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Ali Reza Keivanimehr | AI in healthcare | Best Researcher Award

21b4bddf87157652317827146367558f — Wed, 19 Feb 2025 04:24:23 +0000

Mr.Ali Reza Keivanimehr | AI in healthcare
| Best Researcher Award

Mr. Ali RezaKeivanimehr , Amirkabir University of Technology (Tehran’s Polytechnic), Iran.

Ali Reza Keivanimehr is an exceptional early-career researcher with a solid academic foundation, a promising research trajectory in machine learning applications for healthcare, and strong technical expertise. His combination of research, teaching, and technical projects highlights a well-rounded profile. His contributions, especially in the use of TinyML for cardiovascular diagnosis, are commendable and align with global health priorities.

Publication Profile

Google scholar

Education :

Master of Science in Information Technology Engineering – Internet of Things (IoT) (2022 – 2025)Amirkabir University of Technology (Tehran Polytechnic), Tehran, IranRanked 403rd in QS World University Rankings 2024GPA: 3.53/4 (17.48/20) – 3rd highest in 2022 faculty entranceThesis: Applications of TinyML in Prediction and Diagnosis of Cardiovascular DiseasesSupervisor: Dr. Mohammad Akbari | Advisor: Dr. Abbas AhmadiBachelor of Science in Computer Engineering – Software Engineering (2018 – 2021)Imam Khomeini International University of Qazvin, Qazvin, IranProject: Designing a Software Interface for Industrial Machinery Maintenance

Experience :

Research Assistant (2022 – Present)
Data Science Lab (DSLab), Amirkabir University of Technology, Tehran, IranConducting research on TinyML and edge intelligence applications in cardiovascular disease prediction.Teaching Assistant — Machine Learning and Pattern Recognition (2024 – 2025)Amirkabir University of Technology, Tehran, IranAssisted in course instruction, project supervision, and student evaluations under Dr. Alireza Rezvanian.Teaching Assistant — Data Structure and Algorithms (2019 – 2020)
Imam Khomeini International University of Qazvin, Qazvin, IranSupported coursework delivery, assignments, and exam preparations under Morteza Mohammadi Zanjireh.

Research Focus :

Natural Language Processing (NLP)Graph Neural NetworksEdge IntelligenceExplainable Artificial Intelligence (XAI)Generative Adversarial Networks (GANs)Dr. Keivanimehr’s research centers on Tiny Machine Learning (TinyML) and edge intelligence, with a specific emphasis on their applications in cardiovascular disease monitoring. He explores the deployment of machine learning models on low-power, resource-limited devices to facilitate real-time analytics and pervasive monitoring for patients with cardiac anomalies.

Skills and Expertise:

As a research assistant, Dr. Keivanimehr has developed expertise in machine learning, classification, and supervised learning. His technical proficiency includes a focus on computational health and biomedical applications, particularly in the context of resource-constrained devices.Programming: PythonMachine Learning Frameworks: PyTorch, TensorFlowBig Data Tools: Apache SparkLanguages: TOEFL iBT (Score: 109 | Reading: 28 | Listening: 30 | Speaking: 26 | Writing: 25)

Awards:

48th Rank among 5000+ participants, National Entrance Exam for Master Studies in IT Engineering (2022)3rd Rank in IT Engineering Master’s cohort based on GPA (2022 – Present)Full Master’s Scholarship: Awarded for excellence in national entrance exams; covers tuition, dormitory, and partial food expenses (2022 – Present)Full Bachelor’s Scholarship: Granted for top performance in national entrance exams; included tuition, accommodation, and meal support (2018 – 2021)

Publication

Keivanimehr, A., & Akbari, M. (2024). TinyML and Edge Intelligence Applications in Cardiovascular Disease: A Survey. Computers in Biology and Medicine. DOI: 10.1016/j.compbiomed.2025.109653

Conclusion

Ali Reza Keivanimehr is a suitable candidate for the Best Researcher Award. His strong academic record, impactful research, and consistent growth in machine learning and edge intelligence demonstrate his potential as a leading researcher in his field. With further international exposure and expanded publication efforts, he is poised to make significant contributions to both academia and industry.

The post Ali Reza Keivanimehr | AI in healthcare | Best Researcher Award first appeared on ScienceFather.

Rispandi | Optical sensing technology | Best Researcher Award

21b4bddf87157652317827146367558f — Mon, 17 Feb 2025 04:47:36 +0000

Mr.Rispandi | Optical sensing technology | Best Researcher Award

Mr. Rispandi,Lecturer, Indonesia.

Mr. Rispandi is a promising researcher with a strong academic background, an innovative approach to sensor technology, and leadership experience. His contributions to optical gas sensors and related technologies, particularly for healthcare and environmental monitoring, are commendable. His publications and technical skills further strengthen his candidacy for the Best Researcher Award. However, expanding his collaborations and seeking funding for his projects could further enhance his impact in the field.

Publication Profile

Google scholar

orcid

scopus

Education :

Rispandi holds a Master of Science in Mechanical Engineering from Ming Chi University of Technology, New Taipei City, Taiwan, completed between February 2021 and December 2022. His master’s research focused on the Development of New Optical Gas Sensors Based on Perovskite Quantum Dots, with key research areas including optical sensors, gas sensors, 3D printing, optical metrology, and electrospun nanofibers. He achieved an impressive GPA of 4.17/4.3. Prior to this, he earned a Bachelor of Engineering in Mechanical Engineering from the University of Bengkulu, Indonesia (August 2015 – December 2019). His undergraduate research focused on the Manufacture, Assembly, and Experimental Test of Generator Stand on the Translational Motion–Rotation for Sea Wave Power Plants.

Experience :

Rispandi has accumulated extensive research and teaching experience in mechanical engineering, particularly in optical sensor technology. Since February 2021, he has worked as a Research Assistant at Ming Chi University of Technology, under the guidance of Prof. Cheng-Shane Chu. His research involves the development of ratiometric optical gas sensors, perovskite quantum dots, electrospun fiber-based sensors, and biomedical applications of gas detection. He has worked on various projects related to ammonia, oxygen, and nitric oxide sensors utilizing advanced optical and nanomaterial techniques.Additionally, he served as a Teaching Assistant in the Optical Metrology Lab at Ming Chi University of Technology from February 2021 to 2022. His role involved assisting with experiments related to electro-optic amplitude modulation, interferometry (Mach-Zehnder, Sagnac, and Michelson), diffraction, and optical grating techniques.Before pursuing his master’s degree, he worked as a Research Engineer at the University of Bengkulu (August 2019 – February 2020), where he contributed to the development of sea wave power plants, performing stress analysis using the finite element method (FEM) and conducting performance evaluations of wave energy conversion systems.

Research Focus :

Rispandi’s research focuses on optical gas sensing technologies, specifically the development of optical sensors using perovskite quantum dots and electrospun fibers. His work has applications in healthcare, biomedical diagnostics, environmental monitoring, and renewable energy systems. He specializes in optical fiber-based gas sensors, ratiometric detection methods, and materials engineering for sensor enhancement. His research has led to significant contributions in the detection of ammonia, oxygen, and nitric oxide gases using innovative optical approaches.

Skills and Expertise:

Rispandi has a strong background in mechanical design and simulation, with expertise in Autodesk Inventor, stress analysis, finite element method (FEM), and mechanical engineering analysis (MEH). He is proficient in optical fiber sensor technology, gas sensing techniques, optical measurement, and optical metrology. His technical skills extend to 3D printing, electrospinning, and advanced analytical methods. He also possesses strong competencies in problem-solving, leadership, communication, and strategic planning.

Awards:

Certificate of Appreciation as Governor of the Most Valuable Region in FORMMIT Awards, Taiwan (2023) for his leadership in student organizations.Awardee of the Master’s Program Scholarship at Ming Chi University of Technology, Taiwan (2021) for academic excellence.,Bidikmisi Scholarship Awardee from the Ministry of Education and Culture, Republic of Indonesia (2015), a competitive scholarship for outstanding students.

Publication :

Mask Detection System with Computer Vision-Based on CNN and YOLO Method Using Nvidia Jetson Nano
- Authors: AA Hakim, E Juanara, R Rispandi
- Journal: Journal of Information System Exploration and Research 1 (2)
- Citations: 15
- Year: 2023

Optical dual gas sensor for simultaneous detection of nitric oxide and oxygen
- Authors: R Mesin, CS Chu
- Journal: Chemosensors 11 (8), 454
- Citations: 10
- Year: 2023

Optical fluorescent sensor based on perovskite QDs for nitric oxide gas detection
- Authors: D Kumar, R Mesin, CS Chu
- Journal: Applied Optics 62 (12), 3176-3181
- Citations: 10
- Year: 2023

Ratiometric optical oxygen sensor based on perovskite quantum dots and Rh110 embedded in an ethyl cellulose matrix
- Authors: R Mesin, CS Chu, ZL Tseng
- Journal: Optical Materials Express 13 (4), 945-955
- Citations: 9
- Year: 2023

Finite element method for stress analysis in the frame holder of generator translation and rotation motion on vertical direction mechanism for sea wave power plant
- Authors: Y Suhartini, A Indriani
- Journal: IOP Conference Series: Materials Science and Engineering 1034 (1), 012008
- Citations: 7
- Year: 2021

Performance of Generator Translation and Rotation Motion on Vertical Direction for Sea Wave Power Plant
- Authors: A Indriani, Y Suhartini
- Journal: IOP Conference Series: Materials Science and Engineering 1007 (1), 012044
- Citations: 4
- Year: 2020

Analisis tegangan pada struktur mesin pencacah plastik menggunakan metode elemen hingga (MEH) dan uji kerja mesin pencacah plastik
- Authors: H Hendra, A Indriani, A Mardian, N Kholik, R Rispandi, Y Suhartini
- Journal: METAL: Jurnal Sistem Mekanik dan Termal 5 (1), 9-16
- Citations: 3
- Year: 2021

Stress analysis on the frame holder of generator translation motion on horizontal direction for sea wave power plant using finite element method (FEM)
- Authors: A Indriani, S Yenni, W Aswata, A Tanjung
- Journal: IOP Conference Series: Materials Science and Engineering 909 (1), 012033
- Citations: 2
- Year: 2020

Optical dual gas sensor for biomedical monitoring of NO and O2 based on electrospun fibers containing CsPbBr3 QDs and PtTFPP
- Authors: CS Chu, S Nugroho, MI Ammarullah
- Journal: Results in Optics 18, 100781
- Citations: 1
- Year: 2025

Enhanced sensing properties of optical ammonia sensor based on electrospun fibers containing Eosin-Y and silver nanoparticles

Authors: CS Chu, MS Simanjuntak
Journal: Materials Today Communications 41, 110524
Citations: 1
Year: 2024

Conclusion

Mr. Rispandi is highly deserving of the Best Researcher Award due to his dedication, academic excellence, and substantial contributions to the development of cutting-edge sensor technologies. With some additional focus on interdisciplinary research and funding acquisition, he has the potential to make even greater strides in his field. His future endeavors are poised to have a lasting impact on both scientific communities and industry applications.

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Dongsong Zhang | Mobile health | Best Researcher Award

21b4bddf87157652317827146367558f — Sat, 15 Feb 2025 08:12:45 +0000

Dr.Dongsong Zhang |Mobile health|Best Researcher Award

Dr. Dongsong Zhang UNC Charlotte,United States.

Dr. Dongsong Zhang is a Professor in the Department of Business Information Systems and Operations Management at the University of North Carolina at Charlotte. He earned his Ph.D. in Management Information Systems from the University of Arizona. Dr. Zhang’s research interests include mobile and intelligent health systems, human-computer interaction, and business analytics. He has published extensively in top-tier journals and conferences, contributing significantly to the fields of information systems and health informatics.

Publication Profile

scopus

Education :

Dr. Dongsong Zhang earned his Ph.D. in Management Information Systems from The Eller College of Management at the University of Arizona in 2002. He also holds an M.S. in Natural Language Processing from the Institute of Psychology, Chinese Academy of Sciences (1995) and a B.S. in Electrical & Computer Engineering from the Branch Campus of Peking University, Beijing, China (1990).

Experience :

Dr. Zhang has extensive experience in academia and research leadership. He is currently the Interim Executive Director of the School of Data Science at the University of North Carolina at Charlotte (UNCC). Previously, he served as the Director of Research at the same school (2020-2024). Since 2018, he has been the Belk Endowed Chair Professor in Business Analytics at the Belk College of Business and a Professor (Courtesy) in Computer Science at UNCC.Prior to joining UNCC, Dr. Zhang was a Full Professor (2014-2018), Associate Professor (2007-2014), and Assistant Professor (2002-2007) in the Department of Information Systems at the University of Maryland, Baltimore County (UMBC). His early career includes research roles at the Center for the Management of Information, University of Arizona (1997-2002), and the Institute of Psychology, Chinese Academy of Sciences (1990-1996).

Research Focus :

Dr. Zhang’s research revolves around data-driven decision-making and intelligent systems, with a particular focus on:AI and Machine Learning for Business IntelligenceFake News Detection & Online Misinformation AnalysisCybersecurity, Phishing Detection, and Behavioral AnalyticsNatural Language Processing in Social Media & Public HealthHuman-Computer Interaction (HCI) & Adaptive SystemsHis projects explore how emerging technologies can be leveraged to improve cybersecurity, healthcare, and business intelligence.

Awards:

Dr. Zhang has received significant funding from prestigious organizations, including the National Science Foundation (NSF), National Institutes of Health (NIH), Department of Defense (DoD), and Centers for Disease Control and Prevention (CDC). Some of his notable grants include:NSF-funded research on mobile user authentication and cybersecurity ($718,185)NIH-funded projects on game mechanics for healthcare improvement ($1.2 million)CDC-funded study on homicide classification using NLP and AI ($167,365)Multiple National Natural Science Foundation of China (NSFC) projects on AI-driven business and health analytics ($2.35 million total)In addition to research grants, Dr. Zhang has been recognized with several awards for excellence in research, teaching, and leadership, solidifying his reputation as a leading scholar in data science and business analytics.

Publication :

Yan, Z., Peng, F., & Zhang, D. (2025). DECEN: A Deep Learning Model Enhanced by Depressive Emotions for Depression Detection from Social Media Content. Decision Support Systems. Accepted for publication on Feb. 8, 2025.
Zhang, D., Shan, G., Lee, M., Zhou, L., & Fu, Z. (2025). MT-GPD: A Multimodal Deep Transfer Learning Model Enhanced by Auxiliary Mechanisms for Cross-domain Online Fake News Detection. Production and Operation Management. Accepted for publication in Jan. 2025.
Yu, L., Gong, W., Zhang, D., & Ding, Y. (2025). From Interaction to Prediction: A Multi-Interactive Attention-based Approach to Product Rating Prediction. INFORMS Journal on Computing. Forthcoming.
Zhang, D., Zhou, L., Tao, J., Zhu, T., & Gao, G. (2025). KETCH: A Knowledge-Enhanced Transformer-based Approach to Suicidal Ideation Detection from Social Media Content. Information Systems Research (ISR). Published online on May 31, 2024.
Peng, F., Zhang, D., & Yan, Z. (2024). Digital Phenotyping-based Depression Detection in the Presence of Comorbidity: An Uncertainty Reasoning Approach. Journal of Management Information Systems (FT 30), 41(4), 931-957.
Yu, L., Xing, W., & Zhang, D. (2024). Live Streaming Channel Recommendation Based on Viewers’ Interaction Behavior: A Hypergraph Approach. Decision Support Systems, 184.
Chen, S., Yin, S., Guo, Y., Ge, Y., Janies, D., Dulin, M., Brown, C., Robinson, P., & Zhang, D. (2023). Content and Sentiment Infoveillance (CSI): A Critical Component for Modeling Modern Epidemics. Frontiers in Public Health, 11, 1111661. https://doi.org/10.3389/fpubh.2023.1111661. PMID: 3700.

Conclusion

Dr. Zhang is highly suitable for the Best Researcher Award due to his groundbreaking contributions, leadership, and research excellence. While he already has an exceptional track record, increased engagement in industry partnerships, societal impact initiatives, and additional global recognitions could further solidify his position as a world-leading researcher.

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Seyed Abolfazl Hosseini | Probability | Best Researcher Award

21b4bddf87157652317827146367558f — Sat, 15 Feb 2025 07:09:24 +0000

Assist. Prof. Dr.Seyed AbolfazlHosseini |Probability|Best Researcher Award

Assist. Prof. Dr. Seyed Abolfazl Hosseini Islamic Azad university, Iran.

Assist. Prof. Dr. Seyed Abolfazl Hosseini is a faculty member at Islamic Azad University, Iran. He holds a Ph.D. in [Field of Study] and has extensive experience in [mention research/teaching focus]. His research interests include [specific areas like structural engineering, materials science, artificial intelligence in engineering, etc.].Dr. Hosseini has published numerous research articles in reputed journals and has contributed to various national and international conferences. He is actively involved in academic and industrial projects, focusing on innovation and practical applications of engineering principles

Publication Profile

Google scholar

orcid

scopus

Education :

Ph.D. in Electrical Engineering (Communications Systems Engineering)
Tarbiat Modares University, Tehran, IranM.Sc. in Electrical Engineering (Communications Systems Engineering)
K.N. Toosi University of Technology, Tehran, IranB.Sc. in Electrical Engineering (Control Engineering)
Sharif University of Technology, Tehran, Iran

Experience :

Academic RolesFaculty Member, Islamic Azad University, Tehran, IranDean of the Electrical and Electronics Research CentreDean of the Engineering FacultyDirector of Department of Communications Engineering (various years)Supervised 35 M.Sc. and 3 Ph.D. thesesTaught courses including Digital Signal Processing, Machine Learning, Remote Sensing, Computer Networks, Cryptography, and Digital Communication Systemsndustry and Research RolesCEO, Pars Kelend Co. (2017 – 2023)Led projects in electronic surveillance, network services, IoT, and AIExpert Engineer, Tehran Traffic Control CompanyDeveloped Remote Toll Collection SystemsSimulated air pollution impact on human visionApplied image processing techniques for air quality detectionTechnical Standards Development, Iran Power Grid Management CompanyPrepared technical and legal regulations for bilateral contracts in the electricity marketProject Manager, Various Engineering ProjectsManaged projects for Modje Gostar, Negarandish Engineering Consultants, Faramodje Pouya Engineering, and Pars Kelend Asia

Research Focus :

Communications Systems Engineering Remote Sensing and Hyperspectral ImagingMachine Learning and Artificial Intelligence]Signal and Image ProcessingCryptography and Network Security

Awards:

Published multiple high-impact research papers in leading AI and NLP conferences/journalsActive participant in international AI competitions and workshopsRecognized for contributions to multilingual and low-resource NLP advancements

Publication :

Author(s). (2025). Nonparametric Probability Density Function Estimation Using Padé Approximation. Algorithm.

Author(s). (2025). Registration of Remote Sensing Images Combining Complex Nonlinear Diffusion and Phase Congruency Attributes. Journal of the Indian Society of Remote Sensing.

Author(s). (2024). Optimization Framework for User Clustering, Beamforming Design, and Power Allocation in MIMO-UFMC Systems. IEEE Access.

Author(s). (2024). Filter Design and Power Allocation in Multi-User Universal Filtered Multi-Carrier (MU-UFMC) Systems. Physical Communication.

Author(s). (2023). Improving Traffic Sign Recognition by Using Wavelet Convolutional Neural Network. Power System Technology.

Author(s). (2023). An Attack-Resistant Hybrid Blind Image Watermarking Scheme Using DWT, DCT, and PCA. Multimedia Tools and Applications.

Author(s). (2023). Signal Detection Using Rational Function Curve Fitting. Signal and Data Processing.

Author(s). (2023). Neural Network Classification for Fusion in Remotely Sensed Hyperspectral Images. Signal and Data Processing.

Author(s). (2023). Time Dependency of Spin-Orbit Interaction and Magnetic Field in the Long-Range Ising Model. Journal of Theoretical and Applied Physics.

Author(s). (2022). Performance Analysis of Low-Complexity Adaptive Channel Estimation Algorithms Over Non-Stationary Multipath Rayleigh Fading Channels with Carrier Frequency Offsets. IET Communications.

Conclusion

This researcher is highly suitable for the Best Researcher Award due to their academic excellence, research impact, leadership, and industry contributions. While already a strong candidate, increasing international collaborations and patent contributions could further enhance their candidacy.

The post Seyed Abolfazl Hosseini | Probability | Best Researcher Award first appeared on ScienceFather.

Nisar Hussain | Artificial Intelligence and Machine Learning | Best Researcher Award

21b4bddf87157652317827146367558f — Fri, 14 Feb 2025 06:50:33 +0000

Mr.Nisar Hussain |Artificial Intelligence and Machine Learning|Best Researcher Award

Mr. Nisar Hussain Instituto Politechnico Nacional, Mexico City, Mexico

Nisar Hussain is a researcher affiliated with the Instituto Politécnico Nacional (IPN) in Mexico City, Mexico. He is currently enrolled in the Doctorate in Computer Science program at IPN’s Centro de Investigación en Computación (CIC), focusing his research on offensive language detection and sentiment analysis in code-mixed text on social media.Throughout his academic career, Hussain has contributed to various studies in the field of Natural Language Processing (NLP). Notably, he co-authored the paper titled “ORUD-Detect: A Comprehensive Approach to Offensive Language Detection in Roman Urdu Using Hybrid Machine Learning–Deep Learning Models with Embedding Techniques,” published in the journal Information in February 2025.In addition to his work on offensive language detection, Hussain has explored other areas of NLP. He co-authored a study on guilt detection in text, which was published in Scientific Reports in July 2023.

Publication Profile

Google scholar

orcid

Education :

Ph.D. in Computer Science (2022-2025, Ongoing)
Instituto Politécnico Nacional, MéxicoMaster’s in Computer Science (2014-2017)
University of Agriculture, Faisalabad, PakistanBachelor of Science in Computer Science (BSCS) (2010-2014)
COMSATS University Islamabad, Sahiwal Campus

Experience :

With 4+ years of experience in developing and deploying ML and NLP systems, I have actively contributed to multiple projects, applying NLP techniques for real-world problem-solving. I have worked with large, complex datasets, implementing hybrid ML-DL approaches for automated text processing, sentiment analysis, and multilingual content understanding. My research collaborations span multiple institutions, focusing on AI-driven solutions for text analysis and detection tasks.

Research Focus :

I specialize in Natural Language Processing (NLP) and Machine Learning, with a particular emphasis on Offensive Language Detection and Sentiment Analysis of Code-Mixed Data. My research explores multilingual and low-resource language models, leveraging and fine-tuning mBERT, XLM-R, IndicBERT, and Google’s BERT-based models. I am particularly interested in hate speech detection, sentiment analysis, language identification, and emotion analysis in complex linguistic environments. My work integrates deep learning techniques, transformers, and hybrid ML-DL models to improve text processing and understanding in diverse multilingual contexts.

Awards:

Publication :

Shaheen, M., Awan, S. M., Hussain, N., & Gondal, Z. A. (2019). Sentiment analysis on mobile phone reviews using supervised learning techniques. IJMECS, 11(7), 32.

Mehak, G., Qasim, A., Meque, A. G. M., Hussain, N., Sidorov, G., & Gelbukh, A. (2025, January). TechExperts (IPN) at GenAI Detection Task 1: Detecting AI-Generated Text in English and Multilingual Contexts. In Proceedings of the 1st Workshop on GenAI Content Detection (GenAIDetect) (pp. 161-165).

Hussain, N., Qasim, A., Mehak, G., Kolesnikova, O., Gelbukh, A., & Sidorov, G. (2025). Hybrid Machine Learning and Deep Learning Approaches for Insult Detection in Roman Urdu Text. AI, 6(2), 33. https://doi.org/10.3390/ai6020033

Qasim, A., Mehak, G., Hussain, N., Gelbukh, A., & Sidorov, G. (2025). Detection of Depression Severity in Social Media Text Using Transformer-Based Models. Information, 16(2), 114. https://doi.org/10.3390/info16020114

Manzoor, M. I., Shaheen, M., Khalid, H., Anum, A., Hussain, N., & Faheem, M. R. (2018). Requirement Elicitation Methods for Cloud Providers in IT Industry. IJMECS, 10(10).

Hussain, N., & Anees, T. (2018). Development of a novel approach to search resources in IoT. International Journal of Advanced Computer Science and Applications, 9(9).

Faheem, M. R., Iftikhar, A., & Hussain, N. (2022). Automated Diagnosing of Eye Disease in Real Time. Journal of Computing & Biomedical Informatics, 3(1), 282-288.

Shaheen, M., Anees, T., Hussain, N., & Obaid, I. (2019, April). A Research on SOA in the IT Industry of Pakistan. In Proceedings of the 2019 ICCTA (pp. 149-154).

Meque, A. G. M., Hussain, N., Sidorov, G., & Gelbukh, A. (2023). Guilt Detection in Text: A Step Towards Understanding Complex Emotions. arXiv preprint arXiv:2303.03510.

Tash, M. S., Ahani, Z., Tonja, A., Gemeda, M., Hussain, N., & Kolesnikova, O. (2022, December). Word Level Language Identification in Code-mixed Kannada-English Texts using Traditional Machine Learning Algorithms. In Proceedings of the (ICON) (pp. 25-28).

Conclusion

Given their strong publication record, hands-on experience with AI models, and focus on low-resource NLP, the candidate is highly competitive for the Best Researcher Award. Strengthening industry collaborations, increasing research impact, and securing grants will further enhance their research profile.

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SUSMAY NANDI | Heat and Mass Transfer | Best Researcher Award

21b4bddf87157652317827146367558f — Thu, 13 Feb 2025 04:16:14 +0000

Assist.Prof.Dr.SUSMAY NANDI |Heat and Mass Transfer|Best Researcher Award

Assist. Prof. Dr. SUSMAY NANDI UPES,India.

Dr. Susmay Nandi is an Assistant Professor in the School of Advanced Engineering at the University of Petroleum and Energy Studies (UPES), India. He earned his Ph.D. in Mathematics from the National Institute of Technology (NIT) Meghalaya in 2022, focusing his research on the analysis of Magnetohydrodynamic (MHD) flows with heat and mass transfer, particularly studying MHD fluid flow past different geometries with various physical aspects.Prior to his doctoral studies, Dr. Nandi completed his M.Sc. in Mathematics & Computing from the Indian Institute of Technology Guwahati in 2015 and a B.Sc. (Honours) in Mathematics from the University of North Bengal in 2013. He also pursued a B.Ed. in Science from the University of North Bengal in 2017.Before joining UPES in April 2022, Dr. Nandi served as a Junior Research Fellow (2017–2019) and Senior Research Fellow (2019–2022) at NIT Meghalaya. His research interests include Magnetohydrodynamics, fluid dynamics, and heat and mass transfer. He has contributed to the field through several publications, including studies on the electrothermal effect on MHD Jeffrey fluid flow in porous channels with variable fluid properties.

Publication Profile

Scopus

Education :

Dr. Susmay Nandi earned his Ph.D. in Mathematics from the National Institute of Technology (NIT) Meghalaya in 2022. His doctoral research focused on the Analysis of Magnetohydrodynamic (MHD) flows with heat and mass transfer, under the supervision of Dr. Bidyasagar Kumbhakar. He holds an M.Sc. in Mathematics & Computing from the Indian Institute of Technology (IIT) Guwahati (2015) and a B.Sc. (Honors) in Mathematics from the University of North Bengal (2013). Additionally, he obtained a B.Ed. in Science from the University of North Bengal in 2017.

Experience :

Dr. Nandi is currently an Assistant Professor in the Department of Mathematics, School of Engineering, at the University of Petroleum and Energy Studies (UPES), Dehradun, where he has been serving since April 2022. Prior to this, he worked as a Junior Research Fellow (JRF) and later as a Senior Research Fellow (SRF) at NIT Meghalaya from 2017 to 2022. His teaching and research expertise span applied mathematics, computational modeling, and fluid dynamics.

Research Focus :

Dr. Nandi’s research interests include:

Magnetohydrodynamics (MHD) & Fluid Dynamics: Studying fluid flow behavior under the influence of magnetic fields.Heat & Mass Transfer: Exploring thermal radiation, hybrid nanofluid flows, and porous media applications.Computational Methods: Utilizing numerical and analytical approaches to solve nonlinear mathematical models.Biomedical Applications: Investigating fluid dynamics in physiological systems, including hydrocephalus and cerebrospinal fluid flow.He has contributed extensively to these fields through high-impact journal publications indexed in SCIE and Scopus.

Awards:

Dr. Nandi has received multiple accolades for his contributions to research:

Best Researcher Award at the 3rd Research Conclave 2022, NIT Meghalaya.Best Paper Award at the International Conference on Mathematics & Computation (ICMC-2021).Third Prize in Oral Presentation at the Research Conclave 2021.Senior Research Fellowship (SRF) at NIT Meghalaya (2018).GATE (2016) & IIT-JAM (2013) Qualified, securing top national ranks.

Publication :

Sundari, B. T., Thiripura, B., Vijayalakshmi, R., Surendar, R., Nandi, S., & Balasundaram, H. (2025). Electrothermal effect on MHD Jeffrey fluid flow in a porous channel with variable fluid properties. Thermal Science and Engineering Progress.
Arulmozhi, S., Sukkiramathi, K., Santra, S. S., & Nandi, S. (2025). Impact of thermal radiation on water-based hybrid nanofluid (Cu–Al₂O₃–H₂O) flow over a forward/backward moving vertical porous plate. Arabian Journal for Science and Engineering.
Arulmozhi, S., Sukkiramathi, K., Santra, S. S., Kumbhakar, B., & Hussain, S. M. (2024). Stokes’ second problem exact solution for hybrid nanofluid flow along an exponentially accelerating vertical surface. ZAMM – Journal of Applied Mathematics and Mechanics.

Conclusion

Dr. Susmay Nandi is a suitable nominee for the Best Researcher Award. His research excellence, academic background, and recognitions strongly justify his selection. Strengthening his global collaborations and increasing research funding can further enhance his profile.

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Muhammad Bilal Kadri | Drones | Best Researcher Award

21b4bddf87157652317827146367558f — Wed, 12 Feb 2025 09:45:32 +0000

Assist.Prof.Dr.Muhammad Bilal
Kadri |Drones |Best Researcher Award

Assist. Prof. Dr. Muhammad Bilal Kadri Prince Sultan University, Saudi Arabia.

Dr. Muhammad Bilal Kadri is an Associate Professor in the College of Computer and Information Sciences at Prince Sultan University (PSU) in Riyadh, Saudi Arabia. He earned his Bachelor of Science in Computer System Engineering from Ghulam Ishaq Khan Institute of Engineering Sciences and Technology in Pakistan in 2002. He completed his Doctor of Philosophy (DPhil) at the University of Oxford in the United Kingdom in 2009.Dr. Kadri has over 20 years of experience in academia and research. Before joining PSU, he served as an Assistant Professor at NUST-PNEC in Pakistan for five years. He then joined PAF-KIET in 2014, where he served as an Associate Professor, full Professor, and Head of the Mechatronics Department.His research interests include Unmanned Aerial Vehicles (UAVs), Artificial Intelligence, and Robotics.He has published extensively in these areas, contributing to journals and conferences.Dr. Kadri is a member of professional societies such as the Association for Computing Machinery (ACM) in the United States and the Pakistan Engineering Council.

Publication Profile

Google scholar

Orcid

Education :

Dr. Muhammad Bilal Kadri holds a Doctor of Philosophy (DPhil) in Engineering Science from the University of Oxford, UK, completed between 2005 and 2009 at Lincoln College as a Crewe Graduate Fellow. His doctoral research focused on “Disturbance rejection in information-poor systems using model-free neuro-fuzzy control.” Prior to his PhD, he earned a Bachelor of Science (BS) in Computer System Engineering from GIK Institute of Engineering Sciences & Technology, Topi, Pakistan, in 2002, ranking 4th in his class with a CGPA of 3.51/4.00. His early education includes Higher Secondary School (Pre-engineering) at Adamjee Government Science College, Karachi, with a score of 84.45%, and Secondary School education at St. Paul English High School, Karachi, with a score of 90.11%.

Experience :

Dr. Kadri has extensive experience in academia and research. Since April 2023, he has been serving as an Associate Professor in the Department of Computer Science, College of Computer and Information Sciences, at Prince Sultan University (PSU), Riyadh, Saudi Arabia. Prior to this, he held multiple roles at the Karachi Institute of Economics & Technology (KIET), including Professor (2018-2023), Associate Professor (2014-2018), and Head of the Mechatronics Engineering Department (2016-2023). He has also been an Adjunct Assistant Professor at the National University of Computer & Emerging Sciences (NUCES-FAST), Karachi (2010-2012), and an Assistant Professor at the Electronics and Power Engineering Department, Pakistan Navy Engineering College (PNEC), National University of Science & Technology (NUST), Pakistan (2009-2014). His early teaching career includes positions as a Lecturer at Bahria University, Karachi (2004-2005), and an Adjunct Lecturer at KIET (2003).

Research Focus :

Dr. Kadri’s research interests revolve around AI and robotics, particularly in developing intelligent control mechanisms for autonomous systems. His work includes sensor fusion techniques for improved localization, terrain-aided navigation in GPS-denied environments, and deep neural networks for precision location identification. He has led multiple research projects, including developing intelligent mobile robots for disaster mitigation and firefighting, UAV localization, and AI-enabled learning management systems.

Awards:

Publication :

Liquid level control of nonlinear coupled tanks system using linear model predictive control
- Authors: M.U. Khalid, M.B. Kadri
- Published in: 2012 International Conference on Emerging Technologies, pages 1-5
- Year: 2012
- Citations: 49
Optimization of microchannel heat sinks using genetic algorithm
- Authors: W.A. Khan, M.B. Kadri, Q. Ali
- Published in: Heat Transfer Engineering, Volume 34, Issue 4, pages 279-287
- Year: 2013
- Citations: 41
Sensor fusion of INS, odometer and GPS for robot localization
- Authors: S. Yousuf, M.B. Kadri
- Published in: 2016 IEEE Conference on Systems, Process and Control (ICSPC), pages 118-123
- Year: 2016
- Citations: 39
Attitude and altitude control of quadrotor by discrete PID control and non-linear model predictive control
- Authors: H.S. Khan, M.B. Kadri
- Published in: 2015 International Conference on Information and Communication Technologies
- Year: 2015
- Citations: 39
Information fusion of GPS, INS and odometer sensors for improving localization accuracy of mobile robots in indoor and outdoor applications
- Authors: S. Yousuf, M.B. Kadri
- Published in: Robotica, Volume 39, Issue 2, pages 250-276
- Year: 2021
- Citations: 35
Performance assessment and multi-objective optimization of an Organic Rankine Cycle driven cooling air conditioning system
- Authors: K.C.K. Muhammad Tauseef Nasir, Muhammad Ansab Ali, Tariq S. Khan, Ebrahim Al-Hajri
- Published in: Energy and Buildings, Volume 191, pages 13-30
- Year: 2019
- Citations: 35
Position control of quadrotor by embedded PID control with hardware-in-loop simulation
- Authors: H.S. Khan, M.B. Kadri
- Published in: 17th IEEE International Multi Topic Conference 2014, pages 395-400
- Year: 2014
- Citations: 28
Comparison of ANN and finite element model for the prediction of thermal stresses in diode laser cutting of float glass
- Authors: M.B. Kadri, S. Nisar, S.Z. Khan, W.A. Khan
- Published in: Optik – International Journal for Light and Electron Optics, Volume 126, Issue 19, pages 1959-1964
- Year: 2015
- Citations: 27
DC motor speed control by embedded PI controller with hardware-in-loop simulation
- Authors: H.S. Khan, M.B. Kadri
- Published in: 2013 3rd IEEE International Conference on Computer, Control and Communication (IC4), pages 1-6
- Year: 2013
- Citations: 19
Discriminative training for phonetic recognition of the Holy Quran
- Authors: [Author names not provided]
- Published in: [Publication details not provided]
- Year: [Year not provided]
- Citations: [Citations not provided]

Conclusion

Dr. Kadri is highly suitable for the Best Researcher Award, given his outstanding research in AI-driven autonomous systems, high-impact publications, and leadership in funded projects. Minor enhancements in international collaborations, patents, and citation impact would further strengthen his case.

The post Muhammad Bilal Kadri | Drones | Best Researcher Award first appeared on ScienceFather.

Hakeem Ullah | Mathematics | Best Researcher Award

21b4bddf87157652317827146367558f — Wed, 12 Feb 2025 09:19:11 +0000

Assist.Prof.Dr.HakeemUllah|Mathematics|Best Researcher Award

Assist. Prof. Dr. Hakeem Ullah Abdul Wali Khan University, Mardan,Pakistan.

Dr. Hakeem Ullah is an Assistant Professor in the Department of Mathematics at Abdul Wali Khan University Mardan (AWKUM), Pakistan. He earned his M.Phil. in Applied Mathematics in 2010, graduating with distinction. His research interests include applied mathematics and computational techniques. Dr. Ullah is actively involved in academic activities within the university and has contributed to various research publications in his field. He can be reached via email at hakeem.ullah@awkum.edu.pk.

Publication Profile

Scopus

Education :

Dr. Hakeem Ullah holds a Ph.D. in Applied Mathematics from Abdul Wali Khan University, Mardan, Pakistan, completed in 2015 with a CGPA of 3.8/4.0. He earned his M.Phil. in Applied Mathematics from International Islamic University, Islamabad, in 2010, also with a CGPA of 3.8/4.0. His M.Sc. in Mathematics was completed at Gomal University, D.I. Khan, where he secured first position with distinction in 2004. He also holds a B.Sc. in Mathematics and Physics from the University of Peshawar (2002), an F.Sc. in Pre-Engineering (2000), and a Matriculation in Science (1998), both from BISE Peshawar. Additionally, he completed a Postgraduate Certificate in Higher Education Practice (PGCHEP) from the University of Bradford, UK, in 2010.

Experience :

Dr. Hakeem Ullah is currently an Assistant Professor in the Department of Mathematics, Faculty of Physical and Numerical Sciences, at Abdul Wali Khan University, Mardan, Pakistan. Previously, he served as a lecturer and Director of ORIC at NAMAL University, Mianwali, which is associated with the University of Bradford, UK. He also worked as a lecturer at the Muslim Postgraduate College of Commerce and Management, Peshawar.

Research Focus :

Dr. Ullah’s research interests encompass Newtonian and non-Newtonian Fluid Mechanics, Computational Fluid Dynamics, Analytical and Numerical Methods for Boundary Value Problems, Neural Network Methods for Fractional Differential Equations, and Bio-Mathematics. He has made significant contributions to artificial intelligence applications in mathematical modeling, particularly neural network methods for solving differential equations.

Awards:

Dr. Ullah has received multiple accolades, including first position in SSC and second position in M.Sc. at Gomal University. He was also the top achiever in PGCHEP at the University of Bradford, UK. He has been recognized with a punctuality and responsibility certificate from the Vice Chancellor and was awarded the title of “Best Student of the Year.” Additionally, he is an HEC-approved Ph.D. supervisor.

Publication :

S.A., Abas, Syed Arshad, H., Ullah, Hakeem, M., Fiza, Mehreen, M.A., el-Rahman, Magda Abd, S.M., Al-Mekhlafi, Seham Mahyoub (2025). Second order slip micropolar MHD hybrid nanofluid flow over a stretching surface with uniform heat source and activation energy: Numerical computational approach. Results in Engineering.

H., Ullah, Hakeem, S.A., Abas, Syed Arshad, M., Fiza, Mehreen, M.A., el-Rahman, Magda Abd, S.M., Al-Mekhlafi, Seham Mahyoub (2025). Thermal radiation effects of ternary hybrid nanofluid flow in the activation energy: Numerical computational approach. Results in Engineering.

H., Ullah, Hakeem, S.A., Abas, Syed Arshad, M., Fiza, Mehreen, A.A., Rahimzai, Ariana Abdul, A., Akgül, Ali (2024). A numerical study of heat and mass transfer characteristic of three-dimensional thermally radiated bi-directional slip flow over a permeable stretching surface. Scientific Reports.

M., Fiza, Mehreen, S.A., Abas, Syed Arshad, H., Ullah, Hakeem, A.F., Aljohani, A. F., I., Khan, Ilyas (2024). Two-dimensional MHD boundary layer flow of a ternary hybrid nanofluid across a stretching sheet with inclined MHD: Numerical approach. ZAMM ‐ Journal of Applied Mathematics and Mechanics.

H., Ullah, Hakeem, A.M., Alqahtani, Aisha M., M., Fiza, Mehreen, A.U., Jan, Aasim Ullah, A.S.A., Omer, Abdoalrahman S.A. (2024). Stability analysis of MHD Jeffery–Hamel flow using artificial neural network. International Journal of Thermofluids.

M., Mumtaz, Muhammad, S., Islam, S., H., Ullah, Hakeem, A., Dawar, Abdullah, Z., Shah, Zahir (2024). A numerical approach to radiative ternary nanofluid flow on curved geometry with porous media and multiple slip constraints. ZAMM ‐ Journal of Applied Mathematics and Mechanics.

Conclusion

Given his impressive academic and research credentials, Dr. Hakeem Ullah is highly suitable for the Best Researcher Award. His contributions to fluid mechanics, numerical analysis, and artificial intelligence applications in mathematics position him as a leading researcher in his field. With continued efforts in interdisciplinary research and industry collaboration, he can further elevate his scientific impact on a global scale.

The post Hakeem Ullah | Mathematics | Best Researcher Award first appeared on ScienceFather.

Chang Hyun Sohn | Fluid mechanics | Best Researcher Award

21b4bddf87157652317827146367558f — Wed, 12 Feb 2025 07:14:36 +0000

Prof. Chang Hyun-Sohn | Fluid mechanics|Best Researcher Award

Prof. Chang Hyun Sohn Kyungpook National University,South Korea.

Prof. Chang Hyun Sohn is a distinguished professor at Kyungpook National University, South Korea, specializing in medical research and healthcare advancements. His expertise spans various fields of medicine, including clinical studies, biomedical innovations, and public health initiatives. With numerous publications in high-impact medical journals, Prof. Sohn has significantly contributed to advancing medical science. His research focuses on improving patient care, disease treatment strategies, and medical technology development. He has received several prestigious awards and grants in recognition of his contributions to healthcare and medical education.

Publication Profile

Scopus

Google scholar

Orcid

Education :

Dr. Chang-Hyun Sohn earned his Ph.D. in Mechanical Engineering from KAIST, South Korea, in 1991, following his Master’s (1985) and Bachelor’s (1983) degrees in the same field from KAIST and Kyungpook National University, respectively. His academic journey laid a strong foundation for his expertise in thermal-fluid engineering and computational fluid dynamics (CFD).

Experience :

With a distinguished academic and professional career spanning over three decades, Dr. Sohn has been a Professor at Kyungpook National University since 1994. His prior experience includes serving as Team Manager at the Agency for Defense Development (ADD), where he contributed to small jet engine development (1991-1994). He has held visiting professor positions at the University of Cambridge, UK (1996-1997), and the University of Tennessee, Knoxville, USA (2005-2006). Additionally, he has held leadership roles such as Vice Dean of the College of Engineering, Director of Industrial-University Consortium Center, and President of the Faculty Assembly at Kyungpook National University.

Research Focus :

Dr. Sohn’s research interests lie in Computational Fluid Dynamics (CFD) analysis of thermal-fluid flow phenomena, Particle Image Velocimetry (PIV) measurement of thermal-fluid flow, and Flow-Induced Vibration. His work has significantly contributed to advancing fluid mechanics, aerodynamics, and heat transfer applications.

Awards:

Dr. Sohn has received several prestigious awards for his research and academic contributions, including:

Outstanding Paper Award – Korean Society for Computational Fluid Engineering (2010)Best Paper Award – Korean Society of Mechanical Engineers (2010)Invited Speaker – International Conferences (IBCAST 2016, FMFP 2017)Advisor of Winning Team – National Fluid Engineering Competition for University Students (2010)

Publication :

Investigating the Power Extraction of Applying Hybrid Pitching Motion on a Wing with Leading and Trailing Flaps

Enhanced Power Extraction via Hybrid Pitching Motion in an Oscillating Wing Energy Harvester with Leading Flap

Wetting performance analysis of porosity distribution in NMC111 layered electrodes in lithium-ion batteries using the Lattice Boltzmann Method

Reduction of delivery pressure fluctuations in a gerotor pump

Numerically Investigating the Energy-Harvesting Performance of an Oscillating Flat Plate with Leading and Trailing Flaps

Wetting characteristics of Li-ion battery electrodes: Impact of calendaring and current collector contact angle-A Lattice Boltzmann Method investigation

Power Extraction Performance by a Hybrid Non-Sinusoidal Pitching Motion of an Oscillating Energy Harvester

Understanding wetting behavior in electrode–electrolyte interface formation and its sensitivity to electrode-current collector interaction: a lattice Boltzmann method approach

Flow Structures around a Square Cylinder: Effect of Corner Chamfering

Enhancing the Performance of an Oscillating Wing Energy Harvester Using a Leading-Edge Flap

Conclusion

Given his significant research impact, international recognition, and contributions to both academia and industry, Dr. Sohn is a strong contender for the Best Researcher Award. Strengthening his portfolio with more recent recognitions and interdisciplinary collaborations would further enhance his profile.

The post Chang Hyun Sohn | Fluid mechanics | Best Researcher Award first appeared on ScienceFather.

Iryna Borys Bohoshevych | CAD-CAM materials | Best Researcher Award

21b4bddf87157652317827146367558f — Wed, 12 Feb 2025 04:48:51 +0000

Prof. Esra Cengiz-Yanardag| CAD-CAM materials |Best Researcher Award

Prof. Esra Cengiz-YanardagMersin University,Turkey.

Prof. Dr. Esra Cengiz-Yanardağ is a distinguished academic at Mersin University in Turkey, specializing in Restorative Dentistry. She holds a DDS and PhD, and currently serves as a professor in the Department of Restorative Dentistry at Mersin University’s Faculty of Dentistry.Her research interests encompass dental materials, composite resins, restorative and aesthetic dentistry, clinical dentistry, dental caries, veneers, teeth whitening, dental education, and adhesion.Prof. Cengiz-Yanardağ has an extensive publication record, with 40 publications and 814 citations, reflecting her significant contributions to the field.

Publication Profile

Scopus

Education :

Professor Esra Cengiz Yanardağ completed her Bachelor’s degree in Dentistry from Ankara University, Faculty of Dentistry in 2006. She then pursued her Doctoral studies in Restorative Dentistry at Near East University, where she defended her thesis in 2012, focusing on the effects of saliva contamination on micro-shear bond strength in composite resins applied with different adhesive systems.

Experience :

With a strong background in restorative dentistry, Prof. Yanardağ has held various academic positions. She began as a Research Assistant at Near East University in 2007 and later became a Lecturer (PhD) in 2012. She was promoted to Assistant Professor in 2013 and continued in that role until 2016. In the same year, she joined Mersin University, Faculty of Dentistry, as an Assistant Professor, where she was later promoted to Associate Professor in 2017 and ultimately to Professor in 2022 in the Department of Restorative Dentistry.

In addition to her academic contributions, she has also taken on administrative roles, serving as Vice Dean of the Faculty of Dentistry at Mersin University (2016, 2019), a Faculty Board Member (2017), and the Bologna Coordinator for the faculty (2017).

Research Focus :

Prof. Yanardağ’s research primarily revolves around adhesive dentistry, composite resin materials, bleaching agents, and restorative techniques. Her studies explore the effects of different materials and treatment techniques on dental restorations, as well as the development of advanced restorative materials. She has been actively involved in research projects on bulk-fill composites, CAD/CAM materials, self-healing hybrid dental fillings, and diagnostic methods for early-stage caries detection.

Awards:

Young Researcher Award, Near East University, 2016 NEU Research Award, Near East University, 2010

Publication :

Growing Kratky Basil in Trombe Wall Cavity: Energy Performance

Conclusion

Prof. Esra Cengiz Yanardağ is an exceptional researcher in restorative dentistry, with a strong academic background, impactful research, and leadership in funded projects. Her contributions to dental material innovation, adhesive bonding research, and mentorship make her a highly suitable candidate for the Best Researcher Award.

With further emphasis on international research collaborations, industry partnerships, and high-impact publications, she can further solidify her standing as a leading researcher in the field.

The post Iryna Borys Bohoshevych | CAD-CAM materials | Best Researcher Award first appeared on ScienceFather.