Yalini Devi Neelan | Engineering | Best Researcher Award

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Dr. Yalini Devi Neelan | Engineering | Best Researcher Award

Google Scholar Profile

Educational Details

Dr. Yalini Devi Neelan completed her Ph.D. in Energy Harvesting Applications at Anna University, India, from 2016 to 2021. Her doctoral research focused on innovative methods for harnessing energy through advanced materials and nanotechnology. Prior to her Ph.D., she earned an M.Tech. in Nanoscience and Technology from Anna University, where she achieved an impressive GPA of 8.24/10 from 2014 to 2016. Dr. Neelan’s academic journey began with a Bachelor of Engineering in Electrical and Electronic Engineering, also from Anna University, where she graduated in 2014 with a GPA of 6.41/10. This solid educational background has equipped her with a strong foundation in both engineering principles and nanomaterials, driving her passion for research in energy solutions.

Research Experience

Dr. Yalini Devi Neelan is currently a Postdoctoral Researcher at the University of Milano, Italy, in the Thermoelectric’s Laboratory, where she focuses on the preparation and characterization of nanostructured silicon for thermoelectric applications. Her key responsibilities include preparing nanostructured materials, examining their physicochemical characteristics, and studying their Seebeck coefficient, electrical, and thermal conductivity to calculate the figure of merit (ZT). Prior to this, she was a Postdoctoral Researcher at Chungnam National University, South Korea, where she worked on nanostructured oxide-based materials for antibiotic degradation and battery applications, analyzing their photodegradation and electrochemical properties. Dr. Neelan also served as a Research Associate at Anna University, India, where she focused on energy harvesting and storage applications, preparing oxide-based nanomaterials and managing communications with funding agencies. During her Ph.D. at Anna University, she investigated nanostructured strontium titanate-based oxide thermoelectric materials for energy harvesting from waste heat. Additionally, she collaborated with Shimomura Laboratory at Shizuoka University, Japan, to enhance the thermoelectric power factor of nanostructured SrTiO3 through Gd and Nb co-substitution. Earlier in her academic journey, Dr. Neelan was a project student at the Indian Institute of Technology Madras, where she developed graphene oxide-based strain sensors for motion monitoring. Her diverse research experiences reflect her strong expertise in nanomaterials and energy applications.

Research Focus

Energy harvesting applications, particularly in thermoelectrics, focus on converting waste heat into usable electrical energy, thus promoting sustainable energy solutions. The synthesis of nanomaterials plays a crucial role in this field, as nanostructured materials exhibit enhanced thermoelectric properties due to their unique physical and chemical characteristics. These materials are engineered to optimize energy conversion efficiencies, allowing for effective harvesting from various heat sources. Additionally, advancements in energy storage applications complement energy harvesting by ensuring that the harvested energy can be effectively stored and utilized when needed. By integrating innovative synthesis techniques and exploring novel nanomaterials, researchers aim to improve the performance and efficiency of thermoelectric devices, ultimately contributing to a more sustainable and energy-efficient future.

Top Notable Publications

Enhancing effects of Te substitution on the thermoelectric power factor of nanostructured SnSe₁₋ₓTeₓ
Authors: D. Sidharth, A.S.A. Nedunchezhian, R. Rajkumar, N.Y. Devi, P. Rajasekaran, et al.
Journal: Physical Chemistry Chemical Physics
Year: 2019
Citations: 32

Effect of Gd and Nb co-substitution on enhancing the thermoelectric power factor of nanostructured SrTiO₃
Authors: N.Y. Devi, K. Vijayakumar, P. Rajasekaran, A.S.A. Nedunchezhian, et al.
Journal: Ceramics International
Year: 2021
Citations: 26

Enhanced thermoelectric performance of band structure engineered GeSe₁₋ₓTeₓ alloys
Authors: D. Sidharth, A.S.A. Nedunchezhian, R. Akilan, A. Srivastava, B. Srinivasan, et al.
Journal: Sustainable Energy & Fuels
Year: 2021
Citations: 25

Enhancement of thermoelectric power factor of hydrothermally synthesised SrTiO₃ nanostructures
Authors: N.Y. Devi, P. Rajasekaran, K. Vijayakumar, A.S.A. Nedunchezhian, et al.
Journal: Materials Research Express
Year: 2020
Citations: 15

Biogenic synthesis and characterization of silver nanoparticles: evaluation of their larvicidal, antibacterial, and cytotoxic activities
Authors: S. Mahalingam, P.K. Govindaraji, V.G. Solomon, H. Kesavan, Y.D. Neelan, et al.
Journal: ACS Omega
Year: 2023
Citations: 11

Effect of Bismuth substitution on the enhancement of thermoelectric power factor of nanostructured BiₓCo₃₋ₓO₄
Authors: A.S.A. Nedunchezhian, D. Sidharth, N.Y. Devi, R. Rajkumar, P. Rajasekaran, et al.
Journal: Ceramics International
Year: 2019
Citations: 11

Effective Visible-Light-Driven Photocatalytic Degradation of Harmful Antibiotics Using Reduced Graphene Oxide-Zinc Sulfide-Copper Sulfide Nanocomposites as a Catalyst
Authors: J.K. Shanmugam Mahalingam, Yalini Devi Neelan, Senthil Bakthavatchalam, et al.
Journal: ACS Omega
Year: 2023
Citations: 10

Enhancing the thermoelectric power factor of nanostructured ZnCo₂O₄ by Bi substitution
Authors: A.S.A. Nedunchezhian, D. Sidharth, R. Rajkumar, N.Y. Devi, K. Maeda, et al.
Journal: RSC Advances
Year: 2020
Citations: 7

High thermoelectric power factor of Ag and Nb co-substituted SrTiO₃ perovskite nanostructures
Authors: N.Y. Devi, A.S.A. Nedunchezhian, D. Sidharth, P. Rajasekaran, et al.
Journal: Materials Chemistry and Physics
Year: 2023
Citations: 3

Soad Fars | Nanomaterial | Best Researcher Award

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Prof. Soad Fars | Nanomaterial | Best Researcher Award

Scopus Profile

Orcid Profile

Educational Details:

Prof. Soad Fars earned her B.Sc. in Physics from the Faculty of Science at Suez Canal University, Ismailia, Egypt, in September 1981. She pursued her M.Sc. in Nuclear Physics at Ain Shams University, Cairo, Egypt, completing it in 1986. In October 1992, she was awarded her Ph.D. in Nuclear Physics from Suez Canal University. Her academic journey continued, and in 2012, she became an Associate Professor in Radiation Physics. Prof. Fars has built a distinguished career specializing in nuclear and radiation physics, contributing to research, teaching, and advancing knowledge in her field.

Employment Duties

Prof. Soad Fars currently serves as an Associate Professor in the Radiation Physics Department at the National Center of Radiation Research and Technology, Atomic Energy Authority. Her role encompasses several key responsibilities: overseeing routine operations in the Gamma Spectroscopy Lab, including supervising lab activities and organizing workshops, and supervising both M.Sc. and Ph.D. student theses. Additionally, Prof. Fars conducts her own independent research in radiation physics. Presently, she is also affiliated with Al-Baha University in Saudi Arabia, where she holds the position of Coordinator for the Physics Department and serves as Supervisor of the Development and Quality Committee at the Faculty of Science and Arts (Girls section). Her diverse roles highlight her dedication to both academic leadership and scientific research.

Professional Experience

Throughout her career, Prof. Soad Fars has gained extensive expertise in operating, analyzing, and interpreting data from a variety of scientific instruments. She has significant experience with Gamma Spectrometric Techniques, including both high and low-level gamma spectrometric analysis, and their applications in calculating natural radioactivity levels (NORMs), activity concentrations, and assessing radiological risks. Her work also involves evaluating external and internal radiation hazard indices, as well as understanding the theoretical aspects of these phenomena. Additionally, she has applied DC and AC Electrical Conductivity Circuits to various models, worked with X-Ray Diffraction to determine the structure of both ordered and disordered materials, and utilized UV-Visible-NIR instruments. Prof. Fars is also proficient in Scanning Electron Microscopy (SEM). Furthermore, she has studied the effects of gamma irradiation on polymers and nanomaterials, focusing on modifying their properties for improved applications.

Top Notable Publications

Alshahrani, B., Korna, A.H., Fares, S., Ali, A.H. (2024). Assessment of Radioactivity in Groundwater and Silt from some Underground Wells in Southern Sinai, Egypt. Water, Air, and Soil Pollution, 235(8), 481.

Fares, S.S., Korna, A.H. (2024). Gamma-irradiation-induced tailoring of physical, electrical, optical, and mechanical properties of PVC/PANI/TiO2 nanocomposites for different applications. Optical Materials, 153, 115544.

Fares, S.S. (2024). Impact of Fertilizer Factory Emissions on Radiological Content of Soil: A Study in Upper Egypt. Pollution, 10(2), 790–807.

Fares, S.S. (2024). Determine the hazards of radioactive elements and radon gas manufacturing processes in an Egyptian fertilizer factory. Nuclear Engineering and Technology, 56(5), 1781–1795.

Alshahrani, B., Korna, A.H., Fares, S. (2024). Effect of gamma radiation on the structural, ferromagnetic resonance, optical, and dispersion properties of PVC/MnFe2O4–ZnMn2O4 nanocomposite films. Journal of Materials Science. (Article in Press)

Alshahrani, B., ElSaeedy, H.I., Fares, S., Fahim, R.A., Awed, A.S. (2021). Revealing the effect of gamma irradiation on structural, ferromagnetic resonance, optical, and dispersion properties of PVC/Mn0.5Zn0.5Fe2O4 nanocomposite films. Optical Materials, 118, 111216.

Alshahrani, B., ElSaeedy, H.I., Fares, S., Ashour, A.H., Awed, A.S. (2021). The effect of gamma irradiation on structural, optical, and dispersion properties of PVA/Zn0.5Co0.4Ag0.2Fe2O4 nanocomposite films. Journal of Materials Science: Materials in Electronics, 32(10), 13336–13349.

Alshahrani, B., ElSaeedy, H.I., Fares, S., Gobara, M., Maksoud, M.I.A.A. (2021). Structural, optical, and magnetic properties of nanostructured Ag-substituted Co-Zn ferrites: insights on anticancer and antiproliferative activities. Journal of Materials Science: Materials in Electronics, 32(9), 12383–12401.

Alshahrani, B., ElSaeedy, H.I., Fares, S., Gobara, M., Ashour, A.H. (2021). The effect of Ce3+ doping on structural, optical, ferromagnetic resonance, and magnetic properties of ZnFe2O4 nanoparticles. Journal of Materials Science: Materials in Electronics, 32(1), 780–797.

Elmaghraby, E.K., Abdelaal, S., Abdelhady, A.M., Salama, S., Mansour, N.A. (2020). Experimental determination of the fission-neutron fluence-to-dose conversion factor. Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 949, 162889.

Bruce Hoeneisen | Dark Matter | Best Researcher Award

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Prof. Bruce Hoeneisen | Dark Matter | Best Researcher Award

Scopus Profile

Orcid Profile

Educational Details:

Prof. Bruce Hoeneisen’s educational background is grounded in physics and engineering, though specific details of his degrees are not listed in the provided information. However, his career as a professor at Escuela Politécnica Nacional and Universidad San Francisco de Quito, along with his co-founding role at the latter institution, demonstrates a strong academic foundation. His extensive research and publication history, including his 2024 book Measurements of the Dark Matter Mass, Temperature, and Spin, further highlight his expertise in particle physics and cosmology.

Research Interest:

Prof. Bruce Hoeneisen’s research interests primarily focus on particle physics and cosmology, with a particular emphasis on dark matter. His work includes extensive studies on the mass, temperature, and spin of dark matter, as detailed in his 2024 publication Measurements of the Dark Matter Mass, Temperature, and Spin. Additionally, his prolific output of over 663 scientific articles reflects broad expertise in high-energy physics and related fields.

Professional Experience

Prof. Bruce Hoeneisen has had a distinguished career spanning nearly four decades. From 1972 to 2011, he served as a professor at Escuela Politécnica Nacional and Universidad San Francisco de Quito in Ecuador, where he played a pivotal role in co-founding the latter institution. In addition to his academic positions, he has worked as a freelance engineer. His contributions to the field of physics are vast, with over 663 scientific articles published, showcasing his expertise in dark matter, particle physics, and cosmology.

Top Notable Publications

Understanding elliptical galaxies with warm dark matter

Author(s): Bruce Hoeneisen

Year: 2024

Published in: Physics of the Dark Universe

DOI: 10.1016/j.dark.2024.101643

Type: Journal article

Source: Crossref

Inclusive muon and $B$ quark production cross-sections in $p \bar{p}$ collisions at $\sqrt{s}$ = 1.8-TeV

Author(s): Bruce Hoeneisen

Year: 2017

Published in: International Europhysics Conference on High-energy Physics (HEP 95)

OTHER-ID: 398709

Type: Conference paper

Source: INSPIRE-HEP

Ratio between two $\Lambda$ and $\bar{\Lambda}$ production mechanisms in $p$ scattering

Author(s): Bruce Hoeneisen

Year: 2016

Published in: Phys. Lett. B

DOI: 10.1016/j.physletb.2016.06.072

ARXIV: 1604.05379

Type: Journal article

Source: INSPIRE-HEP

Measurement of the Effective Weak Mixing Angle in $p\bar{p}\rightarrow Z/\gamma^{*}\rightarrow e^{+}e^{-}$ Events

Author(s): Bruce Hoeneisen

Year: 2015

Published in: Phys. Rev. Lett.

DOI: 10.1103/PhysRevLett.115.041801

ARXIV: 1408.5016

Type: Journal article

Source: INSPIRE-HEP

Precision measurement of the top-quark mass in lepton$+$jets final states

Author(s): Bruce Hoeneisen

Year: 2015

Published in: Phys. Rev. D

DOI: 10.1103/PhysRevD.91.112003

ARXIV: 1501.07912

Type: Journal article

Source: INSPIRE-HEP

Tevatron Constraints on Models of the Higgs Boson with Exotic Spin and Parity Using Decays to Bottom-Antibottom Quark Pairs

Author(s): Bruce Hoeneisen

Year: 2015

Published in: Phys. Rev. Lett.

DOI: 10.1103/PhysRevLett.114.151802

ARXIV: 1502.00967

Type: Journal article

Source: INSPIRE-HEP

Measurement of the $W+b$-jet and $W+c$-jet differential production cross sections in $p\bar{p}$ collisions at $\sqrt{s}=1.96$ TeV

Author(s): Bruce Hoeneisen

Year: 2015

Published in: Phys. Lett. B

DOI: 10.1016/j.physletb.2015.02.012

ARXIV: 1412.5315

Type: Journal article

Source: INSPIRE-HEP

Measurement of the $\phi^*_\eta$ distribution of muon pairs with masses between 30 and 500 GeV in 10.4 fb$^{-1}$ of $p\bar{p}$ collisions

Author(s): Bruce Hoeneisen

Year: 2015

Published in: Phys. Rev. D

DOI: 10.1103/PhysRevD.91.072002

ARXIV: 1410.8052

Type: Journal article

Source: INSPIRE-HEP

Measurement of the ratio of inclusive cross sections $\sigma (p\bar{p} \rightarrow Z+2~b \text{jets}) / \sigma (p\bar{p} \rightarrow Z+ \text{2 jets})$ in $p\bar{p}$ collisions at $\sqrt s=1.96$ TeV

Author(s): Bruce Hoeneisen

Year: 2015

Published in: Phys. Rev. D

DOI: 10.1103/PhysRevD.91.052010

ARXIV: 1501.05325

Type: Journal article

Source: INSPIRE-HEP

Marcin Tomsia | Forensic Science | Best Researcher Award

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Marcin Tomsia | Forensic Science | Best Researcher Award

Scopus Profile

Educational Details:

Dr. Marcin Tomsia has made significant contributions to forensic science through his academic and professional work. Currently, he is involved in postgraduate education at the Medical University of Lublin, Poland, where he teaches forensic genetics to laboratory diagnosticians. His previous roles include a position in forensic biology at the Institute of Zoology at Jagiellonian University in Kraków, Poland, where he achieved a top university assessment score.Dr. Tomsia’s academic journey began with his MSc studies in biotechnology at the School of Pharmacy with the Division of Laboratory Medicine at Medical University of Silesia, Katowice, Poland. His MSc thesis focused on the polymorphic IFN-γ gene in recurrent affective disorder. He continued his education with PhD studies at the Medical University of Silesia, specializing in cytophysiology and histology, where his research centered on gene expression profiles in human amnion cells.With a solid foundation in both practical and theoretical aspects of forensic science and biotechnology, Dr. Tomsia’s work has greatly impacted the field, earning him the Best Researcher Award for his exceptional research and contributions to forensic science.

Professional experience:

Dr. Marcin Tomsia is an esteemed professional in forensic science with a diverse and impactful career. Since October 1, 2022, he has served as an Assistant Professor in the Department of Forensic Medicine and Forensic Toxicology at the Medical University of Silesia in Katowice, Poland. He has been a key figure in advancing forensic education and research.Dr. Tomsia has been a dedicated reviewer for MDPI (Switzerland) and Jagiellonian University Press (Poland) since 2021, contributing his expertise to the peer-review process for leading scientific publications.From October 1, 2018, to September 30, 2022, he worked as a full-time genetic technician in the Department of Forensic Medicine and Forensic Toxicology at the Medical University of Silesia. His role involved critical forensic analysis and the application of genetic techniques in various investigations.In addition to his role as a genetic technician, Dr. Tomsia has been a lecturer of forensic genetics in the English division of the Department of Forensic Medicine and Forensic Toxicology since 2016, where he has educated and trained future forensic experts.Previously, from June 1, 2012, to 2018, he worked part-time as a genetic technician in the same department, building a solid foundation of experience in forensic genetics and contributing to the department’s research and diagnostic capabilities.

Skills:

DNA Isolation from Skeletal Remains: Dr. Tomsia has successfully identified over 100 samples from hard tissues, including bones that were buried for over 70 years, demonstrating his proficiency in handling challenging forensic samples DNA Isolation from Biological Traces: He is adept at using differential extraction and manual methods to isolate DNA from various biological traces, ensuring accurate forensic analysis. Biochemical Identification: He has extensive experience with immunochromatographic strip tests for detecting semen, blood, and saliva stains, which aids in precise evidence identification. DNA Concentration Determination: Dr. Tomsia is skilled in employing spectrophotometric (NANODROP 1000), fluorometric (Quantus™, Promega), and RT2 PCR System (ThermoFisher Scientific) methods to measure DNA concentration. Paternity Testing: His expertise covers the complete paternity testing process, including buccal swab collection, DNA isolation, multiplex PCR, capillary electrophoresis, statistical analysis, and data interpretation. Multiplex PCR and Capillary Electrophoresis: Dr. Tomsia is proficient in using PowerPlex® Fusion and PowerPlex® Y23 Systems, as well as ABI PRISM3130 for advanced genetic analysis. Statistical Calculations: He is competent in performing basic statistical calculations and interpreting the results to support forensic investigations. Legal Cooperation: His extensive experience working with judges and prosecutors highlights his ability to contribute effectively to legal proceedings involving forensic evidence. Cell Isolation and Culture: Dr. Tomsia’s expertise includes isolating cells from human amniotic membranes, culturing amniotic membrane stem cells, and conducting gene expression analyses using RT2PCR-Light Cycler 480 (Roche) and flow cytometry (FACS Aria I). He is also skilled in immunohistochemistry analysis.

Scientific projects:

In recent years, significant progress has been made in forensic science through research led by young scientists in the fields of genetic and biochemical analysis. A noteworthy area of exploration is the study of costal cartilage, which has emerged as a valuable niche in forensic investigations. One ongoing project (2023) investigates the potential of costal cartilage as a new niche of human remains in the field of forensic acarology. This builds on previous studies, such as a 2022 project focused on correlating CT imaging results with the age of individuals in the Upper Silesian population. The investigation continues with the aim of enhancing forensic identification techniques using non-invasive imaging methods.

In 2021, a series of research tasks further highlighted the forensic potential of costal cartilage. One study examined the presence of psychoactive substances in postmortem cartilage, while another investigated the genetic and biochemical markers in human semen, even after laundering evidence. These projects have demonstrated how cartilage’s unique properties can aid in the detection of biological materials, preserving DNA integrity, and facilitating forensic identification, as documented in a National Science Foundation-supported study. Additionally, research from 2020 and 2019 expanded on the understanding of how decomposition affects psychoactive substance concentrations in cartilage, as well as its applications in age estimation of deceased individuals, making costal cartilage a vital area of focus in forensic science.

Top Notable Publications

Tomsia, M., Cieśla, J., Śmieszek, J., Michalczyk, K., & Stygar, D. (2024). Long-term space missions’ effects on the human organism: what we do know and what requires further research. Frontiers in Physiology, 15, 1284644.

Freire-Aradas, A., Tomsia, M., Piniewska-Róg, D., Phillips, C., & Branicki, W. (2023). Development of an epigenetic age predictor for costal cartilage with a simultaneous somatic tissue differentiation system. Forensic Science International: Genetics, 67, 102936.

Żarczyńska, M., Żarczyński, P., & Tomsia, M. (2023). Nucleic Acids Persistence—Benefits and Limitations in Forensic Genetics. Genes, 14(8), 1643.

Tomsia, M., Chełmecka, E., Głaz, M., & Nowicka, J. (2023). Epiglottis Cartilage, Costal Cartilage, and Intervertebral Disc Cartilage as Alternative Materials in the Postmortem Diagnosis of Methanol Poisoning. Toxics, 11(2), 152.

Cieśla, J., Skrobisz, J., Niciński, B., Javan, G.T., & Tomsia, M. (2023). The smell of death. State-of-the-art and future research directions. Frontiers in Microbiology, 14, 1260869.

Tomsia, M., Głaz, M., Nowicka, J., Sosnowski, M., & Chełmecka, E. (2022). Fatal Methanol Poisoning Caused by Drinking Industrial Alcohol: Silesia Region, Poland, April–June 2022. Toxics, 10(12), 800.

Tomsia, M., Droździok, K., Banaszek, P., Pałasz, A., & Chełmecka, E. (2022). The intervertebral discs’ fibrocartilage as a DNA source for genetic identification in severely charred cadavers. Forensic Science, Medicine, and Pathology, 18(4), 442–449.

Tomsia, M., Cieśla, J., Pilch-Kowalczyk, J., Banaszek, P., & Chełmecka, E. (2022). Cartilage Tissue in Forensic Science—State of the Art and Future Research Directions. Processes, 10(11), 2456.

Shilin Xia | Remote Sensing | Best Researcher Award

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Mr. Shilin Xia | Remote Sensing | Best Researcher Award

Orcid Profile

Professional Background:

Xia Shilin is a postgraduate student at Chang’an University, Xi’an, China, where he is pursuing a Master of Science degree in Information and Communication Engineering. He earned his Bachelor of Science degree in Electronic Information Engineering from the same institution in 2021. His research focuses on remote sensing object detection and recognition, aiming to advance methodologies and technologies in this field. Xia Shilin is dedicated to developing innovative solutions that enhance the accuracy and efficiency of remote sensing applications.

Ongoing Research Projects:

Xia Shilin is a postgraduate student at Chang’an University, Xi’an, China, pursuing a Master of Science in Information and Communication Engineering. He received his Bachelor of Science degree in Electronic Information Engineering from the same university in 2021. His research is focused on multiscale object detection in remote sensing imagery. This work has been supported by several grants, including those from the National Natural Science Foundation of China (Grants 52172379, 62001058, U1864204, and 62406041), the Shannxi International S&T Cooperation Program Project (2024GH-YBXM-24), and the Special Funds for Fundamental Research Funds of the Central Universities of Chang’an University (Grant 300102242901) and the Fundamental Research Funds for the Central Universities, CHD (Grant 300102404104).

Areas of Research:

Xia Shilin’s research centers on object detection in remote sensing imagery, with a particular emphasis on multiscale detection techniques. This area of study aims to improve the accuracy and efficiency of identifying and classifying objects from satellite and aerial images, which is crucial for various applications including environmental monitoring, urban planning, and disaster management. His work leverages advanced algorithms and machine learning approaches to enhance the detection of objects at different scales, addressing challenges related to image resolution and object size variability. This research is supported by several grants, including those from the National Natural Science Foundation of China and other key funding sources, reflecting the significance and innovation of his contributions to the field.

Contributions:

Xia Shilin’s research introduces several innovative techniques to advance object detection in remote sensing imagery. The parallel structure combining pointwise and partial convolution has been shown to significantly reduce the number of network parameters, optimizing computational efficiency. By integrating context modeling and residual modules, the research enhances the detection of small object features, which are often challenging to identify due to their size. Additionally, the development of an improved upsampling operator and fully connected Feature Pyramid Network (FPN) effectively reduces network parameters while maintaining high performance. These advancements contribute to more accurate and efficient object detection, particularly in complex and varied remote sensing environments.

Top Notable Publications

MSNet: Multi-Scale Network for Object Detection in Remote Sensing Images

Authors: Xia Shilin, [Additional Authors]

Journal: Pattern Recognition

Publication Date: February 2025

DOI: 10.1016/j.patcog.2024.110983

Source: Crossref

 

Chi Liu | Computational Methods | Best Researcher Award

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Dr. Chi Liu | Computational Methods | Best Researcher Award

Scopus Profile

Orcid Profile

Professional Experience:

Dr. Chi Liu is an assistant researcher and project manager at the Chinese Institute of Coal Science. He earned his Bachelor of Engineering (BE) and PhD degrees from Jilin University and Tsinghua University, respectively. Dr. Liu’s research focuses on computational rock mechanics and the catastrophic mechanisms of geomaterials, particularly soft rock interactions with water. He has published over 10 peer-reviewed journal papers, including those in SCI/EI journals. As the principal investigator of more than 10 national and provincial research projects, Dr. Liu has made significant contributions to the field. He is also a member of the Red-bed Engineering Branch of the Chinese Society of Rock Mechanics and Engineering.

Research and Innovations:

Dr. Chi Liu has successfully completed six research projects and is currently engaged in ten ongoing research initiatives. His scholarly impact is reflected in his citation index, with an h-index of 4 on Scopus. In addition to his research, Dr. Liu has contributed to six consultancy and industry-sponsored projects, demonstrating his expertise in practical applications of his work. He has also made significant strides in intellectual property, with eight patents published or under process. Dr. Liu has authored 11 articles in peer-reviewed journals, showcasing his contributions to the field. Despite his extensive involvement in research and industry, he has not held any editorial appointments.

Collaborations: 

Dr. Chi Liu has developed the rock fracture analysis software, FDEMYMs, which boasts independent intellectual property rights. This software represents a significant advancement in the field of computational rock mechanics, offering sophisticated tools for analyzing rock fractures. Its development underscores Dr. Liu’s commitment to enhancing the precision and effectiveness of rock mechanics research through innovative technological solutions.

Professional Memberships:

Dr. Chi Liu is an active member of several prestigious professional organizations. He serves on the Red-bed Engineering Branch of the Chinese Society of Rock Mechanics and Engineering, where he contributes to advancements in rock mechanics and engineering practices. Additionally, he is a member of the China Coal Society, reflecting his engagement with the coal industry and related research. His affiliation with the Geological Society of China further highlights his dedication to the broader geological community and its ongoing development. These memberships underscore Dr. Liu’s commitment to advancing his field through collaborative and professional networks.

Areas of Research:

Dr. Chi Liu’s research is primarily focused on computational mechanics and rock mechanics. His work in computational mechanics involves using advanced simulations and modeling techniques to understand and predict the behavior of materials under various conditions. In rock mechanics, Dr. Liu investigates the physical and mechanical properties of rocks, particularly under complex environmental interactions such as water-rock interactions. His expertise in these areas contributes significantly to the development of practical solutions for geological and engineering challenges, enhancing the safety and efficiency of construction and resource extraction projects.

Contributions:

Dr. Chi Liu firstly proposed a new water-rock interfacial
evolution model named Interfacial Cemented Bonding (ICB) model, and established an
analytical solution describing the time-dependent damage effect of the meso-structure of
soft rock. He also established the cohesive crack constitutive model and interface softening
theory. He developed a novel numerical characterization and simulation methods of all
elements of rock materials based on the self-developed rock fracture calculation software
FDEMYMs with independent intellectual property rights. He also proposed the bearing
skeleton to describe the bearing nature of rock mass, and the life cycle control principle of
rock mass structure.

Top Notable Publications

“Water-rock interfacial softening model of cemented soft rock: An experimental and numerical study”

Authors: Liu, C., Liu, X., Wang, E., Wang, S., Peng, H.

Journal: Results in Engineering

Year: 2024

Volume: 23

Article Number: 102710

Citations: 0

“Optimizing 3D granular modeling with integrated 3DEC and neper techniques for granite mechanics simulation”

Authors: Ma, Q., Liu, X., Wang, E., Liu, C., Jia, W.

Journal: Computers and Geotechnics

Year: 2024

Volume: 173

Article Number: 106578

Citations: 1

Access: Open access

“Discrete Element Study on the Mechanical Response of Soft Rock Considering Water-Induced Softening Effect”

Authors: Liu, C., Liu, X., Peng, H., Wang, E., Wang, S.

Journal: Applied Sciences (Switzerland)

Year: 2024

Volume: 14(9)

Article Number: 3918

Citations: 1

“Dependence of connectivity dominance on fracture permeability and influence of topological centrality on the flow capacity of fractured porous media”

Authors: Wang, C., Liu, X., Wang, E., Wang, M., Liu, C.

Journal: Journal of Hydrology

Year: 2023

Volume: 624

Article Number: 129883

Citations: 3

“Investigation of Multiscale Failure Mechanism of Red Bed Soft Rock using Grain-Based Finite-Discrete Element Method Combined with X-Ray Micro-computerized Tomography”

Authors: Liu, C., Liu, X., Wu, C., Wang, S., Peng, H.

Journal: KSCE Journal of Civil Engineering

Year: 2023

Volume: 27(3)

Pages: 1350–1367

Citations: 6

“Dynamic model for water-rock interface of softening of soft rock and its evolution law”

Authors: Liu, C., Liu, X.-L., Zhang, D., Wang, E.-Z., Wang, S.-J.

Journal: Yantu Gongcheng Xuebao/Chinese Journal of Geotechnical Engineering

Year: 2022

Volume: 44(12)

Pages: 2280–2289

Citations: 9

Yang Han | Condensed Matter Physics | Best Researcher Award

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Prof Dr.Yang Han | Condensed Matter Physics | Best Researcher Award

Google Scholar Profile

Orcid Profile

Educational Details:

Yang Han completed her Ph.D. in 2014 from Nanjing University, China. Following her doctorate, she pursued postdoctoral research at RWTH Aachen University, Germany, from 2014 to 2016, where she focused on [research focus, e.g., materials science, mechanical properties, etc.]. She then continued her postdoctoral work at the University of Lorraine, France, from 2016 to 2018, concentrating on [research focus, e.g., thermoelectric properties, molecular dynamics simulations, etc.]. With a strong background in first-principles calculations and numerical simulations, she now serves as a professor and Ph.D. supervisor at Harbin Engineering University.

Research and Innovations:

Yang Han has made significant contributions to the fields of material science and computational modeling, particularly through her innovative research using numerical simulations to understand the mechanical, thermal transport, electronic, magnetic, and thermoelectric properties of advanced materials. Her groundbreaking work has centered on the following key research innovations:

  1. Topological Defects and Heterojunctions in 3D Graphene Structures: Through the support of the National Natural Science Foundation of China (Project No. 12104111), Yang’s research has provided vital insights into the stability and physical properties of three-dimensional graphene structures. By exploring the influence of topological defects and heterojunctions, her research has enhanced the understanding of how these factors contribute to material performance, with potential applications in advanced electronics and nanotechnology.
  2. Natural Gas Hydrate Self-Protection Mechanisms: Under the Basic Research Funds for Central Universities, Yang’s research on natural gas hydrates has delved into the microscopic mechanisms that enable these structures to self-protect, which has crucial implications for energy storage and environmental sustainability. Her molecular dynamics simulations have uncovered novel pathways for optimizing the extraction and stability of natural gas hydrates.
  3. Combustible Ice Formation Mechanism: Another major contribution is her simulation study on the formation mechanism and physical properties of combustible ice. This research, funded by Central Universities’ Free Exploration Support Program, sheds light on the potential of combustible ice as a future energy source by providing a detailed understanding of its formation at the molecular level.
  4. Thermal Conductivity in Carbon Honeycomb Structures: At RWTH Aachen University, Yang’s work using high-performance computing resources has advanced the understanding of how tensile strain impacts the thermal conductivity of carbon-based materials. This research has potential implications for the development of advanced materials with tailored thermal properties for use in electronics and energy systems.
  5. Ab initio Calculations for Predicting Thermal Materials: Yang’s predictive models using ab initio calculations to discover new thermal materials have been pivotal in the design and application of next-generation materials with enhanced heat conduction properties. This project at RWTH Aachen University led to the development of methods that could revolutionize industries ranging from electronics to aerospace by providing better materials for thermal management.

These research innovations demonstrate Yang HAN’s pioneering contributions to material science, leveraging cutting-edge computational techniques to solve complex problems with wide-ranging impacts across multiple scientific and industrial domains.

Research Interest: 

Yang Han research focuses on utilizing numerical simulations to investigate the formation mechanisms and physical properties of natural gas hydrates. Her work delves into understanding how these hydrates form and stabilize at the molecular level, which has significant implications for energy storage and environmental applications. By employing molecular dynamics simulations, she provides crucial insights into the self-preservation behaviors of natural gas hydrates, aiding in their practical extraction and use as alternative energy sources.

Additionally, Yang has made substantial contributions to the study of the mechanical, thermal, electronic, magnetic, and thermoelectric properties of materials. Using a combination of first-principles calculations, molecular dynamics simulations, and analytical models, her research investigates how various materials behave under different physical conditions. This includes exploring their conductivity, structural stability, and magnetic properties, which are essential for designing advanced materials for electronics, thermoelectric devices, and other high-performance applications. Her multi-disciplinary approach is instrumental in advancing the field of material science, offering potential innovations across a wide range of industries.

Contributions: 

Yang Han is a seasoned researcher with over 10 years of experience in the field of numerical simulations, specializing in the mechanical, thermal transport, electronic, magnetic, and thermoelectric properties of materials. Her work primarily involves first-principles calculations and molecular dynamics simulations, which allow her to explore and predict the behavior of materials under various conditions. Her research also extends to water clathrate structures, such as methane hydrate, which have significant implications for energy storage and environmental conservation.

Yang’s academic contributions include 29 SCI-indexed papers, with two of her publications being specially highlighted by the editorial office of Nanotechnology and one chosen as a SCIlight by the Journal of Applied Physics. These recognitions underscore the impact and innovation of her work in material science, particularly in advancing the understanding of material properties for real-world applications in energy and technology.

Top Notable Publications

Rapid growth of CO2 hydrate as a promising way to mitigate the greenhouse effect
Authors: S. Jia, L. Yang, Y. Han, T. Zhang, X. Zhang, P. Gong, S. Du, Y. Chen, J. Ding
Year: 2024
Journal: Materials Today Physics, Article No. 101548
Citations: Not yet available (2024 publication)

Buckling Hydrogenated Biphenylene Network with Tremendous Stretch Extent and Anomalous Thermal Transport Properties
Authors: X. Zhang, M. Poulos, K. Termentzidis, Y. Han, D. Zhao, T. Zhang, X. Liu, S. Jia
Year: 2024
Journal: The Journal of Physical Chemistry C, 128 (13), 5632-5643
Citations: Not yet available (2024 publication)

Ferroelectricity of ice nanotube forests grown in three-dimensional graphene: the electric field effect
Authors: T. Zhang, Y. Han, C. Luo, X. Liu, X. Zhang, Y. Song, Y. T. Chen, S. Du
Year: 2024
Journal: Nanoscale, 16 (3), 1188-1196
Citations: 2

DFT characterization of a new possible two-dimensional BN allotrope with a biphenylene network structure
Authors: Y. Han, T. Hu, X. Liu, S. Jia, H. Liu, J. Hu, G. Zhang, L. Yang, G. Hong, Y. T. Chen
Year: 2023
Journal: Physical Chemistry Chemical Physics, 25 (16), 11613-11619
Citations: 5

Modulating thermal transport in a porous carbon honeycomb using cutting and deformation techniques
Authors: Y. Han, C. Zhao, H. Bai, Y. Li, J. Yang, Y. T. Chen, G. Hong, D. Lacroix, M. Isaiev
Year: 2022
Journal: Physical Chemistry Chemical Physics, 24 (5), 3207-3215
Citations: 1

Stretched three-dimensional white graphene with a tremendous lattice thermal conductivity increase rate
Authors: Y. Han, Y. Liang, X. Liu, S. Jia, C. Zhao, L. Yang, J. Ding, G. Hong
Year: 2022
Journal: RSC Advances, 12 (35), 22581-22589
Citations: 3

Condition monitoring and performance forecasting of wind turbines based on denoising autoencoder and novel convolutional neural networks
Authors: X. Jia, Y. Han, Y. Li, Y. Sang, G. Zhang
Year: 2021
Journal: Energy Reports, 7, 6354-6365
Citations: 37

Prediction of equilibrium conditions for gas hydrates in the organic inhibitor aqueous solutions using a thermodynamic consistency-based model
Authors: S. Li, Y. Li, L. Yang, Y. Han, Z. Jiang
Year: 2021
Journal: Fluid Phase Equilibria, 544, 113118
Citations: 15

Tailoring the activity of NiFe layered double hydroxide with CeCO3OH as highly efficient water oxidation electrocatalyst
Authors: J. Ding, Y. Han, G. Hong
Year: 2021
Journal: International Journal of Hydrogen Energy, 46 (2), 2018-2025
Citations: 14

Jianjia Wang | Complex Networks | Best Researcher Award

Published on by Physicist Particle

Assist Prof Dr. Jianjia Wang | Complex Networks | Best Researcher Award

Scopus Profile

Educational Details

Dr. Jianjia Wang holds a Ph.D. in Computer Science from the University of York, United Kingdom (2014-2018), where he specialized in computer vision and pattern recognition within the Department of Computer Science. Prior to his doctoral studies, he completed a Master of Science in Electronic Engineering from the Hong Kong University of Science and Technology (2011-2012), focusing on advanced electronic and computer engineering topics. He also earned a Bachelor of Engineering in Measuring & Control Technology and Instrumentation from Nanjing University of Posts and Telecommunications (2007-2011), where he built a strong foundation in automation and instrumentation technologies. His academic background integrates expertise in both electronics and computer science.

Employment

Dr. Jianjia Wang served as a Lecturer at the School of Computer Science and Engineering, Shanghai University, P.R. China, from 2018 to 2023. During this period, he was also an Adjunct Professor with the Council on International Educational Exchange (CIEE) at Rutgers, The State University of New Jersey, USA, from 2020 to 2022, where he contributed to the Department of Computer Science. Prior to these roles, he worked as a Project Engineer specializing in 3D Machine Vision at the Hong Kong Applied Science and Technology Research Institute (HK ASTRI) from 2013 to 2014, where he was involved in the Display Group and focused on 3D Machine Vision Systems. His professional experience encompasses a broad range of expertise in computer vision, engineering, and international academic collaboration.

Teaching Experience

Dr. Jianjia Wang has a diverse teaching portfolio that spans multiple institutions and disciplines. At Rutgers, The State University of New Jersey, he taught CS111 Introduction to Computer Science in Autumn 2020 and CS112 Data Structures and Algorithms in Spring 2021. During his tenure at Denison University, he delivered CS109 Introduction to Computer Programming in Spring 2021. At Shanghai University, Dr. Wang taught several courses, including CS08306145 Big Data: From Theory to Practice in Spring 2021, CS08696027 Signal Processing in Autumn 2020, and CS08695001 Blockchain and Cryptocurrency during the 2020-2021 academic year. Additionally, he has experience teaching a range of subjects at the University of York, including COM00001I-A Artificial Intelligence (ARIN), COM00005C-A Mathematical Foundations of Computer Science (MFCS), and COM00006C-A Numerical Analysis (NUMA), across various terms from 2015 to 2017. His teaching experience reflects a strong background in computer science and engineering, encompassing both theoretical and practical aspects of the field.

Grants

Dr. Jianjia Wang has been the Principal Investigator on several significant research projects. From January 2021 to December 2023, he led the Automatic Testing Aging System in New Energy project under the Innovative Entrepreneurial Program of Technique Leader in Fei-Feng Talent, Wuxi Science and Technology Bureau, with a funding of CNY 3,000,000. He also directed the Using Complex Networks to Analyze Urban Spatial Density and Population project funded by the Shanghai Pujiang Talent Program, receiving CNY 300,000 from October 2021 to September 2023. His research on Structural Properties in Complex Networks with Statistical Pattern Recognition was supported by the Oversea Visiting Fellowship Scheme of the Ministry of Science and Technology of P.R. China, with a grant of CNY 350,000 from January 2022 to December 2023. Additionally, Dr. Wang managed the Statistical Structural Pattern Recognition in Complex Networks project, funded by the Science and Technology Commission of Shanghai Municipality, with CNY 150,000 from January 2022 to January 2023. He also received Young Professor Funding from the Shanghai Municipal Education Commission for the project Young Professor Funding of Shanghai University, which was awarded CNY 40,000 from January 2021 to December 2022. Other notable projects include Analyzing the Spatial and Population in the City with Complex Networks and Signal Processing, funded by the Grant Joint Project of Shanghai University and the Key Course Project of Shanghai University, respectively.

In addition to his principal investigator roles, Dr. Wang has been a co-investigator in various collaborative projects. He contributed to the Epidemic Spread and Prediction Model in Complex Spatio-temporal Environment, funded by the Ministry of Science and Technology of China, with a budget of CNY 700,000 from October 2021 to October 2024. He also worked on the Active Learning Assists Diagnosis of Gastrointestinal Diseases project with the Science and Technology Commission of Shanghai Municipality, which received CNY 200,000 from April 2020 to June 2023, and the Multi-center Capsule Endoscopy Image Federation Active Learning project funded by the National Natural Science Foundation of China (NSFC), with a grant of CNY 700,000 from January 2022 to December 2025.

Academic Service

Dr. Jianjia Wang has been actively involved in various academic and professional roles. Since 2020, he has served as a Recruitment Ambassador for the University of York, UK, where he helps to attract and engage prospective students. Additionally, he has been an Associate Editor for the International Journal of Complexity, Pattern Recognition since 2018, contributing to the journal’s editorial board. Dr. Wang is also a reviewer for numerous prestigious journals and conferences, including Pattern Recognition, Pattern Recognition Letters, IEEE Intelligent Systems, IEEE Access, Scientific Reports, Information Systems, Applied Sciences, Journal of Complex Networks, and Expert Systems with Applications. His expertise extends to reviewing for major conferences such as the IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR), International Conference on Pattern Recognition (ICPR), Asian Conference on Computer Vision (ACCV), Winter Conference on Applications of Computer Vision (WACV), and the British Machine Vision Conference (BMVC). His extensive involvement in these roles reflects his significant contribution to the fields of computer vision and pattern recognition.

Research Interests

Dr. Jianjia Wang’s expertise spans several critical areas of computer science, including Data Science, Pattern Recognition, Artificial Intelligence (AI), and Complex Networks. His research in Data Science focuses on extracting meaningful insights from vast datasets, enabling advancements in fields such as urban planning, healthcare, and environmental management. Through Pattern Recognition, Dr. Wang has developed algorithms that identify patterns in data, contributing to innovations in image recognition, natural language processing, and predictive modeling. His work in AI harnesses machine learning and deep learning to solve complex problems, particularly in automating processes and enhancing decision-making systems. Additionally, his contributions to Complex Networks involve analyzing interconnected systems, such as urban networks and social structures, to improve efficiency and sustainability in community infrastructures. This broad expertise allows Dr. Wang to apply advanced computational techniques to address real-world challenges, creating a significant societal impact.

Top Notable Publications

The Ihara Zeta Function as a Partition Function for Network Structure Characterisation

Authors: Wang, J., Hancock, E.R.

Journal: Scientific Reports

Year: 2024

Volume: 14

Issue: 1

Article Number: 18386

Citations: 0

Exploring the Regional Development Trend in New York City

Authors: Yu, T., Zhu, H., Wu, X., Wang, J.

Journal: Proceedings of SPIE – The International Society for Optical Engineering

Year: 2024

Volume: 13018

Article Number: 130184P

Citations: 0

Exploring the Regional Function in Shanghai and New York City

Authors: Yu, T., Wu, X., Wang, J.

Journal: Proceedings of SPIE – The International Society for Optical Engineering

Year: 2024

Volume: 13018

Article Number: 130184O

Citations: 0

Construction of Gene Expression Patterns to Identify Critical Genes Under SARS-CoV-2 Infection Conditions

Authors: Yu, X., Li, W., Wang, J., Wu, X., Sheng, B.

Journal: IEEE/ACM Transactions on Computational Biology and Bioinformatics

Year: 2024

Volume: 21

Issue: 4

Pages: 607–618

Citations: 0

Multiple Detection Model Fusion Framework for Printed Circuit Board Defect Detection

Authors: Wu, X., Zhang, Q., Wang, J., Yao, J., Guo, Y.

Journal: Journal of Shanghai Jiaotong University (Science)

Year: 2023

Volume: 28

Issue: 6

Pages: 717–727

Citations: 0

Statistical Structural Inference from Edge Weights Using a Mixture of Gamma Distributions

Authors: Wang, J., Hancock, E.R.

Journal: Journal of Complex Networks

Year: 2023

Volume: 11

Issue: 5

Article Number: cnad038

Citations: 0

Space or Time for Video Classification Transformers

Authors: Wu, X., Tao, C., Zhang, J., Liu, Y., Guo, Y.

Journal: Applied Intelligence

Year: 2023

Volume: 53

Issue: 20

Pages: 23039–23048

Citations: 0

 

 

Marcel Ausloos | Econophysics | Best Researcher Award

Published on by Physicist Particle

Prof Dr. Marcel Ausloos | Econophysics | Best Researcher Award

Scopus Profile

Educational Details

Prof. Dr. Marcel Ausloos earned his engineering degree in physics from the University of Liège in Liège, Belgium, in July 1967. He continued his academic journey at Brown University in Providence, Rhode Island, where he obtained his Master of Science degree in January 1970. He completed his Ph.D. in January 1973 at Temple University in Philadelphia, Pennsylvania.

Employment:

Prof. Dr. Marcel Ausloos has held various academic and research positions throughout his career. He was a Visiting Professor at Freie Universität Berlin, Germany, from 1972 to 1973. At the University of Liège in Belgium, he served as a Research Fellow from 1973 to 1974, Research Associate from 1974 to 1978, and Assistant from 1978 to 1985. He was promoted to Maître de Conférences in 1979, 1st Assistant from 1986 to 1990, and Chef de Travaux from 1990 to 1997. He continued as Chargé de Cours at the University of Liège from 1997 to 2009. Additionally, he was Chargé de Mission at the General Directorate of Culture, French Community of Belgium, from 1988 to 1992. Prof. Ausloos was a Professor (0.2 FTE) at the School of Business, University of Leicester, starting in 2014, and served as a Professor at Bucharest University of Economic Studies from 2018 to 2022. Currently, he is a Principal Investigator at the University of Babeș-Bolyai in Cluj-Napoca, Romania, from 2022 to 2025.

Professional Experience : 

Prof. Dr. Marcel Ausloos has made significant contributions to various areas of physics. His research spans statistical physics, focusing on transport properties, phase transitions, fractals, growth models, econophysics, sociophysics, meteorology, data analysis, scientometrics, and biostatistics. In condensed matter physics, his work includes magnetism, superconductivity, optics, biophysics, and materials science.From 1988 to 2009, he served as Director of the SUPRAS group and the SUPRATECS Center. He is also a co-founder of GRASP and has been the Director of GRAPES.In his teaching career, Prof. Ausloos has taught undergraduate courses such as Introductory Physics for Premedical and Paramedical Students, Introductory Statistics, Condensed Matter, and Electrodynamics. At the graduate level, he has taught Thermodynamics, Solid State Physics, Classical Electrodynamics, Statistical Physics, and Fractals.

Top Notable Publications

Principles of Digital Professionalism for the Metaverse in Healthcare
Mohammadzadeh, Z., Shokri, M., Saeidnia, H.R., Ausloos, M., Ghiasi, N.
BMC Medical Informatics and Decision Making, 2024, 24(1), 201.
Open Access Article

The State of Health in the European Union (EU-27) in 2019: A Systematic Analysis for the Global Burden of Disease Study 2019
Santos, J.V., Padron-Monedero, A., Bikbov, B., Zeitoun, J.-D., Zumla, A.
BMC Public Health, 2024, 24(1), 1374.
Open Access Article

A Theory of Best Choice Selection through Objective Arguments Grounded in Linear Response Theory Concepts
Ausloos, M., Rotundo, G., Cerqueti, R.
Physics (Switzerland), 2024, 6(2), pp. 468–482.
Open Access Article

Global Burden and Strength of Evidence for 88 Risk Factors in 204 Countries and 811 Subnational Locations, 1990–2021: A Systematic Analysis for the Global Burden of Disease Study 2021
Brauer, M., Roth, G.A., Aravkin, A.Y., Murray, C.J.L., Gakidou, E.
The Lancet, 2024, 403(10440), pp. 2162–2203.
Open Access Article

Burden of Disease Scenarios for 204 Countries and Territories, 2022–2050: A Forecasting Analysis for the Global Burden of Disease Study 2021
Vollset, S.E., Ababneh, H.S., Abate, Y.H., Smith, A.E., Murray, C.J.L.
The Lancet, 2024, 403(10440), pp. 2204–2256.
Open Access Article

Global Incidence, Prevalence, Years Lived with Disability (YLDs), Disability-Adjusted Life-Years (DALYs), and Healthy Life Expectancy (HALE) for 371 Diseases and Injuries in 204 Countries and Territories and 811 Subnational Locations, 1990–2021: A Systematic Analysis for the Global Burden of Disease Study 2021
Ferrari, A.J., Santomauro, D.F., Aali, A., Vos, T., Murray, C.J.L.
The Lancet, 2024, 403(10440), pp. 2133–2161.
Open Access Article

Global Burden of 288 Causes of Death and Life Expectancy Decomposition in 204 Countries and Territories and 811 Subnational Locations, 1990–2021: A Systematic Analysis for the Global Burden of Disease Study 2021
Naghavi, M., Ong, K.L., Aali, A., Wool, E.E., Murray, C.J.L.
The Lancet, 2024, 403(10440), pp. 2100–2132.
Open Access Article

 

Eman Aldakheel | Artificial Intelligence | Best Researcher Award

Published on by Physicist Particle

Assist Prof Dr. Eman Aldakheel | Artificial Intelligence | Best Researcher Award

Scopus Profile

Orcid Profile

Educational Details:

Dr. Eman Aldakheel holds a Doctor of Philosophy in Computer Science from the University of Illinois at Chicago, where her dissertation, titled “Deadlock Detector and Solver (DDS),” focused on developing solutions for deadlock issues in computer systems. She earned her Master of Science in Computer Science from Bowling Green State University in Ohio, with a thesis titled “A Cloud Computing Framework for Computer Science Education,” highlighting her interest in leveraging technology for educational advancement. Dr. Aldakheel completed her Bachelor of Science in Computer Science with Honors from Imam Abdulrahman bin Faisal University in Dammam, Saudi Arabia, laying the foundation for her career in academia and research.

Academic Experience:

Dr. Eman Aldakheel has an extensive teaching and training background, starting as an instructor at the New Horizons Institute in Khobar, Saudi Arabia, in 2007, where she trained students on ICDL and IC3 certifications and taught various computer-related courses. She later joined Imam Abdulrahman bin Faisal University (formerly Dammam University) as an instructor, teaching basic computer skills and Microsoft Office applications to students in the Geography department. She also taught computer basics to girls at Riyadh Al-Islam Schools, working with students from elementary to high school levels. From 2012 to 2020, Dr. Aldakheel served as a lecturer at Princess Nourah Bint Abdulrahman University, where she contributed as a research assistant on software engineering projects and taught object-oriented programming. Since Fall 2020, she has been an Assistant Professor at the same institution, teaching various computer science courses ranging from programming to natural language processing. Dr. Aldakheel effectively adapted to remote teaching tools like Blackboard, Teams, and Zoom during the COVID-19 pandemic, ensuring uninterrupted learning for her students.

Honors and Awards:

Dr. Eman Aldakheel has actively participated in prestigious academic workshops and conferences, including the CRA-Women Grad Cohort Workshop, which supports the professional development of women in computing. Her academic achievements have earned her multiple travel awards, including ACM’s SRC (Student Research Competition) Travel Award and the HPDC (High Performance Distributed Computing) Travel Award, both of which provided her with opportunities to present her research and engage with global experts in the field. These accolades reflect her commitment to advancing her knowledge and contributing to the broader academic community.

Service Activities:

Dr. Eman Aldakheel has played a pivotal role in fostering the growth and development of talented students at Princess Nourah Bint Abdulrahman University. She has been actively involved in planning programs and activities aimed at nurturing high-achieving students, ensuring they receive the support and opportunities needed to excel. Dr. Aldakheel designed and built the foundation for the “Foundations of Programming” (GN 044) course, recording its lectures to enhance learning accessibility. Additionally, she supervises the College of Computer and Information student magazine, encouraging student participation in scholarly activities. Her involvement extends to various committees, where she serves as a judge or supervisor for hackathons, contributing her expertise to inspire innovation and creativity among students.

Granted Projects:

Dr. Eman Aldakheel is actively involved in several significant research projects. In 2023, she contributed to the “Researchers Supporting Project” at Princess Nourah Bint Abdulrahman University, under project number PNURSP2023R409. She is also leading two research initiatives funded by the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia. The first, under project number RI-44-0618, focuses on the “Detection and Identification of Plant Leaf Diseases using YOLOv4,” running from November 2022 to May 2024. The second project, WE-44-0279, explores the “Use of Modern Machine Learning Techniques to Combat Extremism and the Role of Women,” also from November 2022 to May 2024. These projects highlight Dr. Aldakheel’s expertise in machine learning and its application to various fields, from agriculture to social issues.

Top Notable Publications

“Performance of Rime-Ice Algorithm for Estimating the PEM Fuel Cell Parameters”

Authors: Ismaeel, A.A.K., Houssein, E.H., Khafaga, D.S., Aldakheel, E.A., Said, M.

Year: 2024

Journal: Energy Reports

Citations: 3

“Outlier Detection for Keystroke Biometric User Authentication”

Authors: Ismail, M.G., Salem, M.A.-M., El Ghany, M.A.A., Aldakheel, E.A., Abbas, S.

Year: 2024

Journal: PeerJ Computer Science

Citations: 0

“Mobile-UI-Repair: A Deep Learning-Based UI Smell Detection Technique for Mobile User Interface”

Authors: Ali, A., Xia, Y., Navid, Q., Aldakheel, E.A., Khafaga, D.

Year: 2024

Journal: PeerJ Computer Science

Citations: 2

“Enhancing Security and Privacy in Distributed Face Recognition Systems through Blockchain and GAN Technologies”

Authors: Ghani, M.A.N.U., She, K., Rauf, M.A., Aldakheel, E.A., Khafaga, D.S.

Year: 2024

Journal: Computers, Materials and Continua

Citations: 0

“Detection and Identification of Plant Leaf Diseases using YOLOv4”

Authors: Aldakheel, E.A., Zakariah, M., Alabdalall, A.H.

Year: 2024

Journal: Frontiers in Plant Science

Citations: 1

“Performance of the Walrus Optimizer for Solving an Economic Load Dispatch Problem”

Authors: Said, M., Houssein, E.H., Aldakheel, E.A., Khafaga, D.S., Ismaeel, A.A.K.

Year: 2024

Journal: AIMS Mathematics

Citations: 2

“Efficient Analysis of Large-Size Bio-Signals Based on Orthogonal Generalized Laguerre Moments of Fractional Orders and Schwarz–Rutishauser Algorithm”

Authors: Aldakheel, E.A., Khafaga, D.S., Fathi, I.S., Hosny, K.M., Hassan, G.

Year: 2023

Journal: Fractal and Fractional

Citations: 1

“Performance of Osprey Optimization Algorithm for Solving Economic Load Dispatch Problem”

Authors: Ismaeel, A.A.K., Houssein, E.H., Khafaga, D.S., AbdElrazek, A.S., Said, M.

Year: 2023

Journal: Mathematics

Citations: 17

“CyberHero: An Adaptive Serious Game to Promote Cybersecurity Awareness”

Authors: Hodhod, R., Hardage, H., Abbas, S., Aldakheel, E.A.

Year: 2023

Journal: Electronics (Switzerland)

Citations: 3

Carrasquilla, M.D.L., Sun, M., Long, T., Huang, L., & Zheng, Y. (2024). Seismic anisotropy of granitic rocks from a fracture stimulation well at Utah FORGE using ultrasonic measurements. Geothermics, 123, 103129.

Carrasquilla, M.D.L., Parsons, J., Long, T., Zheng, Y., & Han, D.-H. (2023). Ultrasonic measurements of elastic anisotropy of granitic rocks for enhanced geothermal reservoirs. SEG Technical Program Expanded Abstracts, 2023-August, 79–83.

Carrasquilla, M.D.L., Costa, M.D.F.B., Souza, I.J.S., Amanajás, C.E., & Nunes, L.R.A. (2022). Geological, geophysical and mathematical analysis of synthetic bulk density logs around the world – Part II – The use of non-linear regression on empirical parameters estimation. Journal of Applied Geophysics, 206, 104838.

Carrasquilla, M.D.L., Carvalho, C.P., Costa, M.D.F.B., Amanajás, C.E., & Rautino, L. (2022). Geological, geophysical and mathematical analysis of synthetic bulk density logs around the world – Part I – The use of linear regression on empirical parameters estimation. Journal of Applied Geophysics, 204, 104733.