Work with thought leaders and academic experts in Information Systems

Companies can benefit from working with an academic researcher in Information Systems in several ways. Firstly, they can gain valuable insights and knowledge about the latest trends and advancements in the field. Researchers can help companies solve complex problems by applying their expertise and conducting in-depth analysis. Additionally, collaborating with researchers can provide companies with access to cutting-edge technology and tools. By working with an academic researcher, companies can stay ahead of the competition and make informed decisions based on data-driven research.

Researchers on NotedSource with backgrounds in Information Systems include Ping Luo, Jerry Schnepp, Ph.D., Martin Tsui, Edoardo Airoldi, David J. Lilja, Jeffrey Townsend, Jim Samuel, Dr Leandra Jordaan, Catherine Tucker, Balamurugan Tangiisuran, Anit Kumar Sahu, TuongThuy Vu, Suhang Wang, Dr. Haikun Huang, Ph.D., Denys Dutykh, and Deepak Khazanchi.

Ping Luo

Toronto, Ontario, Canada
Bioinformatics Specialist at Princess Margaret Cancer Centre with experience in deep learning
Most Relevant Research Expertise
Information Systems
Other Research Expertise (21)
single-cell genomics
deep learning
complex network analysis
Genetics (clinical)
Genetics
And 16 more
About
8 years of science and engineering experience integrating multi-omics data to identify biomarkers for cancer studies. Seeking to apply data analytics expertise to develop new diagnosis and treatment strategies.
Most Relevant Publications (1+)

23 total publications

Evaluation of single-cell RNAseq labelling algorithms using cancer datasets

Briefings in Bioinformatics / Dec 30, 2022

Christensen, E., Luo, P., Turinsky, A., Husić, M., Mahalanabis, A., Naidas, A., Diaz-Mejia, J. J., Brudno, M., Pugh, T., Ramani, A., & Shooshtari, P. (2022). Evaluation of single-cell RNAseq labelling algorithms using cancer datasets. Briefings in Bioinformatics, 24(1). https://doi.org/10.1093/bib/bbac561

See Full Profile

Jerry Schnepp, Ph.D.

Chicago, Illinois, United States of America
Chair of Computer Science, Judson University
Most Relevant Research Expertise
Information Systems
Other Research Expertise (18)
Human Computer Interaction
User Experience
Interactive Media
Computer Graphics
Accommodations for the Deaf
And 13 more
About
As a technologist, designer, and creative problem-solver, I'm passionate about teaching people to embrace new technology and explore. I am the Chair of the Computer Science department at Judson University. Before my appointment, I served as an Associate Professor in the College of Technology, Architecture and Applied Engineering at Bowling Green State University (BGSU). I teach courses in Programming, Data Structures and Algorithms, Software Design Patterns, Interactive Media, Usability, User Experience, and Augmented/Virtual Reality. I was the founding director of the Collab Lab, a hands-on, creative space for students and faculty to engage in collaborative work. My research efforts are directed in several areas: AI Supported Individualized Learning, Learner Experience Design, Technology for Online Assessment, Interactive Mobile Learning, and Computerized Sign Language Synthesis. I enjoy collaborating on projects involving cutting-edge technology and new applications.
Most Relevant Publications (2+)

20 total publications

An automated technique for real-time production of lifelike animations of American Sign Language

Universal Access in the Information Society / May 14, 2015

McDonald, J., Wolfe, R., Schnepp, J., Hochgesang, J., Jamrozik, D. G., Stumbo, M., Berke, L., Bialek, M., & Thomas, F. (2015). An automated technique for real-time production of lifelike animations of American Sign Language. Universal Access in the Information Society, 15(4), 551–566. https://doi.org/10.1007/s10209-015-0407-2

Special issue: recent advances in sign language translation and avatar technology

Universal Access in the Information Society / Jun 02, 2015

Wolfe, R., Efthimiou, E., Glauert, J., Hanke, T., McDonald, J., & Schnepp, J. (2015). Special issue: recent advances in sign language translation and avatar technology. Universal Access in the Information Society, 15(4), 485–486. https://doi.org/10.1007/s10209-015-0412-5

See Full Profile

Martin Tsui

San Francisco, California, United States of America
University of California, San Francisco
Most Relevant Research Expertise
Information Systems
Other Research Expertise (15)
Biochemistry
Structural Biology
Cryo-EM
CRISPR
Molecular Assembly and Interaction
And 10 more
About
Martin Tsui is an accomplished scientist with a strong background in biochemistry. He received his Ph.D. in Molecular Biophysics from Florida State University in 2017, where he conducted research on the structure and function of CRISPR proteins. Prior to that, he obtained his B.S. in Chemistry from the University of California, San Diego in 2012. After completing his graduate studies, Martin founded his own company, Stealth, where he serves as a Founder & CEO. Under his leadership, the company has developed innovative solutions for the biotech industry and has gained recognition for its groundbreaking research. Before starting his company, Martin worked as a Senior Scientist at Amazon, where he applied his expertise in protein biochemistry and CRISPR to improve the company's product development processes and creating new products. He also gained valuable experience as a Postdoctoral Scholar at the University of California, San Francisco and Postdoctoral Fellow at the Van Andel Institute, where he studied cancer proteins, SARS-CoV-2, HIV proteins, and the role of proteins in neurodegenerative diseases, respectively. Martin is a highly driven and passionate individual who is dedicated to advancing the field of biotechnology. His impressive education and diverse experience have equipped him with the skills and knowledge to make significant contributions to the scientific community. He continues to pursue new opportunities to further his research and make a positive impact in the world of science.
Most Relevant Publications (1+)

16 total publications

Comparative host–pathogen protein–protein interaction analysis of recent coronavirus outbreaks and important host targets identification

Briefings in Bioinformatics / Sep 11, 2020

Khan, A. A., & Khan, Z. (2020). Comparative host–pathogen protein–protein interaction analysis of recent coronavirus outbreaks and important host targets identification. Briefings in Bioinformatics, 22(2), 1206–1214. https://doi.org/10.1093/bib/bbaa207

See Full Profile

Edoardo Airoldi

Professor of Statistics & Data Science Temple University & PI, Harvard University
Most Relevant Research Expertise
Information Systems
Other Research Expertise (43)
Statistics
Causal Inference
Network Science
Cell Biology
Molecular Biology
And 38 more
About
Edoardo Airoldi is a Professor in the Department of Machine Learning at Temple University. He is also the Director of the Center for Machine Learning and Health. He is a world-renowned expert in the fields of machine learning and artificial intelligence, with a focus on applications to health. Airoldi is a member of the prestigious Association for the Advancement of Artificial Intelligence (AAAI) and the International Machine Learning Society (IMLS). He has published over 200 papers in leading journals and conferences, and his work has been covered by various media outlets including The New York Times, The Wall Street Journal, The Economist, and Wired.
Most Relevant Publications (5+)

106 total publications

Assessing the Impact of Granular Privacy Controls on Content Sharing and Disclosure on Facebook

Information Systems Research / Dec 01, 2016

Cavusoglu, H., Phan, T. Q., Cavusoglu, H., & Airoldi, E. M. (2016). Assessing the Impact of Granular Privacy Controls on Content Sharing and Disclosure on Facebook. Information Systems Research, 27(4), 848–879. https://doi.org/10.1287/isre.2016.0672

A Coevolution Model of Network Structure and User Behavior: The Case of Content Generation in Online Social Networks

Information Systems Research / Mar 01, 2019

Bhattacharya, P., Phan, T. Q., Bai, X., & Airoldi, E. M. (2019). A Coevolution Model of Network Structure and User Behavior: The Case of Content Generation in Online Social Networks. Information Systems Research, 30(1), 117–132. https://doi.org/10.1287/isre.2018.0790

Confidence sets for network structure

Statistical Analysis and Data Mining / Sep 09, 2011

Airoldi, E. M., Choi, D. S., & Wolfe, P. J. (2011). Confidence sets for network structure. Statistical Analysis and Data Mining, 4(5), 461–469. https://doi.org/10.1002/sam.10136

Network sampling and classification: An investigation of network model representations

Decision Support Systems / Jun 01, 2011

Airoldi, E. M., Bai, X., & Carley, K. M. (2011). Network sampling and classification: An investigation of network model representations. Decision Support Systems, 51(3), 506–518. https://doi.org/10.1016/j.dss.2011.02.014

An entropy approach to disclosure risk assessment: Lessons from real applications and simulated domains

Decision Support Systems / Apr 01, 2011

Airoldi, E. M., Bai, X., & Malin, B. A. (2011). An entropy approach to disclosure risk assessment: Lessons from real applications and simulated domains. Decision Support Systems, 51(1), 10–20. https://doi.org/10.1016/j.dss.2010.11.014

See Full Profile

David J. Lilja

Minneapolis, Minnesota, United States of America
Professor Emeritus of Electrical and Computer Engineering, University of Minnesota
Most Relevant Research Expertise
Information Systems
Other Research Expertise (15)
Computer architecture
high-performance parallel processing
computer systems performance analysis
approximate computing
Hardware and Architecture
And 10 more
About
**Research Expertise** Computer architecture, high-performance parallel processing, computer systems performance analysis, approximate computing, computing with emerging technologies, and storage systems. **Biographical summary** David J. Lilja received a Ph.D. and an M.S., both in Electrical Engineering, from the [University of Illinois at Urbana-Champaign,](http://www.uiuc.edu/) and a B.S. in Computer Engineering from [Iowa State University](http://www.iastate.edu/) in Ames. He is Professor Emeritus of [Electrical and Computer Engineering](http://www.ee.umn.edu/) at the [University of Minnesota](http://www.umn.edu/) in Minneapolis. He previously served as a member of the graduate faculties in [Computer Science](http://www.cs.umn.edu/), [Scientific Computation](http://www.scicomp.umn.edu/), and [Data Science](http://datascience.umn.edu//).  He served ten years as the head of the ECE department at the University of Minnesota, worked as a research assistant at the Center for Supercomputing Research and Development at the [University of Illinois,](http://www.uiuc.edu/) and as a development engineer at [Tandem Computers Incorporated](http://www.tandem.com/) in Cupertino, California.  He received a [Fulbright](http://www.fulbright.org/) Senior Scholar Award to visit the University of Western Australia and was a visiting Professor at the University of Canterbury in Christchurch, New Zealand. He has chaired and served on the program committees of numerous conferences.  He was elected a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and a Fellow of the American Association for the Advancement of Science (AAAS) for contributions to the statistical analysis of computer performance. He also is a registered Professional Engineer.
Most Relevant Publications (4+)

99 total publications

Accelerating geoscience and engineering system simulations on graphics hardware

Computers & Geosciences / Dec 01, 2009

Walsh, S. D. C., Saar, M. O., Bailey, P., & Lilja, D. J. (2009). Accelerating geoscience and engineering system simulations on graphics hardware. Computers & Geosciences, 35(12), 2353–2364. https://doi.org/10.1016/j.cageo.2009.05.001

JaViz: A client/server Java profiling tool

IBM Systems Journal / Jan 01, 2000

Kazi, I. H., Jose, D. P., Ben-Hamida, B., Hescott, C. J., Kwok, C., Konstan, J. A., Lilja, D. J., & Yew, P.-C. (2000). JaViz: A client/server Java profiling tool. IBM Systems Journal, 39(1), 96–117. https://doi.org/10.1147/sj.391.0096

Exploring Performance Characteristics of the Optane 3D Xpoint Storage Technology

ACM Transactions on Modeling and Performance Evaluation of Computing Systems / Feb 04, 2020

Yang, J., Li, B., & Lilja, D. J. (2020). Exploring Performance Characteristics of the Optane 3D Xpoint Storage Technology. ACM Transactions on Modeling and Performance Evaluation of Computing Systems, 5(1), 1–28. https://doi.org/10.1145/3372783

High Quality Down-Sampling for Deterministic Approaches to Stochastic Computing

IEEE Transactions on Emerging Topics in Computing / Jan 01, 2021

Najafi, M. H., & Lilja, D. J. (2021). High Quality Down-Sampling for Deterministic Approaches to Stochastic Computing. IEEE Transactions on Emerging Topics in Computing, 9(1), 7–14. https://doi.org/10.1109/tetc.2017.2789243

See Full Profile

Jeffrey Townsend

New Haven, CT, Connecticut, United States of America
Professor of Biostatistics and Ecology & Evolutionary Biology
Most Relevant Research Expertise
Information Systems
Other Research Expertise (52)
Evolutionary Genomics
Microbiology
Infectious Diseases
Genetics
Cell Biology
And 47 more
About
Jeffrey Townsend is a Professor of Organismic and Evolutionary Biology at Yale University. He received his Ph.D. from Harvard University in 2002 and his Sc.B. from Brown University in 1994. He has been a teacher at St. Ann's School and an Assistant Professor at the University of Connecticut. He is currently the Elihu Professor of Biostatistics at Yale University.
Most Relevant Publications (3+)

207 total publications

Identifying modules of cooperating cancer drivers

Molecular Systems Biology / Mar 01, 2021

Klein, M. I., Cannataro, V. L., Townsend, J. P., Newman, S., Stern, D. F., & Zhao, H. (2021). Identifying modules of cooperating cancer drivers. Molecular Systems Biology, 17(3). Portico. https://doi.org/10.15252/msb.20209810

Bringing Web 2.0 to bioinformatics

Briefings in Bioinformatics / Oct 08, 2008

Zhang, Z., Cheung, K.-H., & Townsend, J. P. (2008). Bringing Web 2.0 to bioinformatics. Briefings in Bioinformatics, 10(1), 1–10. https://doi.org/10.1093/bib/bbn041

A Bayesian method for analysing spotted microarray data

Briefings in Bioinformatics / Jan 01, 2005

Meiklejohn, C. D., & Townsend, J. P. (2005). A Bayesian method for analysing spotted microarray data. Briefings in Bioinformatics, 6(4), 318–330. https://doi.org/10.1093/bib/6.4.318

See Full Profile

Jim Samuel

Associate Professor at Rutgers University
Most Relevant Research Expertise
Information Systems
Other Research Expertise (21)
Analytics
Artificial Intelligence
Informatics
Machine Learning
NLP NLU NLG Behavioral Finance
And 16 more
About
Jim Samuel is an Associate Professor of Practice and Executive Director of the Informatics Program at the Bloustein School. He is an information and artificial intelligence (AI) scientist, with significant industry experience in finance, technology, entrepreneurship and data analytics. Dr. Samuel’s primary research covers human intelligence and artificial intelligences interaction and information philosophy.  Dr. Samuel’s applied research focuses on the optimal use of big data and smart data driven AI applications, textual analytics, natural language processing and artificially intelligent public opinion informatics. His expertise extends to socioeconomic implications of AI, applied machine learning, social media analytics, AI education and AI bias. Dr. Samuel completed his Ph.D. from the Zicklin School of Business, Baruch College – City University of New York, and he also has M.Arch and M.B.A (International Finance) degrees.  Dr. Samuel has worked with large multinational financial services corporations, and advises businesses and organizations on data analytics and AI driven value creation strategies. He is passionate about research driven thought leadership in AI, information philosophy, analytics and informatics. 
Most Relevant Publications (5+)

44 total publications

Regulation of data-driven market power in the digital economy: Business value creation and competitive advantages from big data

Journal of Information Technology / Feb 24, 2023

Fast, V., Schnurr, D., & Wohlfarth, M. (2023). Regulation of data-driven market power in the digital economy: Business value creation and competitive advantages from big data. Journal of Information Technology, 026839622211143. https://doi.org/10.1177/02683962221114394

Customized AI Readers: An Adaptive Framework for Flexible Human Handwriting Recognition of Numerical Digits with OCR Methods

Information / May 26, 2023

Jain, P. H., Kumar, V., Samuel, J., Singh, S., Mannepalli, A., & Anderson, R. (2023). Customized AI Readers: An Adaptive Framework for Flexible Human Handwriting Recognition of Numerical Digits with OCR Methods. Information, 14(6), 305. https://doi.org/10.3390/info14060305

Adaptive cognitive fit: Artificial intelligence augmented management of information facets and representations

International Journal of Information Management / Aug 01, 2022

Samuel, J., Kashyap, R., Samuel, Y., & Pelaez, A. (2022). Adaptive cognitive fit: Artificial intelligence augmented management of information facets and representations. International Journal of Information Management, 65, 102505. https://doi.org/10.1016/j.ijinfomgt.2022.102505

Would you please like my tweet?! An artificially intelligent, generative probabilistic, and econometric based system design for popularity-driven tweet content generation

Decision Support Systems / May 01, 2021

Garvey, M. D., Samuel, J., & Pelaez, A. (2021). Would you please like my tweet?! An artificially intelligent, generative probabilistic, and econometric based system design for popularity-driven tweet content generation. Decision Support Systems, 144, 113497. https://doi.org/10.1016/j.dss.2021.113497

COVID-19 Public Sentiment Insights and Machine Learning for Tweets Classification

Information / Jun 11, 2020

Samuel, J., Ali, G. G. Md. N., Rahman, Md. M., Esawi, E., & Samuel, Y. (2020). COVID-19 Public Sentiment Insights and Machine Learning for Tweets Classification. Information, 11(6), 314. https://doi.org/10.3390/info11060314

See Full Profile

Dr Leandra Jordaan

I work at the intersection of information, wise judgement, and the social reality of people.
Most Relevant Research Expertise
Information Systems
Other Research Expertise (8)
Phronesis
Ethnography
Organisational research
Information architecture
Communication and Resource Optimization
And 3 more
About
I am an ICT and IS expert with experience in higher education support services, championing various complex projects, programmes and frameworks to improve cross-disciplinary communication, optimize the use of available resources, and ensure an excellent user experience when accessing information across all digital platforms. Servant leadership, organizational acumen, and innovative/analytical problem-solving combined with extensive ICT expertise and a blend of other relevant disciplines, equip me with a unique perspective to design and implement effective solutions where people and information converge. Professional Focus: Adding measurable value to any organisation seeking to navigate the complex and rapidly evolving landscape of digital transformation, implementing frameworks for effective communication, increased synergy, and organizational success through the resulting innovation.

See Full Profile

Catherine Tucker

Advertising & Economics Professor at MIT
Most Relevant Research Expertise
Information Systems
Other Research Expertise (23)
Marketing
Economics
Regulation
IT
Economics and Econometrics
And 18 more
About
Catherine Tucker is a Professor of Economics and Data Science at the Massachusetts Institute of Technology. She is also a member of the MIT Sloan School of Management's faculty. She is a world-renowned expert in the fields of big data, machine learning, and consumer behavior. She has worked extensively on the use of data science to improve public policy and has been a consultant to government agencies and businesses around the world. In addition to her academic work, she is a popular speaker and has been featured in many media outlets, including The Economist, The New York Times, The Wall Street Journal, and Wired.
Most Relevant Publications (1+)

94 total publications

Active Social Media Management: The Case of Health Care

Information Systems Research / Mar 01, 2013

Miller, A. R., & Tucker, C. (2013). Active Social Media Management: The Case of Health Care. Information Systems Research, 24(1), 52–70. https://doi.org/10.1287/isre.1120.0466

See Full Profile

Balamurugan Tangiisuran

Boston, Massachusetts, United States of America
Associate Professor in Clinical Pharmacy at Universiti Sains Malaysia
Most Relevant Research Expertise
Information Systems
Other Research Expertise (51)
Geriatrics
Pharmacy
Internal Medicine
Psychiatry and Mental health
Clinical Psychology
And 46 more
About
Dr. Bala brings a wealth of knowledge and expertise to his role as an Associate Professor in Clinical Pharmacy at the School of Pharmaceutical Sciences, USM. He has a proven track record of success in his field, having held key leadership positions such as Director at the Malaysian National Poison Centre and Program Chairman (Clinical Pharmacy) at the School of Pharmaceutical Sciences, USM. He holds a Bachelor of Pharmacy from USM and a PhD from Brighton and Sussex Medical School, UK. Additionally, he has been appointed as Visiting Senior Lecturer at King's College London and as a Fellow of the WHO Collaborating Centre for Drug Information at the National Poison Centre. <br> Bala's research focuses on the areas of clinical pharmacy practice and medication safety, as well as geriatric pharmacy. He has published more than 50 peer-reviewed journal articles/abstracts and has been invited as a guest speaker at numerous international and domestic scientific events. He is an experienced internal and external examiner for over 40 PhD and Master thesis and has actively reviewed manuscripts for international academic journals. Bala's teaching activities encompass both undergraduate and postgraduate-level instruction, and he has supervised the research of numerous postgraduate students. He is committed to curriculum development and has implemented innovative and interactive teaching methods to improve student learning outcomes. He has successfully graduated 24 students, including 4 PhDs, 4 MSc, and 16 Master in Clinical Pharmacy. He is dedicated to producing sustainable pharmacy education and closing the knowledge transfer gap for students. If you're interested in Clinical Pharmacy, Geriatric pharmacy, Medication Safety, Research and Education, feel free to connect and exchange ideas.
Most Relevant Publications (1+)

78 total publications

Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust

International Journal of Information Management / Jun 01, 2017

Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110. https://doi.org/10.1016/j.ijinfomgt.2017.01.002

See Full Profile

Anit Kumar Sahu

PhD from CMU working in ML/AI
Most Relevant Research Expertise
Information Systems
Other Research Expertise (19)
Federated Learning
Stochastic Optimization
Data Selection
Electrical and Electronic Engineering
Signal Processing
And 14 more
About
Anit Kumar Sahu is a highly accomplished researcher and engineer in the field of Electrical and Computer Engineering. He earned his PhD from Carnegie Mellon University in 2018, where he focused his research on statistical machine learning. During his time at CMU, he received the A.G. Jordan award for outstanding thesis. After completing his PhD, Anit joined Amazon Services LLC as a Senior Applied Scientist, where he works on developing innovative solutions for complex business problems using machine learning and artificial intelligence. Prior to joining Amazon, Anit worked at Bosch Center for Artificial Intelligence as a Machine Learning Research Scientist, where he developed cutting-edge algorithms for adversarial machine learning. He is currently Principal AI Scientist at GE Healthcare AI, where he is responsible for leading research and development efforts in the healthcare sector. With his extensive education and experience in both academia and industry, Anit has become a leading expert in the field of machine learning, computer vision, and artificial intelligence. He has published numerous research papers in top conferences and journals, and his work has been widely cited by other researchers in the field. Apart from his professional accomplishments, Anit is also passionate about mentoring and teaching the next generation of engineers and scientists. In his free time, Anit enjoys hiking, trying new restaurants, and traveling to new places. He also actively participates in various volunteer activities and is dedicated to giving back to his community.
Most Relevant Publications (3+)

59 total publications

Distributed Constrained Recursive Nonlinear Least-Squares Estimation: Algorithms and Asymptotics

IEEE Transactions on Signal and Information Processing over Networks / Jan 01, 2016

Sahu, A. K., Kar, S., Moura, J. M. F., & Poor, H. V. (2016). Distributed Constrained Recursive Nonlinear Least-Squares Estimation: Algorithms and Asymptotics. IEEE Transactions on Signal and Information Processing over Networks, 1–1. https://doi.org/10.1109/tsipn.2016.2618318

Recursive Distributed Detection for Composite Hypothesis Testing: Nonlinear Observation Models in Additive Gaussian Noise

IEEE Transactions on Information Theory / Aug 01, 2017

Sahu, A. K., & Kar, S. (2017). Recursive Distributed Detection for Composite Hypothesis Testing: Nonlinear Observation Models in Additive Gaussian Noise. IEEE Transactions on Information Theory, 63(8), 4797–4828. https://doi.org/10.1109/tit.2017.2686435

Guest Editorial Inference and Learning over Networks

IEEE Transactions on Signal and Information Processing over Networks / Dec 01, 2016

Matta, V., Richard, C., Saligrama, V., & Sayed, A. H. (2016). Guest Editorial Inference and Learning over Networks. IEEE Transactions on Signal and Information Processing over Networks, 2(4), 423–425. https://doi.org/10.1109/tsipn.2016.2615526

See Full Profile

TuongThuy Vu

Geospatial Scientist with over 20-year experiences focusing in data fusion and applications to environmental and disaster management. Also, 10-years experiences as manager and senior executive in higher education.
Most Relevant Research Expertise
Information Systems
Other Research Expertise (29)
Geospatial Data Science
Urban Remote Sensing
Disaster Monitoring
Global and Planetary Change
Earth-Surface Processes
And 24 more
About
Professor Vu, a geospatial scientist by training and research, boasts two decades of expertise spanning Eurasia. Following his PhD in 2003, he commenced his journey as a research scientist at the Earthquake Disaster Mitigation Research Center in Kobe, Japan, before transitioning to a postdoctoral role at Chiba University from 2006 to 2007. Throughout his tenure in Japan, he directed his efforts towards leveraging geospatial technologies for disaster mitigation and management. Subsequently, he joined the GEOGrid team at the National Institute of Advanced Industrial Science and Technology (AIST), delving into research on high-performance computing platforms. His academic journey continued with a teaching stint at the Royal Institute of Technology in Sweden, before assuming roles at the University of Nottingham Malaysia Campus and later Hoa Sen University in Vietnam, where he ascended to the position of Vice-President. Presently, as a Professor and Dean of Engineering and Science at Curtin University Malaysia, Professor Vu's contributions extend beyond academia. Recognized as a Docent by the Royal Institute of Technology in Sweden, he holds esteemed memberships in various professional bodies, including the Open Source Geospatial Foundation and IEEE. Additionally, he is honored as a Fellow and council member of the ASEAN Academy of Engineering and Technology (AAET), as well as a Fellow of the Higher Education Academy.
Most Relevant Publications (1+)

71 total publications

An Empirical Study on Improving the Speed and Generalization of Neural Networks Using a Parallel Circuit Approach

International Journal of Parallel Programming / May 12, 2016

Phan, K. T., Maul, T. H., & Vu, T. T. (2016). An Empirical Study on Improving the Speed and Generalization of Neural Networks Using a Parallel Circuit Approach. International Journal of Parallel Programming, 45(4), 780–796. https://doi.org/10.1007/s10766-016-0435-4

See Full Profile

Suhang Wang

Professor at Pennsylvania State University
Most Relevant Research Expertise
Information Systems
Other Research Expertise (20)
Machine learning
Graph Mining
Theoretical Computer Science
Information Systems and Management
Computer Science Applications
And 15 more
About
Dr. Suhang Wang is an Assistant Professor of Computer Science and Engineering at Pennsylvania State University. He received his PhD in Computer Science from Arizona State University in 2018, and his Master's degree in Electrical Engineering: Systems from the University of Michigan in 2013. Before joining Penn State, Dr. Wang was a postdoctoral researcher at the University of California, Santa Barbara. His research interests include natural language processing, artificial intelligence, and machine learning. He was recognized for his work at the International Conference on Knowledge Discovery and Data Mining in 2017 and the Fifth ACM International Conference on Web Search and Data Mining in 2016.
Most Relevant Publications (4+)

92 total publications

FakeNewsNet: A Data Repository with News Content, Social Context, and Spatiotemporal Information for Studying Fake News on Social Media

Big Data / Jun 01, 2020

Shu, K., Mahudeswaran, D., Wang, S., Lee, D., & Liu, H. (2020). FakeNewsNet: A Data Repository with News Content, Social Context, and Spatiotemporal Information for Studying Fake News on Social Media. Big Data, 8(3), 171–188. https://doi.org/10.1089/big.2020.0062

Exploring Hierarchical Structures for Recommender Systems

IEEE Transactions on Knowledge and Data Engineering / Jun 01, 2018

Wang, S., Tang, J., Wang, Y., & Liu, H. (2018). Exploring Hierarchical Structures for Recommender Systems. IEEE Transactions on Knowledge and Data Engineering, 30(6), 1022–1035. https://doi.org/10.1109/tkde.2018.2789443

Facilitating Time Critical Information Seeking in Social Media

IEEE Transactions on Knowledge and Data Engineering / Oct 01, 2017

Ranganath, S., Wang, S., Hu, X., Tang, J., & Liu, H. (2017). Facilitating Time Critical Information Seeking in Social Media. IEEE Transactions on Knowledge and Data Engineering, 29(10), 2197–2209. https://doi.org/10.1109/tkde.2017.2701375

Self-Supervised learning for Conversational Recommendation

Information Processing &amp; Management / Nov 01, 2022

Li, S., Xie, R., Zhu, Y., Zhuang, F., Tang, Z., Zhao, W. X., & He, Q. (2022). Self-Supervised learning for Conversational Recommendation. Information Processing &amp; Management, 59(6), 103067. https://doi.org/10.1016/j.ipm.2022.103067

See Full Profile

Dr. Haikun Huang, Ph.D.

Chief Technology Officer at Great Victory Legends
Most Relevant Research Expertise
Information Systems
Other Research Expertise (25)
Computational Design
Graphics
Vision
VR/AR/MR
Cognitive Science.
And 20 more
About
Dr. Haikun Huang holds a Ph.D. in Computer Science from UMass Boston and is a postdoctoral research fellow at George Mason University. His graduation thesis was titled AI-driven Computational Design Tools For Synthesizing Human-centric Design and won the Umass Boston year's graduate program award. With a strong background in AR/VR/MR, computational design, graphics, HCI, and vision, he is passionate about applying artificial intelligence techniques to create innovative 3D content creation tools and virtual experiences.   Dr. Huang has published his research in prestigious conferences such as IEEE VR and ACM CHI, and his work has been recognized with a Best Paper Honorable Mention Award at CHI 2019. He is also an active reviewer for IEEE VR and CHI, contributing to advancing these fields. From 2017 to 2023, he has successfully published 21 papers, which have been cited more than 470 times. In the first half of 2023 alone, it was cited more than 180 times. At the same time, his h-index is 12, and i10-index is 15.   In addition to his academic achievements, he has years of industry experience, particularly in the game development sector. He has also been a columnist for popular game development forums in China, where he shared his expertise and insights with fellow developers.   He has also served as a teaching assistant for various computer science courses, including Computer Games Programming, Computer Vision, Programming in C, and (Computer Architecture and Organization at UMB. These experiences have allowed him to hone his teaching skills and effectively communicate complex concepts to students.   As a co-founder and CTO of Great Victory Legends, he gained valuable experience leading technical teams and developing cutting-edge solutions. He is confident in bringing this expertise into the classroom and providing students with a comprehensive understanding of the subject matter.   He also runs his studio as a freelance and sells the tools on Unity Asset Store. The tools he develops are all about practical tools to improve development efficiency. UPython 3 Pro is his masterpiece. It provides real-time communication between Unity and Python. It was used in the research projects he was involved in. AR/VR researchers deeply love it.
Most Relevant Publications (1+)

34 total publications

Physiological responses and enjoyment of Kinect-based exergames in older adults at risk for falls: A feasibility study

Technology and Health Care / Jul 23, 2019

Ogawa, E., Huang, H., Yu, L.-F., & You, T. (2019). Physiological responses and enjoyment of Kinect-based exergames in older adults at risk for falls: A feasibility study. Technology and Health Care, 27(4), 353–362. https://doi.org/10.3233/thc-191634

See Full Profile

Denys Dutykh

Professional Applied Mathematician, Modeller, and Advisor
Most Relevant Research Expertise
Information Systems
Other Research Expertise (50)
Applied mathematics
fluid mechanics
scientific computing
numerical methods
Fluid Flow and Transfer Processes
And 45 more
About
Dr. Denys Dutykh initially comes from the broad field of Applied Mathematics. He did his Master's degree in numerical methods applied to the problems of Continuum Mechanics and a Ph.D. thesis at Ecole Normale Supérieure de Cachan (France) on the mathematical modeling of tsunami waves. After this, he was hired as a permanent research scientist at the Institute of Mathematics (INSMI) at the Centre National de la Recherche Scientifique (CNRS). His research activities have been conducted in the following years at the picturesque University Savoie Mont Blanc (USMB, France) in the field of mathematical methods applied to the modeling and simulation of nonlinear waves (mostly in Fluid Dynamics). The Habilitation thesis of Dr. Dutykh was defended there on the topic of the mathematical methods in the environment. Since then, his research interests have significantly broadened to include the Dimensionality Reduction methods in Machine Learning, modeling of PV panels, and even some more theoretical questions in the Number Theory.
Most Relevant Publications (1+)

186 total publications

Flight Trajectories Optimization of Fixed-Wing UAV by Bank-Turn Mechanism

Drones / Mar 07, 2022

Machmudah, A., Shanmugavel, M., Parman, S., Manan, T. S. A., Dutykh, D., Beddu, S., & Rajabi, A. (2022). Flight Trajectories Optimization of Fixed-Wing UAV by Bank-Turn Mechanism. Drones, 6(3), 69. https://doi.org/10.3390/drones6030069

See Full Profile

Deepak Khazanchi

Mutual of Omaha Distinguished Chair of Information Science &Technology, University of Nebraska Omaha
Most Relevant Research Expertise
Information Systems
Other Research Expertise (4)
Applied ML
Virtual Teams
Metaverses
Fairness of ML
About
Dr. Deepak Khazanchi is Mutual of Omaha Distinguished Chair of IS&T and Professor of Information Systems and Quantitative Analysis in the [College of Information Science & Technology](http://www.ist.unomaha.edu/) (IS&T), [University of Nebraska at Omaha](http://www.unomaha.edu/) (UNO). Between 2002 and 2021, he served the College of IS&T as the Associate Dean for Academic Affairs, Community Engagement and Internationalization Officer, and as the Chair of the Department of Information Systems & Quantitative Analysis. Deepak is also the Executive Director of the [Center for Management of IT](https://cmit.unomaha.edu) which focusses on applied R&D, training, and community projects. He has affiliate faculty appointments in UNO’s [International Studies & Programs](http://world.unomaha.edu/) and the [Leonard and Shirley Goldstein Center for Human Rights (GCHR)](https://www.unomaha.edu/college-of-arts-and-sciences/goldstein-center-for-human-rights/about-us/index.php). Dr. Khazanchi has served as a visiting professor and senior scholar with the Center for Integrated Emergency Management (CIEM) at the [University of Agder](http://www.hia.no/) (Kristiansand, Norway), [University of International Business & Economics](http://english.uibe.edu.cn/) (Beijing, China), [Mahindra University](https://www.mahindrauniversity.edu.in/) (Hyderabad, India), [Chiba University of Commerce](https://www.cuc.ac.jp/eng/) (Japan), [Management Center Innsbruck](https://www.mci.edu/en/) (Innsbruck, Austria), and [Murdoch University](https://www.murdoch.edu.au/) (Perth, Australia). Dr. Khazanchi is a Fulbright alum having received a Fulbright Core award for Austria (2022), and the Fulbright Specialist Grants for Norway (2014) and Japan (2023). Deepak has been instrumental in establishing multiple international collaborations for UNO with universities in Austria, Norway, Germany, Japan, India and China. He is also regularly involved as a thesis/dissertation committee member and/or external examiner for a number of graduate and PhD students at universities around the world. Dr. Khazanchi has published over 100 articles in peer-reviewed journals, books, and conferences. Over the last two decades, he has received (individually and in collaboration with others) approximately $10 million in grant funding and donations from private foundations, corporations, federal and state agencies to support his teaching, research, and community engagement activities. Deepak does applied research through a multidisciplinary lens and in the recent years has focused on areas such as applied ML in SHM, perceived fairness of AI/ML systems, Decent Work and the ICT Profession, Metaverse Technology Capabilities, Virtual Project Management, Fast Response Virtual Teams for Crisis Management, mhealth interventions, Risk analysis in extended enterprise environments, Mixed Research Methods, and the application of philosophy of science in computing disciplines.  His research has been published in both practitioner and peer-reviewed journals including the following: *International Journal of Information* *Management (IJIM), International Journal of IT Project Management (IJITPM), IEEE Access, Structural Health Monitoring (SHM), AIS Transactions on Human-Computer Interaction (THCI), Current Opinion in Neurology, Journal of Gerontological Nursing, Journal of Information Systems (JIS), The ISACA Journal*, *Journal of Information Technology Case and Application Research (JITCAR)*, *Communications of the Association of Information Systems* (CAIS), *Journal of the Association of Information Systems* (JAIS), *Electronic Markets, Decision Support Systems*, *Information Systems Management*, *Journal of Information Technology Management*, *ACM’s DATA BASE for Advances in Information Systems*, *Journal of Computer Information Systems*, *American Journal of Business,* and *Information Processing and Management*. He has also presented his research at a number of national/international/regional peer-reviewed conferences. Dr. Khazanchi has also given practitioner-oriented talks & conducted workshops for companies and organizations in the USA, India and Norway on a variety of topics including: “Role of Digitalization and Digital Transformation to achieve Resiliency during Supply Chain Disruptions”; “Fast Response Virtual Teams During Crisis”; “Beyond Innovation: Using Transformative Thinking as a part of our Daily Work”; “Virtual Teams & Project Management”; “Best Practices in IT Project Management”; “Politics of Project Management”; and “Patterns of Effective Virtual Project Management.” Dr. Khazanchi has been engaged in collaborative interactions with the business and nonprofit community through various R&D projects, service to the IT profession, and community service at the regional, national and international levels. Two of his community projects, [CodeCrush](https://codecrush.unomaha.edu) and iSTEM After School have celebrated their 10th year in 2024. He was one of the founding board members, served as chairman, and currently continues to serve on the board of directors of the nonprofit, [Collective for Youth](https://www.collectiveforyouth.org/) in Omaha. Deepak has also served on several other community boards including as a Trustee for the [Brownell Talbot Preparatory School](http://www.brownell.edu/), member of the Board of [Refugee Empowerment Center in Omaha](https://refugeeempowerment.org), and [Benson Theater](https://bensontheatre.org). He has served on the Board of Management for the [Sir Padmpat Singhania University](https://www.spsu.ac.in/) (Udaipur, India), the Executive Council for [Bennett University](http://www.bennettuniversity.com/) (NOIDA, India), and the Planning and Monitoring Board of the [JSS Academy of Higher Education and Research](https://jssuni.edu.in/JSSWeb/WebHome.aspx) (Mysuru, India). Deepak was one of the founding members and has served as the President/President-elect of the [Midwest Association of Information Systems, ](https://www.mwais.org)AMCIS representative member of the [Association of Information Systems](https://www.aisnet.org) Council, and the Chair of the AMCIS Site Advisory committee.  Dr. Khazanchi is the founder and first President of the Association for Information Systems (AIS) [Special Interest Group for IT Project Management](https://aisnet.org/members/group.aspx?id=89773). He has served as the conference general chair and/or co-chair of multiple international and regional conferences including hosting the [2023 Information for Crisis Response & Management Global Conference](https://iscram2023.net) (May 27-31,2023), 2022 MWAIS Conference, 2022 VINC (Vivekananda Institute National Conference), 2020 ACM SIGITE Conference, 2016 [Brain Informatics and Health (BIH 201)](https://www.springer.com/gp/book/9783319471020) conference, 2020 [ACM’s Special Interest Group in IT Education (SIGITE)](https://www.unomaha.edu/college-of-information-science-and-technology/sigite2020/index_page.php) conference, 2015 International Conference on Advances in Management and Technology in a Global World (ICAMT-2015), 2005 [Americas Conference in Information Systems (AMCIS),](http://aisnet.org/?AMCISPage) and the 2007 IEEE [International Conference on Data Mining (ICDM)](https://dblp.org/db/conf/icdm/icdm2007.html). Deepak has also served as the VP of Programs for the [Project Management Institute’s (PMI) Heartland Chapter](https://pmiheartland.org/). Dr. Khazanchi is an [AIS Distinguished Member – Cum Laude](https://aisnet.org/page/DistinguishedMemberList#k) and a Fellow of the [IAITQM (International Academy of Information Technology and Quantitative Management)](http://iaitqm.org/fellows.html).  Deepak has been recognized as the [Nebraska Tech Collaborative as one of their 2024 PIONEERS](https://www.linkedin.com/posts/nebraska-tech-collaborative_ntcpioneers-activity-7133808994401357824-gpQV) and received the 2024 [AIM Institute’s Higher Education Technology Leader Award.](https://www.aimtechawards.org/)[DAA 2024 (Khazanchi)](https://dkhazanchi.wordpress.com/wp-content/uploads/2025/01/daa-2024-khazanchi.pdf "DAA 2024 (Khazanchi)") His undergraduate alma mater, [IIT Kharagpur](https://www.iitkgp.ac.in/), honored him with the Distinguished Alumnus Award (DAA) in its commencement held on December 30th 2024. The [DAA](https://dkhazanchi.wordpress.com/about-2/bio/_wp_link_placeholder) recognizes the “professional achievements and contributions of its alumni” ([DAA 2024 Khazanchi)](https://dkhazanchi.wordpress.com/wp-content/uploads/2025/01/daa-2024-khazanchi.pdf "DAA 2024 (Khazanchi)"). Deepak arrived in academics after working in managerial and technical positions with responsibility for designing structures (bridges and buildings) and as a project engineer for a multinational construction project.  He received the Ph.D. degree in Business Administration with a specialization in Management Information Systems from [Texas Tech University](http://www.ttu.edu/). Prior to this, he earned the MBA degree from [Southern Illinois University at Carbondale](http://www.siuc.edu/) and obtained an undergraduate degree in Civil Engineering from the [Indian Institute of Technology (IIT), Kharagpur](https://www.iitkgpfoundation.org/index.html) (India). He can be reached via e-mail at [[email protected]](mailto:%[email protected]), his “web presence” is at [https://dkhazanchi.com/](https://dkhazanchi.com/) and @khazanchi on twitter. He is [living his dream](https://web.archive.org/web/20220701234428/https://www.unomaha.edu/college-of-information-science-and-technology/news/2006/12/living-his-dream.php) as an academic and enjoys any free time he has with his family and traveling.

See Full Profile

Example Information Systems projects

How can companies collaborate more effectively with researchers, experts, and thought leaders to make progress on Information Systems?

Optimizing Supply Chain Management

An academic researcher in Information Systems can help companies optimize their supply chain management processes. By analyzing data and implementing advanced algorithms, researchers can identify bottlenecks, reduce costs, and improve overall efficiency.

Enhancing Cybersecurity Measures

With the increasing threat of cyber attacks, companies can benefit from collaborating with an academic researcher in Information Systems to enhance their cybersecurity measures. Researchers can develop innovative solutions, conduct vulnerability assessments, and provide recommendations to strengthen the company's security infrastructure.

Implementing Data Analytics Strategies

Data analytics is crucial for companies to make informed business decisions. An academic researcher in Information Systems can help companies implement data analytics strategies by developing predictive models, analyzing large datasets, and providing insights that can drive business growth.

Designing User-Friendly Interfaces

User experience is a key factor in the success of digital products and services. By collaborating with an academic researcher in Information Systems, companies can benefit from expertise in designing user-friendly interfaces. Researchers can conduct usability studies, gather user feedback, and optimize the user experience to enhance customer satisfaction.

Integrating Emerging Technologies

Emerging technologies such as artificial intelligence, blockchain, and Internet of Things (IoT) have the potential to transform industries. Academic researchers in Information Systems can help companies explore and integrate these technologies into their existing systems, enabling them to innovate and gain a competitive edge.