Work with thought leaders and academic experts in automotive engineering

Companies can greatly benefit from collaborating with academic researchers in the field of Automotive Engineering. These experts bring a deep understanding of automotive technologies, industry trends, and innovative solutions. By working with them, companies can gain access to cutting-edge research, advanced engineering techniques, and specialized knowledge. They can provide valuable insights and recommendations for improving vehicle performance, fuel efficiency, safety, and sustainability. Academic researchers can also assist in developing new technologies, conducting feasibility studies, and optimizing manufacturing processes. Their expertise can help companies stay ahead of the competition, enhance product quality, reduce costs, and drive innovation in the automotive industry.

Researchers on NotedSource with backgrounds in automotive engineering include Jim Samuel, Emmanuel Iarussi, Steve Efe, Konstantinos Tsavdaridis, Milad Hosseinpour, Denys Dutykh, Athul Prasad, Irma Kuljanishvili, Jean Twenge, Diego Bestel, and Mohamad (Moe) El Hariri.

Jim Samuel

Associate Professor at Rutgers University
Most Relevant Research Expertise
Automotive Engineering
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 (1+)

44 total publications

They Are Not Mistaken! Why Passive Investments Matter

Journal of Management Policy and Practice / Nov 01, 2018

They Are Not Mistaken! Why Passive Investments Matter. (2018). Journal of Management Policy and Practice, 19(4). https://doi.org/10.33423/jmpp.v19i4.192

See Full Profile

Milad Hosseinpour

Ph.D. Mechanical Engineer with 7 years of expertise in precision metrology
Most Relevant Research Expertise
Automotive Engineering
Other Research Expertise (13)
Optical Metrology
Gear Metrology and Inspection
Nano-composite Material
FEM
Structural Optimization
And 8 more
About
Innovative and detail-oriented Ph.D. Mechanical Engineer with 7 years of expertise in precision measurements, dimensional metrology, and manual inspection equipment. Proficient in CMM programming, 3D CAD (Solidworks, ANSYS, HyperMesh), and Vision Inspection Systems. Recognized for innovative problem-solving skills, meticulous attention to detail, and effective team leadership. Specialized in GD&T, GR&R, and Calibration Systems. Ready to contribute a comprehensive skillset and a quality-oriented approach to a dynamic role.
Most Relevant Publications (2+)

9 total publications

Free vibration analysis of an electro-elastic GPLRC cylindrical shell surrounded by viscoelastic foundation using modified length-couple stress parameter

Mechanics Based Design of Structures and Machines / Dec 27, 2019

Ghabussi, A., Ashrafi, N., Shavalipour, A., Hosseinpour, A., Habibi, M., Moayedi, H., Babaei, B., & Safarpour, H. (2019). Free vibration analysis of an electro-elastic GPLRC cylindrical shell surrounded by viscoelastic foundation using modified length-couple stress parameter. Mechanics Based Design of Structures and Machines, 49(5), 738–762. https://doi.org/10.1080/15397734.2019.1705166

Vibration response of viscoelastic sandwich plate with magnetorheological fluid core and functionally graded-piezoelectric nanocomposite face sheets

Journal of Vibration and Control / Jan 02, 2018

Ghorbanpour Arani, A., BabaAkbar Zarei, H., & Haghparast, E. (2018). Vibration response of viscoelastic sandwich plate with magnetorheological fluid core and functionally graded-piezoelectric nanocomposite face sheets. Journal of Vibration and Control, 107754631774750. https://doi.org/10.1177/1077546317747501

See Full Profile

Denys Dutykh

Professional Applied Mathematician, Modeller, and Advisor
Most Relevant Research Expertise
Automotive Engineering
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

An innovative method to determine optimum insulation thickness based on non-uniform adaptive moving grid

Journal of the Brazilian Society of Mechanical Sciences and Engineering / Mar 14, 2019

Gasparin, S., Berger, J., Dutykh, D., & Mendes, N. (2019). An innovative method to determine optimum insulation thickness based on non-uniform adaptive moving grid. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41(4). https://doi.org/10.1007/s40430-019-1670-6

See Full Profile

Athul Prasad

5G / 6G Technology and Ventures at Samsung; D.Sc. (Tech), MBA
Most Relevant Research Expertise
Automotive Engineering
Other Research Expertise (35)
Machine Learning
Mobility Management
5G / New Radio
Dynamic Resource Allocation
Electrical and Electronic Engineering
And 30 more
About
Dr. Athul Prasad received his MBA from MIT where he was a Sloan Fellow, M.Sc. (Tech.) (with distinction) and D.Sc. (Tech) from Aalto University, B.Tech (with distinction) from University of Kerala, and is also a graduate of the year-long executive management (LEAD) program from Stanford University's Graduate School of Business. He was with Nokia from 2014-2023 and is currently with Samsung based out of Mountain View, CA. He has coauthored over 40 peer reviewed scientific publications and has written a book on 5G "End-to-End Mobile Communications: Evolution to 5G," McGraw-Hill, Aug. 2020. He's also the co-inventor of over 90 patents.
Most Relevant Publications (2+)

75 total publications

Energy-Efficient D2D Discovery for Proximity Services in 3GPP LTE-Advanced Networks: ProSe Discovery Mechanisms

IEEE Vehicular Technology Magazine / Dec 01, 2014

Prasad, A., Kunz, A., Velev, G., Samdanis, K., & Song, J. (2014). Energy-Efficient D2D Discovery for Proximity Services in 3GPP LTE-Advanced Networks: ProSe Discovery Mechanisms. IEEE Vehicular Technology Magazine, 9(4), 40–50. https://doi.org/10.1109/mvt.2014.2360652

5G Radio Access Networks: Enabling Efficient Point-to-Multipoint Transmissions

IEEE Vehicular Technology Magazine / Dec 01, 2019

Saily, M., Barjau, C., Navratil, D., Prasad, A., Gomez-Barquero, D., & Tesema, F. B. (2019). 5G Radio Access Networks: Enabling Efficient Point-to-Multipoint Transmissions. IEEE Vehicular Technology Magazine, 14(4), 29–37. https://doi.org/10.1109/mvt.2019.2936657

See Full Profile

Irma Kuljanishvili

Post Doctoral Research Associate at Harvard University
Most Relevant Research Expertise
Automotive Engineering
Other Research Expertise (25)
Nanoscience
Nanomaterials
Condensed Matter Physics
Scanning Probe Miscroscopy
Nanofabrication and Nanolitography
And 20 more
About
Dr. Kuljanishvili is a highly educated physicist with a PhD in condensed matter physics, in low temperature nanoscale physics, focused on scanning probe microscopy and spectroscopy. She obtained her PhD from Michigan State University in 2005. After completing her doctoral studies, she worked as a Post Doctoral Research Associate at Harvard University till 2006 and later as a Post Doctoral Research Fellow at Northwestern University till 2011. During these positions, she conducted research on various topics related to condensed matter physics, nanoscience and nanotechnology, low dimensional materials physics and used variety of scanning probe microscopy and spectroscopy and nanolithography techniques in her research. Dr. Kuljanishvili has published numerous research papers in well-respected scientific journals and has presented her work at national and international conferences. She is highly skilled in experimental techniques and data analysis, and has a strong understanding of theoretical concepts in her field. In addition to her research experience, Irma has mentored numerous undergraduate and graduate students and taught courses in physics at the university level. She is dedicated to the advancement of science and technology and is constantly seeking opportunities to expand her knowledge and skills in her field.
Most Relevant Publications (1+)

43 total publications

Microstructural Features of 3D-Printed Alloy

Metal Powder Report / Feb 01, 2024

Microstructural Features of 3D-Printed Alloy. (2024). Metal Powder Report, 79(1). https://doi.org/10.12968/s0026-0657(24)70004-6

See Full Profile

Mohamad (Moe) El Hariri

Energy enthusiast with over five years of industry experience and academic professorship in modeling and control of various energy systems.
Most Relevant Research Expertise
Automotive Engineering
Other Research Expertise (25)
IoT Application in smart grid
Datacentric communications
Cyber security and resilience of power systems
artificial intelligen
Electrical and Electronic Engineering
And 20 more
About
Moe El Hariri is an accomplished engineer and educator with a Ph.D. in Electrical and Computer Engineering from Florida International University. He has a strong background in data analysis, machine learning, and renewable energy systems. Moe has extensive experience working as a data scientist for Community Energy Labs, where he applied his expertise to develop innovative solutions for renewable energy projects. He also has a strong passion for teaching and has been an Assistant Professor at Colorado School of Mines, where he has mentored students and conducted research in the areas of energy systems and sustainability. Moe is a dedicated and driven individual, constantly seeking new challenges and opportunities to make a positive impact in the field of renewable energy.
Most Relevant Publications (1+)

37 total publications

A Bilateral Decision Support Platform for Public Charging of Connected Electric Vehicles

IEEE Transactions on Vehicular Technology / Jan 01, 2019

Hariri, A. O., El Hariri, M., Youssef, T., & Mohammed, O. A. (2019). A Bilateral Decision Support Platform for Public Charging of Connected Electric Vehicles. IEEE Transactions on Vehicular Technology, 68(1), 129–140. https://doi.org/10.1109/tvt.2018.2879927

See Full Profile

Example automotive engineering projects

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

Electric Vehicle Battery Optimization

An academic researcher in Automotive Engineering can collaborate with a company to optimize the performance and efficiency of electric vehicle batteries. They can conduct research on battery materials, design, and management systems to enhance energy storage, extend battery life, and improve charging capabilities.

Autonomous Vehicle Navigation Systems

Collaborating with an academic researcher specializing in Automotive Engineering can help companies develop advanced navigation systems for autonomous vehicles. The researcher can contribute expertise in sensor technologies, data fusion, machine learning, and control systems to enhance the accuracy, reliability, and safety of autonomous vehicle navigation.

Vehicle Lightweighting and Material Selection

Working with an academic researcher in Automotive Engineering can assist companies in optimizing vehicle lightweighting strategies and material selection. The researcher can analyze different materials, such as composites and alloys, and provide recommendations for reducing vehicle weight while maintaining structural integrity and safety.

Emissions Reduction and Environmental Sustainability

An academic researcher in Automotive Engineering can collaborate with companies to develop innovative solutions for emissions reduction and environmental sustainability. They can conduct research on alternative fuels, hybrid powertrains, and emission control technologies to help companies meet regulatory requirements and achieve sustainability goals.

Advanced Driver Assistance Systems (ADAS)

Collaborating with an academic researcher specializing in Automotive Engineering can benefit companies in the development of advanced driver assistance systems (ADAS). The researcher can contribute expertise in sensor technologies, computer vision, and machine learning to enhance the performance and safety of ADAS features, such as adaptive cruise control and lane keeping assist.