resistance in gliomas. Nature Communications, 11(1):3883, 2020.


 

Hu H*, Mu Q*†, Bao Z*‡, Chen Y*†, Liu Y*, Chen J, Wang K, Wang Z, Nam Y†, Jiang B‡, Sa JK, Cho H-J, Her N-G, Zhang C, Zhao Z, Zhang Y, Zeng F, Wu F, Kang X, Liu Y, Qian Z, Wang Z, Huang R, Wang Q, Zhang W, Qiu X, Li W, Nam D-H, Fan X#, Wang J#, Jiang T#. Mutational landscape of secondary glioblastoma guides MET-targeted trial in brain tumor. Cell; 175 (6), 1665-1678, 2018.

 
Full list at .


 


Related News


 

Schwartz expertise focuses on predicting customer behavior, understanding its drivers, and examining how firms actively manage their customer relationships through interactive marketing. His research in customer analytics stretches managerial applications, including online display advertising, email marketing, video consumption, and word-of-mouth. He teaches marketing topics. Schwartz holds a BA and PhD from the University of Pennsylvania. 

Balaji Padmanabhan has a bachelor's degree in computer science from Indian Institute of Technology (IIT) Madras and a PhD from New York University’s Stern School of Business and has worked in the data science, AI/machine learning and business analytics areas for 25 years. His current work addresses the design of artificial and augmented intelligence solutions that combine data, machine learning and modeling the real-world through complex systems simulations and has broad applications across business, policy, media and healthcare. He has published extensively in data science and related areas at premier journals and conferences in the field and has served on the editorial board of leading journals including Management Science, MIS Quarterly, INFORMS Journal on Computing, Information Systems Research, Big Data, ACM Transactions on MIS and the Journal of Business Analytics. 

Department: English, Libraries 
Areas of expertise:

Digital Humanities
Artificial intelligence and machine learning
Digital libraries and museums
Open access and scholarly publishing 

Nowviskie is the Dean of Libraries and a professor of English. She was previously the executive director of the Digital Library Federation and a Council on Library and Information Resources (CLIR) Distinguished Presidential Fellow. She was president of the Association for Computers and the Humanities and chair of the Modern Language Association’s Committee on Information Technology. 
Her research interests include digital humanities, digital libraries, community-based archives, Nineteenth-century literature, material culture, textual criticism, machine learning, environmental humanities in the context of climate change, indigenous ways of knowing and the history of the book. 
Nowviskie earned a bachelor's degree in English and archaeology at the University of Virginia, a master's degree in English education at Wake Forest University and a doctorate in English at the University of Virginia.

Wei's research focuses on how massive location-based social media data can help the understanding of the nature of human activities and the dynamics of social interactions.
Courses Wei has taught include python programming; data mining and modeling; data visualization; machine learning; and data analysis on AWS.
Wei earned a doctorate in geography at the University of Georgia, master's degrees in GIS and urban planning at Wuhan University and University of Twente; and a bachelor's degree in urban planning at Wuhan University.