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Work with thought leaders and academic experts in Artificial Intelligence

Companies can benefit from working with experts in Artificial Intelligence in various ways. These researchers can help develop and implement AI solutions to improve efficiency, automate processes, and enhance decision-making. They can also assist in data analysis and predictive modeling to identify patterns and trends. Additionally, AI researchers can provide insights and recommendations for optimizing business strategies and customer experiences. By collaborating with these experts, companies can gain a competitive edge, drive innovation, and achieve their business goals.

Researchers on NotedSource with backgrounds in Artificial Intelligence include Dr. Andrew Raij, Ph.D., IQRAM HUSSAIN, Ph.D., Ping Luo, Tyler Streeter, Dr. Wolfgang Messner, Nicolangelo Iannella, Keiran Thompson, Christos Makridis, David J. Hamilton, PhD, ENG. BRYAN ASEGA, Artem Timoshenko, Ph.D., Dr. Charles Lassiter, Ph.D., and Professor(Dr) Sanjay Rout.

Dr. Andrew Raij, Ph.D.

Orlando, Florida, United States of America
Principal Research Scientist and Lab Director | VR, AR, MR, XR, Spatial Computing, Immersive Technologies
Most Relevant Research Expertise
Artificial Intelligence
Other Research Expertise (13)
Human-Computer Interaction
Virtual Reality
Augmented Reality
Human Factors and Ergonomics
Modeling and Simulation
And 8 more
About
Dr. Andrew Raij, Ph.D. is a principal researcher at the Charles Stark Draper Laboratory, where he leads research on human-centered computing and virtual / augmented / mixed reality. For over 20 years, Dr. Raij has been helping companies unlock the transformative power of immersive technologies through **rigorous user research, strategic guidance, and creative problem-solving**. With a deep understanding of human behavior in immersive environments, he bridges the gap between cutting-edge technology and real-world needs. His career began in academia, where he was an Assistant Professor and Director of the Powerful Interactive Experiences (PIE) Lab at the University of South Florida. Later, he joined Universal Creative, where he applied his expertise to the challenge of using immersive, wearable technologies in the theme park environment. At Draper Labs, his research focuses on applying immersive technologies to training and situational awareness. Dr. Raij earned his Ph.D. in the Department of Computer & Information Science & Engineering from the University of Florida in 2009. Prior to this, he completed his M.S. in Computer Science at the University of North Carolina at Chapel Hill in 2003 and his B.S. in Computer Science at Northwestern University in 2001.
Most Relevant Publications (1+)

54 total publications

A Large-Scale Study of Surrogate Physicality and Gesturing on Human–Surrogate Interactions in a Public Space

Frontiers in Robotics and AI / Jul 07, 2017

Kim, K., Nagendran, A., Bailenson, J. N., Raij, A., Bruder, G., Lee, M., Schubert, R., Yan, X., & Welch, G. F. (2017). A Large-Scale Study of Surrogate Physicality and Gesturing on Human–Surrogate Interactions in a Public Space. Frontiers in Robotics and AI, 4. https://doi.org/10.3389/frobt.2017.00032

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IQRAM HUSSAIN, Ph.D.

New York City, New York, United States of America
Weill Cornell Medicine, Cornell University, NY, USA
Most Relevant Research Expertise
Artificial Intelligence
Other Research Expertise (32)
Biomedical & Medical Physics
AI (Machine & Deep Learning)
Anesthesiology
Sleep Medicine
Human Gait & brain
And 27 more
About
Iqram Hussain works at the Department of Anesthesiology, Weill Cornell Medicine, Cornell University, NY, USA. Earlier, he was a postdoctoral researcher at the Medical Research Center, Department of Biomedical Engineering, Seoul National University. He pursued a Ph.D. degree in Medical Physics from the University of Science and Technology (UST), South Korea. He worked as a Research Associate with the Korea Research Institute of Standards and Science (KRISS), Daejeon, South Korea. He worked on the Knowledgebase Super Brain (KSB) project at the Electronics and Telecommunication Research Institute (ETRI), Daejeon. He received a B.Sc. degree in mechanical engineering from the Khulna University of Engineering & Technology, Bangladesh, in 2007. He has ten years of work experience in power plant operation and maintenance and power plant project management. His research interests include wearable sleep monitoring, neuroscience, medical physics, human factors, and ergonomics. He has experience in healthcare research, project management, power plant operation, and maintenance. He is a reviewer in IEEE Access, Sensors, Applied Sciences, Biomedical Signal Processing and Control, IEEE Transactions, Science of the Total Environment, Neuroscience Informatics, Brain Sciences, etc. He is a guest editor in special issues of several Journals. Website: https://sites.google.com/view/iqram/home
Most Relevant Publications (1+)

43 total publications

Tracking Trajectory Planning of Space Manipulator for Capturing Operation

International Journal of Advanced Robotic Systems / Sep 01, 2006

Huang, P., Xu, Y., & Liang, B. (2006). Tracking Trajectory Planning of Space Manipulator for Capturing Operation. International Journal of Advanced Robotic Systems, 3(3), 31. https://doi.org/10.5772/5735

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Ping Luo

Toronto, Ontario, Canada
Bioinformatics Specialist at Princess Margaret Cancer Centre with experience in deep learning
Most Relevant Research Expertise
Artificial Intelligence
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

CASNMF: A Converged Algorithm for symmetrical nonnegative matrix factorization

Neurocomputing / Jan 01, 2018

Tian, L.-P., Luo, P., Wang, H., Zheng, H., & Wu, F.-X. (2018). CASNMF: A Converged Algorithm for symmetrical nonnegative matrix factorization. Neurocomputing, 275, 2031–2040. https://doi.org/10.1016/j.neucom.2017.10.039

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Tyler Streeter

Iowa City, Iowa, United States of America
Theoretical Machine Learning / Statistics Researcher: Bayes, Information Theory, Boltzmann Machines
Most Relevant Research Expertise
artificial intelligence
Other Research Expertise (43)
machine learning
undirected graphical models
Boltzmann machines
Markov random fields
Ising models
And 38 more
About
I am a researcher and software engineer focused on making machine learning simpler, more general, and more effective. Having spent many years studying a wide range of existing models and algorithms, I now work on deriving new methods from elegant theoretical principles. I enjoy writing clean code and simple APIs, designing data visualizations to gain intuition about new domains, simulating physical processes with unexpected emergent behavior, building tangible objects from humble materials, and capturing big ideas with small math. My ideal project is one that lets me be a scientist, artist, and engineer.

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Dr. Wolfgang Messner

Columbia, SC
Professor in International Business with expertise in Data Analytics and Machine Learning
Most Relevant Research Expertise
Artificial Intelligence
Other Research Expertise (14)
International Business
International Marketing
International Management
Strategy and Management
Business and International Management
And 9 more
About
Results-oriented and internationally experienced project manager, consultant, and researcher with a passion for leveraging machine learning and advanced statistical techniques to solve intricate challenges in international marketing and consumer behavior. Demonstrated track record of driving strategic initiatives, cultivating cross-border partnerships, and delivering tangible impacts on revenue generation. Highly adaptable to rapidly evolving technologies and market trends. Aiming to apply my expertise to lead transformative projects and elevate organizational success on a global scale. **Research and publication overview** · Authored 36 peer-reviewed journal publications (data analytics, international business, marketing) · Authored and edited 8 business books, published by *Palgrave Macmillan* and *Springer* · Published 5 teaching cases with *SAGE* and *Ivey* · Research impact (Google Scholar): h-index of 17 with 1,000+ citations **Competences in data analysis (selected)** · Supervised: Neural networks, deep learning · Unsupervised: Kohonen self-organizing maps · Frequentist and Bayesian regression analysis · Multilevel (hierarchical) modeling · Exploratory and confirmatory factor analysis · fs/QCA \| HLM \| SPSS \| JASP \| Python\, incl\. Keras\, Dalex
Most Relevant Publications (1+)

65 total publications

Improving the cross-cultural functioning of deep artificial neural networks through machine enculturation

International Journal of Information Management Data Insights / Nov 01, 2022

Messner, W. (2022). Improving the cross-cultural functioning of deep artificial neural networks through machine enculturation. International Journal of Information Management Data Insights, 2(2), 100118. https://doi.org/10.1016/j.jjimei.2022.100118

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Nicolangelo Iannella

Oslo
Senior Research fellow, The University of Oslo, Faculty of Mathematics and Natural Sciences
Most Relevant Research Expertise
Artificial Intelligence
Other Research Expertise (18)
Neuromorphic circuits
Neural networks, Neural learning and applications
Theoretical and Mathematical neuroscience
Computational neuroscience
Cognitive Neuroscience
And 13 more
About
Following pre-doctoral studies in Mathematics and Theoretical Physics, I received a PhD in Computational Neuroscience from the University of Electro-Communications, Japan in 2009. From 2009, I was a Postdoctoral Researcher in RIKEN BSI. In 2010, I won the prestigious Australian Research Council (ARC) Australian Postdoctoral Award (APD) fellowship, based at the University of Adelaide from 2010–2014. In 2012 he completed a Graduate Certificate in Education (Higher Education) (GCEHE) from the University of Adelaide. From 2014–2017 he was an adjunct research fellow at the University of South Australia. From 2016–2018, he was a Cascade (Marie Curie) Research Fellow in Mathematical Sciences at the University of Nottingham. From 2018- a research fellow at the University of Oslo. His research interests include AI, Artificial and spiking neural networks and learning algorithms, synaptic plasticity, neuronal dynamics, and neuromorphic engineering. Dr. Iannella is a member of SFN and a Senior member of the IEEE.
Most Relevant Publications (2+)

47 total publications

A spiking neural network architecture for nonlinear function approximation

Neural Networks / Jul 01, 2001

Iannella, N., & Back, A. D. (2001). A spiking neural network architecture for nonlinear function approximation. Neural Networks, 14(6–7), 933–939. https://doi.org/10.1016/s0893-6080(01)00080-6

A neuromorphic VLSI design for spike timing and rate based synaptic plasticity

Neural Networks / Sep 01, 2013

Rahimi Azghadi, M., Al-Sarawi, S., Abbott, D., & Iannella, N. (2013). A neuromorphic VLSI design for spike timing and rate based synaptic plasticity. Neural Networks, 45, 70–82. https://doi.org/10.1016/j.neunet.2013.03.003

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Keiran Thompson

Palo Alto, California, United States of America
Stanford University
Research Expertise (6)
Physical and Theoretical Chemistry
Colloid and Surface Chemistry
Biochemistry
Catalysis
Computer Science Applications
And 1 more
About
Keiran Thompson is a machine learning and quantum chemistry researcher. Originally from Australia, he currently works as an AI research scientist at Stanford University where he transfers machine learning knowledge from the private sector to academic research which can then be reconverted back to private sector usage. He is experienced with large scale numerical computing and has led several startups as Chief Scientist.

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Christos Makridis

Nashville, TN
Web3 and Labor Economist in Academia, Entrepreneurship, and Policy
Research Expertise (16)
Finance
Economics and Econometrics
Accounting
Pharmacology (medical)
Law
And 11 more
About
Christos A. Makridis holds academic appointments at Columbia Business School, Stanford University, Baylor University, University of Nicosia, and Arizona State University. He is also an adjunct scholar at the Manhattan Institute, senior adviser at Gallup, and senior adviser at the National AI Institute in the Department of Veterans Affairs. Christos is the CEO/co-founder of [Dainamic](https://www.dainamic.ai/), a technology startup working to democratize the use and application of data science and AI techniques for small and mid sized organizations, and CTO/co-founder of [Living Opera](https://www.livingopera.org/), a web3 startup working to bridge classical music and blockchain technologies. Christos previously served on the White House Council of Economic Advisers managing the cybersecurity, technology, and space activities, as a Non-resident Fellow at the Cyber Security Project in the Harvard Kennedy School of Government, as a Digital Fellow at the Initiative at the Digital Economy in the MIT Sloan School of Management, a a Non-resident Research Scientist at Datacamp, and as a Visiting Fellow at the Foundation for Defense of Democracies. Christos’ primary academic research focuses on labor economics, the digital economy, and personal finance and well-being. He has published over 70 peer-reviewed research papers in academic journals and over 170 news articles in the press. Christos earned a Bachelor’s in Economics and Minor in Mathematics at Arizona State University, as well a dual Masters and PhDs in Economics and Management Science & Engineering at Stanford University.

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David J. Hamilton, PhD

Fairfax, Virginia, United States of America
PhD Neuroscience focused on computational modeling of biologically plausible neuronal circuits.
Most Relevant Research Expertise
Artificial Intelligence
Other Research Expertise (5)
Cognitive Neuroscience
Biomedical Engineering
Cellular and Molecular Neuroscience
Modeling and Simulation
Machine Learning
About
David J. Hamilton, PhD Neuroscience, GMU, 2016. His current research focus is Efficient Generative AI leveraging biologically plausible computational circuits and spiking neural networks to implement transformer-based algorithms. Dr. Hamilton has extensive R&D experience in Generative AI and Machine Learning capability development. Specific projects include transformer-based LLM sensor parameter tuning, analytic prediction, Cyber Threat Analysis Platform R&D, US Treasury cyber defense, credit card fraud detection, sensor fusion/analysis, LIDAR signal characterization, and active/passive sonar signal detection/classification. Companies for which David has worked include Intelligent Mission Consulting Services (2020-2023), Northrop Grumman (2004-2020), NeuralTech/CardSystems (1994-2004), Raytheon (1980-1994), and AAI (1977-1980). Earlier in his career, David received his MSEE (1981) from Loyola University, Maryland, and his BSEE (1977) from PSU. He is well published, holds memberships in Society for Neuroscience (SfN), AAAS, IEEE, and continues to maintain his association with GMU as an Affiliate Faculty.
Most Relevant Publications (1+)

14 total publications

Self-sustaining non-repetitive activity in a large scale neuronal-level model of the hippocampal circuit

Neural Networks / Oct 01, 2008

Scorcioni, R., Hamilton, D. J., & Ascoli, G. A. (2008). Self-sustaining non-repetitive activity in a large scale neuronal-level model of the hippocampal circuit. Neural Networks, 21(8), 1153–1163. https://doi.org/10.1016/j.neunet.2008.05.006

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ENG. BRYAN ASEGA

Nairobi
Software Engineer - Python, PHP, AI Developer, Web3 | Geologist - Seismology, Stratigraphy, Hydrogeologist
Most Relevant Research Expertise
Artificial Intelligence
Other Research Expertise (5)
Seismology
Hydrogeology
Blockchain
Stratigraphy
DevOps
About
I am a Full-Stack Software Engineer with 3 years of Industrial development experience. I am also a graduate Geologist with 1 year of experience in Hydrogeology, Stratigraphy, and Seismology. I am currently innovating the use of Blockchain Technology, Python, and Machine Learning in Stratigraphy, Hydrogeology, and Seismology.

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Artem Timoshenko, Ph.D.

Chicago, Illinois, United States of America
Professor at Kellogg School of Management
Most Relevant Research Expertise
Artificial Intelligence
Other Research Expertise (3)
Marketing
Management
Innovation
About
I am a Professor of Marketing at Kellogg School of Management at Northwestern University. My research and consulting focus on the business applications of AI, including innovation, product management, marketing, and sales. Happy to collaborate!

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Dr. Charles Lassiter, Ph.D.

Spokane, Washington, United States of America
Associate professor of philosophy with publications on mind, language, knowledge, and culture
Most Relevant Research Expertise
Artificial Intelligence
Other Research Expertise (12)
philosophy of mind
embodied cognition
extended cognition
philosophy of language
social psychology
And 7 more
About
My research is at the intersection of mind, technology, and culture. I regularly publish on topics including: 1\. embodied and encultured cognition 2\. computational models of reasoning 3\. epistemology of expertise Outside of my publishing work, I have taught philosophy at the undergraduate and graduate levels since 2015. My other professional role includes helping other humanists be more public-facing in their own research. Finally, I gather and analyze data from the philosophy job market on my blog: https://charleslassiter.weebly.com/blog
Most Relevant Publications (1+)

22 total publications

Could a robot flirt? 4E cognition, reactive attitudes, and robot autonomy

AI & SOCIETY / Jan 02, 2021

Lassiter, C. (2021). Could a robot flirt? 4E cognition, reactive attitudes, and robot autonomy. AI & SOCIETY, 37(2), 675–686. https://doi.org/10.1007/s00146-020-01116-6

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Professor(Dr) Sanjay Rout

Delhi
Industry Expert Dr. Sanjay - Former Honorary Chancellor, Leading Chair Professor and Advisory Consultant for Research and Development Forums.
Most Relevant Research Expertise
Artificial Intelligence
Other Research Expertise (14)
HealthScience
Technology
Management
Law
Journalism
And 9 more
About
Dr. Sanjay Rout is an experienced professor and business professional with a diverse educational background. He holds a Ph.D in Management from Magadh University, as well as a PGDSCM in Management from the Institute of management technology. In addition, he has also completed a LLB in Law and an MBA in Management. Dr. Rout's expertise lies in the field of Business Analytics, which he studied at The Wharton Business School. He has also gained valuable experience through his various roles in the business world, including serving as the Chancellor at Mahavideha University, CEO at Innovation Solution Lab, and COO at ISL PUBLICATIONS. Dr. Rout is also involved in various organizations and serves on the Board of Directors at Spiritual Data. He has also worked as a consultant for companies such as NISG, Ernst and Young LLP, Pwc and Sutra PMU, and CAEMAS. With his extensive education and experience, Dr. Sanjay Rout is a highly knowledgeable and respected professor in the field of Business Analytics.
Most Relevant Publications (1+)

32 total publications

The Application of Interactive Humanoid Robots in the History Education of Museums Under Artificial Intelligence

International Journal of Humanoid Robotics / Nov 21, 2022

Yang, K., & Wang, H. (2022). The Application of Interactive Humanoid Robots in the History Education of Museums Under Artificial Intelligence. International Journal of Humanoid Robotics, 20(06). https://doi.org/10.1142/s0219843622500165

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Example Artificial Intelligence projects

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

AI-powered Customer Service Chatbot

An AI researcher can develop a chatbot that uses natural language processing and machine learning algorithms to provide personalized customer support. This chatbot can handle customer inquiries, resolve issues, and even make product recommendations, improving customer satisfaction and reducing the workload of customer service teams.

Automated Fraud Detection System

By collaborating with an AI researcher, companies can build an automated fraud detection system that analyzes large volumes of data in real-time. This system can identify suspicious patterns and anomalies, flagging potential fraudulent activities and minimizing financial losses.

Predictive Maintenance for Manufacturing

An AI expert can develop predictive maintenance models that leverage machine learning algorithms to analyze sensor data from manufacturing equipment. By predicting equipment failures in advance, companies can schedule maintenance activities, reduce downtime, and optimize production efficiency.

AI-powered Marketing Campaign Optimization

Working with an AI researcher, companies can optimize their marketing campaigns using AI techniques. These researchers can analyze customer data, segment audiences, and recommend personalized content and targeting strategies to maximize campaign effectiveness and ROI.

AI-driven Supply Chain Optimization

Collaborating with an AI expert can help companies optimize their supply chain operations. These researchers can develop AI models to analyze historical data, predict demand, optimize inventory levels, and streamline logistics, leading to cost savings and improved operational efficiency.