Sandeep Jain | Engineering and Technology | Best Researcher Award

Sandeep Jain | Engineering and Technology | Best Researcher Award

Dr Sandeep Jain, Sungkyunkwan University, Republic of Korea, South Korea

Dr. Sandeep Jain is a metallurgical engineer and researcher with expertise in machine learning applications in alloy design, lightweight materials, and high-entropy alloys. He holds a Ph.D. (2023) and M.Tech. (2017) from IIT Indore and a B.E. in Mechanical Engineering (2013). Currently a Postdoctoral Researcher at Sungkyunkwan University, South Korea, Dr. Jain focuses on designing multicomponent alloys and optimizing manufacturing processes. He has published extensively, including works on machine learning-driven phase prediction and flow stress modeling. Dr. Jain is a guest editor, reviewer for leading journals, and recipient of prestigious awards like the Global Best Achievement Award 2024. ๐Ÿงช๐Ÿค–๐ŸŒ

Publication Profile

Orcid

Education

Dr. Sandeep Jain is a dedicated scholar with a robust academic background in engineering. ๐ŸŽ“ He earned his Ph.D. (2017-2023) and M.Tech (2015-2017) in Metallurgical Engineering and Materials Science from the prestigious Indian Institute of Technology Indore, achieving impressive CGPAs of 8.67 and 8.75, respectively. ๐Ÿ“˜โœจ His journey in engineering began with a B.E. in Mechanical Engineering from MBM Engineering College, Jodhpur (2009-2013), where he secured a commendable 68% score. ๐Ÿ”ง๐Ÿ“š Dr. Jainโ€™s academic excellence reflects his passion for materials science and mechanical engineering, laying a solid foundation for impactful contributions to his field. ๐Ÿš€๐Ÿ”ฌ

Research Experience

Dr. Sandeep Jain, currently a Postdoctoral Researcher at Sungkyunkwan University, South Korea ๐Ÿ‡ฐ๐Ÿ‡ท, specializes in designing lightweight multicomponent alloys and optimizing injection molding processes using machine learning ๐Ÿค–. As a Research Associate at IIT Delhi ๐Ÿ‡ฎ๐Ÿ‡ณ, he analyzed the mechanical and creep behavior of Ni-based superalloys and pioneered sustainable rose gold plating methods ๐ŸŒŸ. His tenure at IIT Indore included designing lightweight Ni-based alloys and conducting advanced phase equilibria studies ๐Ÿ”ฌ. Dr. Jainโ€™s expertise extends to simulation tools like ANSYS Fluent, XRD, and EBSD, contributing to innovative and sustainable material development ๐ŸŒ.

Teaching Experience

Dr. Sandeep Jain has an extensive teaching background in materials science and engineering. As a Teaching Assistant at the Indian Institute of Technology Indore (Dec 2017โ€“Nov 2022 and July 2015โ€“June 2017), he contributed to courses like Solidification and Phase Field Modelling, Computational Methods for Materials, and Physical Metallurgy. His expertise also spans practical modules, including Mechanical Workshop, Casting and Welding Lab. Earlier, he served as a Guest Faculty at Govt. Engineering College, Ajmer (Aug 2013โ€“June 2014), teaching Material Science, Engineering Mechanics, Strength of Materials, and more. Dr. Jainโ€™s dedication to education blends technical knowledge with hands-on experience. ๐ŸŽ“๐Ÿ› ๏ธ๐Ÿ“š

Awards / Fellowships

Dr. Sandeep Jain has earned prestigious accolades for his outstanding achievements in academia and research. In 2024, he was honored with the Global Best Achievement Awards ๐ŸŽ–๏ธ๐ŸŒŸ, recognizing his contributions to his field. His academic journey has been supported by prestigious fellowships, including the Ph.D. Fellowship ๐Ÿง‘โ€๐ŸŽ“๐Ÿ“š and the M.Tech. Fellowship ๐ŸŽ“๐Ÿ”ฌ, both awarded by the Ministry of Human Resource Development (MHRD), Government of India. These honors highlight his dedication, innovation, and excellence in advancing knowledge and contributing to societal progress. Dr. Jain’s achievements continue to inspire and set benchmarks for aspiring scholars worldwide. ๐Ÿš€๐Ÿ“–

Research Focus

Dr. Sandeep Jain’s research focuses on the development and application of machine learning techniques to predict mechanical properties in lightweight alloys and high entropy alloys. His studies include hardness prediction, flow stress, phase prediction, and the influence of processing methods like friction stir processing. These investigations aim to enhance the performance of advanced materials such as Al-Mg-based alloys and CoCrFeNiV high entropy alloys. His work bridges the gap between experimental studies and computational simulations, contributing valuable insights into alloy design and optimization. ๐ŸŒŸ๐Ÿ”๐Ÿ“Š

Publication Top Notes

A Machine Learning Perspective on Hardness Prediction in Advanced Multicomponent Al-Mg Based Lightweight Alloys

Ali Othman Albaji | Computer Science and Artificial Intelligence | Best Researcher Award

Ali Othman Albaji | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Ali Othman Albaji, Libyan Authority for Scientific Research, Libya

With a Bachelor’s in Electrical Engineering and a Master’s in Electronics & Telecommunications from Universiti Teknologi Malaysia, this accomplished professional has extensive experience in academia and industry. Currently an Assistant Professor at the Higher College of Science and Technology in Libya, they also lead CR Technology System in the MENA region. Their research interests include optical wireless technologies and machine learning applications in environmental monitoring. Fluent in Arabic and English, with a diploma in Italian, they are also the President of the Postgraduate Student Society at UTM. ๐Ÿ“ก๐ŸŽ“๐ŸŒโœ๏ธ

Publication profile

google scholar

Academic Backgroundย 

With a diverse academic journey, the individual holds a Masterโ€™s in Public Management and Leadership from the London School of Economics (LSE), UK, completed in 2010. They further pursued a Master in Electronics and Telecommunications at the University Technology Malaysia from 2019 to 2023. Their foundational education includes a Bachelor’s degree in Electrical Engineering, specializing in General Communications, from the Civil Aviation Higher College in Tripoli, Libya, earned in 2007. Additionally, they completed a Diploma in the Italian language during the 2011/2012 academic year. ๐ŸŽ“๐Ÿ“ก

Experience

Dr. Ali Othman Albaji boasts a diverse work history across reputable organizations. He started as a Sales Advisor at Akida Company (LG) and ZTE/Telecom China, honing his expertise in the telecommunications field. His academic journey includes significant roles as an Assistant Professor and lecturer in Electronics and Telecommunications. In addition to his teaching, he has demonstrated leadership as the Chairman of CR Technology System (CRTS Group) and the President of the Postgraduate Student Society at Universiti Teknologi Malaysia. Dr. Albajiโ€™s commitment to both academia and industry underscores his dedication to advancing technology and education. ๐Ÿ“ก๐ŸŽ“๐Ÿ’ผ๐ŸŒŸ

Main Hard Skillsย 

Dr. Albaji possesses a robust set of technical skills, including proficiency in CAD Design, MATLAB Simulation Analysis, Python, and data visualization tools like Tableau. His capabilities extend to qualitative and quantitative analysis, SCADA systems, and programming languages like Verilog and HTML. These skills enable him to tackle complex research problems and contribute innovatively to his field.ย 

Languagesย 

Fluent in Arabic and English, with an IELTS Band Score of 8.5, Dr. Albaji also has a very good command of Italian. This linguistic proficiency allows him to collaborate with international researchers and disseminate his work to a broader audience.ย 

Research focus

Ali Othman Albaji’s research focus centers on machine learning applications in environmental noise classification, emphasizing smart cities and mobile communications. His work includes developing algorithms for monitoring and classifying noise pollution using MATLAB, contributing to urban planning and public health. He has also explored traffic noise impacts on residential areas and mobile telecommunications in Libya. His diverse research interests extend to the design and implementation of communication systems, highlighting the integration of technology in environmental studies. Through these contributions, Albaji aims to enhance noise management and promote sustainable urban environments. ๐ŸŒ๐Ÿ“Š๐Ÿ”Š๐Ÿ“ก

Publication top notes

Investigation on Machine Learning Approaches for Environmental Noise Classifications

A Machine Learning for Environmental Noise Monitoring and Classification Using Matlab

Machine Learning for Environmental Noise Classification in Smart Cities

Designing the Global System for Mobile Communications GSM-900 Cellular Network up to the Nominal Cell Plan in Tripoli, Libya

Conclusion and Recommendations

A Review of Traffic Highway Noise Towards Residential Area

NOISE POLLUTION DATA REPORTING AND WAREHOUSING USING TABLEAU SOFTWARE

Designing and Implementing a Signed Multiplier Radix-2 Using Boothโ€™s Algorithm

Abderrezzaq Benalia | Engineering and Technology | Best Researcher Award

Abderrezzaq Benalia | Engineering and Technology | Best Researcher Award

Assist Prof Dr Abderrezzaq Benalia, Higher normal school of Constantine, Algeria

Evaluation for Best Researcher Award: Assist. Prof. Dr. Abderrezzaq Benalia.

Publication profile

google scholar

Educational Background

Dr. Abderrezzaq Benalia holds a Ph.D. in Environmental Engineering from Salah Boubnider University, Constantine 3, Algeria. His doctoral research focused on the extraction and valorization of natural plant products as bio-coagulants for improving water quality, showcasing his commitment to sustainable environmental practices. Additionally, his M.Sc. thesis on the coagulation-flocculation process for drinking water treatment further solidifies his expertise in environmental engineering.

Positions Held and Teaching Experience

Dr. Benalia has held several notable positions, including being a representative of the environment in Yahia Beni Guecha, Mila, Algeria, from 2011 to 2016. His teaching experience spans various prestigious institutions, such as the Higher Normal School of Constantine and the National Polytechnic School of Constantine, where he has taught subjects like Chemical Kinetics, Analytical Chemistry, and Water Chemistry. His teaching excellence is reflected in his consistent contributions to environmental and process engineering education.

Research Interests and Supervision

His areas of interest include biomaterials, water and wastewater treatment, water pollution, and the extraction of natural substances. Dr. Benalia has also shown a strong commitment to mentoring students, having supervised several graduate projects, including Long Cycle and Engineer/Master students.

Additional Contributions

Dr. Benalia has been actively involved in organizing scientific events, such as the Inaugural National Congress in Physical and Chemistry Science (INCPCS 2024). He has also led significant research projects, including the improvement of bioenergy production from biodegradable waste, demonstrating his leadership and innovation in environmental research.

Prizes, Awards, and Honors

Dr. Benalia has received numerous accolades, including the Young Researcher Award from Salah Boubnider University in 2016, and the Best Researcher Award in Environmental Engineering from World Top Scientists in 2024. These awards recognize his impactful contributions to the field of environmental engineering.

Publications and Communications

Dr. Benalia has authored several high-impact publications in renowned journals. His research on the removal of dyes from water using aluminum-based water treatment sludge and the application of plant-based coagulants in water treatment highlights his innovative approach to environmental challenges. His work on the synthesis and application of bio-sorbents from artichoke and orange peels for wastewater treatment further emphasizes his focus on sustainable solutions.

Conclusion

Dr. Abderrezzaq Benalia’s extensive educational background, diverse teaching experience, and impactful research contributions make him a strong candidate for the Best Researcher Award. His dedication to environmental sustainability, innovative research, and student mentorship exemplifies the qualities of a top researcher in his field.

Publication top notes

Use of acorn leaves as a natural coagulant in a drinking water treatment plant

Use of Aloe vera as an Organic Coagulant for Improving Drinking Water Quality

Optimization of active coagulant agent extraction method from Moringa Oleifera seeds for municipal wastewater treatment

The use of as natural coagulant in algerian drinking water treatment plant

The use of central composite design (CCD) to optimize and model the coagulation-flocculation process using a natural coagulant: Application in jar test and semi-industrial scale

Use of Extracted Proteins fromย Oak Leavesย as Bio-Coagulant for Water and Wastewater Treatment: Optimization by a Fractional Factorial Design

The adsorptive removal of Bengal rose by artichoke leaves: Optimization by full factorials design

Valorization of pine cones (pinus nigras) for industrial wastewater treatment and crystal violet removal: a sustainable approach based on bio-coagulants and a bio-adsorbent

Etude Expรฉrimentale et Modรฉlisation Du Processus de La Coagulation Floculation: Application Aux Eaux Destinรฉe a La Consommation

Waqas Haroon | Engineering and Technology | Best Researcher Award

Waqas Haroon | Engineering and Technology | Best Researcher Award

Dr Waqas Haroon, International Isalmic University, Islamabad, 44000, Pakistan, Pakistan

Based on Dr. Waqas Haroon’s qualifications and accomplishments, he appears to be a strong candidate for a Best Researcher Award.

publication profile

google scholar

Education and Academic Excellence

Dr. Haroon is currently pursuing a PhD in Transportation Engineering at the University of Engineering and Technology, Taxila, with a commendable GPA of 3.61/4. His earlier degrees in Transportation Engineering (M.Sc.) and Civil Engineering (B.Sc. Hons.) also reflect high academic performance, with GPAs of 3.54/4 and 3.36/4, respectively. This solid educational foundation underscores his commitment and expertise in his field. ๐ŸŽ“๐Ÿ“š

Research Contributions

Dr. Haroon’s research output is impressive, with several high-quality publications either accepted or under review in reputable journals. His work includes studies on the performance of modified asphalt binders, nano silica effects, and the impact of carpooling on traffic sustainability. These contributions reflect a deep engagement with current issues in transportation engineering and materials science. ๐Ÿ“„๐Ÿ”ฌ

Professional Development

Dr. Haroon has participated in various professional courses, enhancing his knowledge in areas such as entrepreneurship, infrastructure development, and modern engineering techniques. His proactive approach to professional development showcases his dedication to staying updated with industry trends and practices. ๐Ÿ› ๏ธ๐ŸŒŸ

Teaching and Administrative Roles

As a lecturer at International Islamic University, Islamabad, Dr. Haroon has taken on multiple responsibilities, including teaching and administrative roles. His involvement in committees and technical activities highlights his leadership and organizational skills, which complement his research expertise. ๐Ÿ‘จโ€๐Ÿซ๐Ÿ“ˆ

Achievements and Recognition

Dr. Haroon has received several accolades, including a merit-based laptop award and internal merit scholarships, indicating recognition of his academic and research excellence. These achievements reinforce his qualifications and potential as a top researcher. ๐Ÿ…๐ŸŽ–๏ธ

Overall, Dr. Waqas Haroonโ€™s strong academic background, significant research contributions, commitment to professional development, and recognized achievements make him a suitable candidate for the Best Researcher Award.

 

Yifei Zhang | Engineering and Technology | Best Researcher Award

Yifei Zhang | Engineering and Technology | Best Researcher Award

Mr Yifei Zhang, University of Leeds, China

Yifei Zhang appears to be a strong candidate for the Research for Best Researcher Award based on the provided details.

Publication profile

Orcid

Education

University of Leeds: School of Electronic & Electrical Engineering (10/2023-Present), Harbin Institute of Technology: School of Electrical Engineering and Automation (09/2021-07/2023) – GPA: 89.968/100, Zhejiang Sci-Tech University: Qixin College (09/2017-06/2021) – GPA: 4.04/5 (Top 1/37).

Publications

Hybrid ANPC Grid-Tied Inverter Design with Passivity-Based Sliding Mode Control Strategy (07/2024) Summary: This publication explores an advanced inverter design integrating a passivity-based sliding mode control strategy, enhancing grid-tied inverter performance and reliability.Analysis and Error Separation of Capacitive Potential in the Inductosyn (09/2022) Summary: This work focuses on capacitive potential errors in inductosyn devices, providing a detailed analysis and separation methods to improve measurement accuracy.

Honors

Honorable Mention, American College Students Mathematical Contest in Modeling (04/2020). Provincial Third Prize, National Mathematical Contest in Modeling for College Students (12/2019). Third Prize, Zhejiang University Student Robot Creative Competition (12/2019). Provincial Third Prize, National Electronic Design Competition for College Students (09/2019).

Research Statement

Harmonic Cancellation Design of Circular Induction Synchronizer (03/2022-09/2022): Developed a system for measuring angles in circular induction synchronizers, focusing on error analysis and optimization for harmonic elimination. Optimal Design of Finite Angle Driven Flux Switching Arc Permanent Magnet Motor (01/2022-07/2022): Conducted finite element simulations to optimize motor parameters and reduce torque ripple. Brushless DC Motor Drive Controller Design (09/2020-06/2021): Designed and assembled a control board for brushless DC motors, implementing both sensorless and sensor-based control.

Publication top notes

Hybrid ANPC Grid-Tied Inverter Design with Passivity-Based Sliding Mode Control Strategy

 

 

 

Ioannis Chatzilygeroudis | Computer Science and Artificial Intelligence | Best Researcher Award

Ioannis Chatzilygeroudis | Computer Science and Artificial Intelligence | Best Researcher Award

Prof Ioannis Chatzilygeroudis, University of Patras, Greece

Prof. Emeritus at the University of Patras, Greece, with a rich educational background in Mechanical and Electrical Engineering (NTUA), Theology (University of Athens), MSc in Information Technology, and a PhD in Artificial Intelligence (University of Nottingham). Fluent in Greek and English, he specializes in AI, KR&R, knowledge-based systems, theorem proving, intelligent tutoring, e-learning, machine learning, natural language generation, sentiment analysis, semantic web, and educational robotics. His prolific research includes a PhD thesis, 18 edited volumes, 21 book chapters, 46 journal papers, 115 conference papers, 8 national conference papers, and 14 workshop papers. ๐Ÿ“š๐Ÿค–๐Ÿ’ป๐ŸŒ

Publication profile

Orcid

Education

๐Ÿ“š From September 1968 to June 1974, completed secondary education, earning a Certificate of High School Graduation in Science. ๐ŸŽ“ Pursued a Diploma in Mechanical and Electrical Engineering with a specialization in Electronics at the National Technical University of Athens from October 1974 to July 1979. ๐Ÿ“œ From February to June 1983, obtained a Certificate of Educational Studies from PATES of SELETE, Greece. ๐Ÿ“– Achieved a Bachelor in Theology from the University of Athens, completed between October 1979 and December 1987. ๐ŸŽ“ Earned an MSc in Information Technology from the University of Nottingham in 1989, followed by a PhD in Artificial Intelligence from the same university in 1992. ๐Ÿง  Thesis: “Integrating Logic and Objects for Knowledge Representation and Reasoning.”

Experience

๐Ÿ“˜ From Feb. 1982 to June 1982, I served as a part-time lab professor at PALMER Higher School of Electronics in Greece, teaching Electronics Lab. My full-time teaching journey began at TEI of Athens (1982-84), where I covered courses like Electrotechnics and Circuit Theory. My secondary education tenure (1984-92) focused on electrical engineering subjects. I then transitioned to higher education, teaching at TEI of Kozani and Chalkida, and later at the University of Nottingham (1990-92). From 1995-2006, I was a senior researcher and lecturer at the University of Patras, ultimately becoming a professor (2009-2023). Now, I am a Professor Emeritus. ๐ŸŽ“๐Ÿ”ฌ

Projects

From June 1993 to November 1995, I managed the CTI team for the DELTA-CIME project, developing a knowledge-based production control system. I led several initiatives, including the MEDFORM project for multimedia education and the national project for educational software in chemistry. As a senior researcher, I contributed to intelligent systems for tele-education and hybrid knowledge representation. I led multiple European projects like MENUET, AVARES, and TESLA, focusing on innovative education through virtual reality. My work aims to enhance learning experiences across disciplines, involving collaboration with various international partners. ๐ŸŒ๐Ÿ“š๐Ÿ’ป๐ŸŽ“

Research focus

Ioannis Hatzilygeroudis specializes in artificial intelligence and its applications in various domains, particularly in agriculture and healthcare. His research includes intelligent systems for diagnosing farmed fish diseases, employing deep learning techniques for image analysis, and exploring natural language processing methods. He has contributed significantly to the development of expert systems and reinforcement learning approaches to improve disease prediction in aquaculture. Additionally, his work in sentiment analysis and e-learning demonstrates a commitment to advancing educational technologies and user experience. Hatzilygeroudis’s interdisciplinary approach combines computer science with practical applications, making significant strides in health and environmental management. ๐ŸŒฑ๐ŸŸ๐Ÿ’ป๐Ÿ“Š

Publication focus

Using Level-Based Multiple Reasoning in a Web-Based Intelligent System for the Diagnosis of Farmed Fish Diseases

An Integrated GIS-Based Reinforcement Learning Approach for Efficient Prediction of Disease Transmission in Aquaculture

Speech Emotion Recognition Using Convolutional Neural Networks with Attention Mechanism

Expert Systems for Farmed Fish Disease Diagnosis: An Overview and a Proposal

Expert Systems for Farmed Fish Disease Diagnosis: An Overview and a Proposal

A Convolutional Autoencoder Approach for Boosting the Specificity of Retinal Blood Vessels Segmentation

Evaluating Deep Learning Techniques for Natural Language Inference

Tech Advancement Award

Tech Advancement Award

Introduction:

Welcome to the Tech Advancement Award, celebrating innovation and excellence in technology. This award recognizes individuals or teams who have made significant contributions to advancing technology and pushing the boundaries of what's possible.

About the Award:

The Tech Advancement Award honors pioneers who have demonstrated exceptional creativity, ingenuity, and impact in the realm of technology. From groundbreaking inventions to transformative software solutions, this award celebrates those who drive progress and innovation in the tech industry.

Eligibility:

  • Open to individuals, teams, and organizations worldwide
  • No age limits
  • Candidates must have developed or contributed to innovative technological advancements
  • Qualifications may include relevant degrees, certifications, or professional experience
  • Publications, patents, or other documentation showcasing technological achievements are encouraged

Recurrence:

Annual

Evaluation Criteria:

  • Degree of innovation and originality
  • Impact on industry or society
  • Technological advancement and scalability
  • Demonstrated effectiveness or applicability of the technology

Submission Guidelines:

  • Submit a detailed description of the technological advancement or innovation
  • Provide evidence of impact, such as case studies, testimonials, or adoption rates
  • Include any relevant publications, patents, or technical documentation
  • Follow the specified format and submission deadlines

Recognition:

Recipients of the Tech Advancement Award receive a prestigious certificate, public recognition through various channels, and opportunities for further collaboration and support from industry partners.

Community Impact:

The Tech Advancement Award aims to inspire and empower individuals and organizations to push the boundaries of technology for the betterment of society. By recognizing and promoting technological innovation, this award fosters a culture of creativity, collaboration, and progress in the tech industry.

Biography:

Applicants are invited to provide a brief biography highlighting their contributions to technological advancements, relevant experience, and notable achievements in the field.

Abstract and Supporting Files:

Include a comprehensive abstract summarizing the technological advancement's objectives, methodology, and impact. Supporting files such as technical specifications, demonstrations, or user testimonials can enhance the submission and demonstrate the innovation's significance.