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. Pantaleon Fassbender, ENG. BRYAN ASEGA, Artem Timoshenko, Ph.D., Dr. Antonio Pagliaro, Ph.D., Dawn Hancock, Ping Luo, Tyler Streeter, Dr. Andrew Raij, Ph.D., Dr. Vartenie Aramali, Ph.D., Keiran Thompson, Christos Makridis, Dr. Wolfgang Messner, Nicolangelo Iannella, and IQRAM HUSSAIN, Ph.D..

Dr. Pantaleon Fassbender

Gainesville, Florida, United States of America
28 Years Experience
Highly experienced global leadership and corporate health management advisor
Education

Rheinische Friedrich-Wilhelms-Universität Bonn

Th.D., Theological Ethics / March, 1995

Bonn

Rheinische Friedrich-Wilhelms-Universität Bonn

M.Sc., Psychology / May, 1993

Bonn

Rheinische Friedrich-Wilhelms-Universität Bonn

M.A., Theology / February, 1990

Bonn
Experience

Twisters Management Consulting LLC

Managing Director / November, 2019Present

International L&D and training expert. Leadership and data science advisor. Corporate Health Management for global clients

Kambs Consulting

Director / July, 2010Present

KPMG

Senior Manager / September, 1999June, 2010

Manager/ Senior Manager with the Service Lines Forensic Services and Restructuring

Most Relevant Research Expertise
Artificial Intelligence
Other Research Expertise (8)
Applied Psychology
Communication
Experimental and Cognitive Psychology
Human-Computer Interaction
Philosophy
And 3 more
About
With over 25 years of experience in corporate health management, talent management, and crisis management consulting, I am passionate about helping leaders and organizations overcome challenges and achieve their goals. As a Managing Director at Twisters Management Consulting LLC, I leverage my expertise in evidence-based management, applied psychology, data storytelling, and analytical skills to provide innovative and effective solutions for my clients. One of my unique offerings is horse-assisted coaching, which is a powerful and experiential method to enhance personal and professional development. By working with a horse and a coach on the ground, clients can gain insights into their body language, communication style, emotional intelligence, and leadership presence. I also specialize in personality assessment-at-a-distance, which is a valuable tool for due diligence, ghost negotiation, fraud investigation, and other high-stakes situations. Additionally, I have a strong background in investigative psychology and forensics, which enables me to apply behavioral analysis and profiling techniques to various security contexts.
Most Relevant Publications (1+)

7 total publications

Application of artificial intelligence: risk perception and trust in the work context with different impact levels and task types

AI & SOCIETY / Jun 02, 2023

Klein, U., Depping, J., Wohlfahrt, L., & Fassbender, P. (2023). Application of artificial intelligence: risk perception and trust in the work context with different impact levels and task types. AI & SOCIETY. https://doi.org/10.1007/s00146-023-01699-w

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Ping Luo

Toronto, Ontario, Canada
8 Years Experience
Assistant Professor at Algoma University
Education

University of Saskatchewan

Ph.D., Biomedical Engineering / September, 2019

Saskatoon, Saskatchewan, Canada

Beijing Institute of Technology

M.Eng., Biomedical Engineering / June, 2015

Beijing

Hunan University

B.Eng., Computer Science / June, 2010

Changsha
Experience

Princess Margaret Cancer Centre

Postdoctoral Researcher / November, 2019Present

I work in Dr. Trevor Pugh's lab and design cancer diagnosis and treatment strategies by analyze cell-free DNA and single cell sequencing data

Princess Margaret Cancer Centre

Bioinformatics Specialist / September, 2023Present

I work in Dr. Tak Mak's lab and study tumor immunology using single cell and TCR sequencing data.

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
21 Years Experience
Theoretical Machine Learning / Statistics Researcher: Bayes, Information Theory, Boltzmann Machines
Education

Iowa State University

PhD (ABD), Machine Learning / May, 2024 (anticipated)

Ames, Iowa, United States of America

Iowa State University

MS, Reinforcement Learning, Computer Graphics / December, 2005

Ames, Iowa, United States of America

Iowa State University

BS, Computer Engineering / May, 2004

Ames, Iowa, United States of America
Experience

Brainpower Labs

Machine Learning Researcher / October, 2008Present

• Pure AI/ML research and software development. • AI research/development contract with SRAM. • Derived math results (currently 6,500 pages of notes), and designed new learning algorithms involving probabilistic graphical models, Bayesian methods, and information theory. • Built internal software tools in C/C++ and Python to aid research, including interactive visualizations of machine learning and Monte Carlo sampling algorithms. • Designed a novel brain-inspired architecture for artificial general intelligence, and implemented it in in C++ and Python with interactive debugger and test environments. • Developed commercial software to fund research agenda, including iBonsai, a meditative interactive 3D tree simulation in C++ for iOS (120k users). • Graphics engineering contract with Avatree (custom generative 3D tree growth algorithm and glTF exporter in C).

VR Applications Center, Iowa State University

AI/ML Graduate Researcher / August, 2006December, 2009

• Performed independent research on topographic maps, maximum entropy learning algorithms, Bayesian networks, reinforcement learning, and systems neuroscience. • Developed open source C++ libraries for unit testing, profiling, and parallel programming.

IBM Research

Computational Neuroscience Research Intern / May, 2006August, 2006

• Implemented a novel computational model of the cerebellum. • Demonstrated motor learning and transfer of complex reaching behaviors with a simulated 6-muscle arm. • Participated in discussions of global brain modeling and information theoretic learning rules.

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. Andrew Raij, Ph.D.

Orlando, Florida, United States of America
20 Years Experience
Principal Research Scientist and Lab Director | VR, AR, MR, XR, Spatial Computing, Immersive Technologies
Education

University of Florida

Ph.D., Dept. of Computer & Info. Science & Engineering / May, 2009

Gainesville, Florida, United States of America

University of North Carolina at Chapel Hill

M.S., Computer Science / December, 2003

Chapel Hill, North Carolina, United States of America

Northwestern University

B.S., Computer Science / June, 2001

Evanston, Illinois, United States of America
Experience

Draper Laboratory

Principal Member of Technical Staff / January, 2021Present

Universal Studios / NBCUniversal

Technical Program Manager / December, 2016November, 2020

University of Central Florida

Research Associate Professor / March, 2015September, 2016

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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Christos Makridis

Nashville, TN
10 Years Experience
Web3 and Labor Economist in Academia, Entrepreneurship, and Policy
Education

Stanford University

Dual Ph.D., Economics and Management Science & Engineering / June, 2018

Stanford, California, United States of America

Arizona State University

B.S., Economics and Mathematics / May, 2012

Tempe, Arizona, United States of America
Experience

Stanford University

Digital Fellow / August, 2020Present

Department of Veterans Affairs

Senior Adviser, National AI Institute / January, 2020Present

Columbia Business School

Adjunct Associate Research Scholar / February, 2022Present

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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Dr. Wolfgang Messner

Columbia, SC
29 Years Experience
Professor in International Business with expertise in Data Analytics and Machine Learning
Education

University of Kassel

Dr. rer. pol., Economics and social sciences / 2004

Kassel

University of Wales

M.B.A., Financial management / 1998

Cardiff

Technical University Munich

B.Sc. & M.Sc. (Dipl.-Inform. Univ.), Computer science; artificial intelligence; computer graphics / 1995

Munich
Experience

University of South Carolina, Darla Moore School of Business | Columbia, SC, USA

Clinical Professor of International Business / 2016Present

• Developed novel algorithms for eXplainable Artificial Intelligence (XAI). Leveraged machine learning and deep learning techniques to address research questions in international business and marketing • Utilized advanced statistical approaches to assess cultural diversity and differences across regions and populations • Investigated variations in the impact of the COVID-19 pandemic on public health systems and consumer behavior • Taught under- and postgraduate courses in the #1-ranked international business department, as recognized by US News & World Report. Courses include data analytics, management consulting, and intercultural team management • Engaged in collaborative student consulting projects with companies such as Positec, SC SBDC, Seabin Australia, Thomson Reuters, UPS Global Supply Chain Solutions (Data & Innovation), and UPS International

MYRA School of Business | Mysore, India

Professor of International Management / 20132016

• Analyzed cultural differences in consumer behavior with a focus on the effectiveness of marketing strategies • Formulated strategic initiatives for conducting business in emerging markets • Taught postgraduate courses on customer service, business case analysis, and international business

GloBus Research | London, UK & Bangalore, India

Co-founder & Director / 20112017

• Developed customized learning solutions for executives • Created assessment tools to evaluate intercultural communication competence and team effectiveness • Led the design and delivery of the India module within the prestigious Leadership Excellence Program offered collaboratively by WHU, IDG, and DXC Technology

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
6 Years Experience
Senior Research fellow, The University of Oslo, Faculty of Mathematics and Natural Sciences
Education

University of Adelaide

Graduate Certificate in Education (Higher Education) , School of Electrical & Electronic engineering / December, 2012

Adelaide, South Australia, Australia

Denki Tsushin Daigaku

PhD (Eng), Information and Communications Engineering / March, 2009

Chofu
Experience

University of Oslo

Postdoctoral Fellow / July, 2018Present

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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IQRAM HUSSAIN, Ph.D.

New York City, New York, United States of America
7 Years Experience
Weill Cornell Medicine, Cornell University, NY, USA
Education

Korea University of Science and Technology

Doctor of Philosophy, Medical Physics / February, 2022

Daejeon

Khulna University of Engineering and Technology

Bachelor of Science, Mechanical Engineering / April, 2007

Khulna
Experience

Weill Cornell Medicine

Postdoctoral Associate / March, 2023Present

Seoul National University

Postdoctoral Fellow / March, 2022February, 2023

Korea Research Institute of Standards and Science

PhD Researcher / September, 2017February, 2022

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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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.