Gil Ju Lee | Engineering | Best Researcher Award

Posted on by ScienceFather

Prof. Gil Ju Lee | Engineering | Best Researcher Award

Associate Professor at Pusan National University, South Korea

Dr. Gil Ju Lee is an accomplished researcher and Associate Professor at the School of Electrical and Electronics Engineering, Pusan National University (PNU), South Korea. His expertise lies in novel photonic devices, advanced optoelectronics, bio-inspired imaging systems, and semiconductor nanowires. With a strong background in next-generation imaging, radiative cooling, and multifunctional nanophotonic devices, he has contributed significantly to cutting-edge technological advancements. Dr. Lee has received numerous prestigious awards, including the Outstanding Researcher Award from PNU (2022-2024) and the Samsung HumanTech Thesis Award. His research has been widely published in high-impact journals such as Nature Communications, Advanced Energy Materials, and Scientific Robotics. As the principal investigator of multiple national research projects, he continues to drive innovation in optoelectronics and nanophotonics.

Professional ProfileΒ 

Education

Dr. Gil Ju Lee earned his Integrated M.S./Ph.D. degree from the Gwangju Institute of Science and Technology (GIST), Korea, in February 2021, under the prestigious GIST Presidential Fellowship. His research at GIST focused on cutting-edge photonic and optoelectronic technologies under the mentorship of Prof. Young Min Song. Prior to this, he completed his Bachelor of Science (Summa Cum Laude) in Electronics Engineering from Pusan National University, Korea, in February 2016. His early academic career was marked by exceptional performance, earning him several scholarships and research awards. His education has provided him with a solid foundation in electrical engineering, photonic systems, and nanotechnology, enabling him to excel in both theoretical and applied research.

Professional Experience

Dr. Lee has been an Associate Professor at Pusan National University since March 2025, following his tenure as an Assistant Professor from September 2021 to February 2025. Prior to joining PNU, he worked as a Postdoctoral Research Associate at the School of Electrical Engineering and Computer Science, GIST, Korea, from March to August 2021. Throughout his career, Dr. Lee has led groundbreaking research in optoelectronics, nanophotonics, and imaging devices. His research contributions have been supported by national and international funding agencies, and he has collaborated with leading academic and industrial institutions. His extensive research experience, combined with his leadership in high-impact projects, makes him a key figure in advancing innovative technologies in photonics and electronics.

Research Interests

Dr. Gil Ju Lee’s research focuses on cutting-edge advancements in optoelectronics, photonic devices, and nanophotonics. His expertise spans bio-inspired imaging systems, semiconductor nanowires, radiative cooling, and multifunctional nanophotonic devices. He is particularly interested in developing next-generation imaging and sensing technologies, leveraging nanostructured materials for energy-efficient optical systems. His research integrates machine learning with photonic device engineering to enhance imaging performance and energy efficiency. Dr. Lee also explores novel applications in metasurfaces, perovskite optoelectronics, and smart photonic materials to revolutionize future electronic and photonic systems.

Awards and Honors

Dr. Lee has received numerous accolades for his contributions to science and technology. Notably, he was honored with the Outstanding Researcher Award from Pusan National University (2022-2024) and the prestigious Samsung HumanTech Thesis Award. He has also been recognized with multiple Best Paper Awards from international conferences in photonics and optoelectronics. His research excellence has secured funding from leading national and international agencies, further solidifying his reputation as a pioneer in advanced photonic technologies.

Research Skills

Dr. Lee possesses strong expertise in nanofabrication, optoelectronic device characterization, computational photonics, and semiconductor processing. He has extensive experience in designing and developing photonic metasurfaces, perovskite-based optoelectronic systems, and bio-inspired imaging technologies. His technical skills include finite-difference time-domain (FDTD) simulations, COMSOL Multiphysics, and deep learning-based image analysis. Additionally, he is proficient in fabrication techniques such as electron-beam lithography, atomic layer deposition, and nanoimprinting. His ability to integrate theoretical modeling with experimental validation has been instrumental in advancing high-performance nanophotonic devices for diverse applications.

Conclusion

Dr. Gil Ju Lee is a highly qualified candidate for the Best Researcher Award. His extensive contributions to optoelectronics, bio-inspired imaging, and photonic device research, coupled with high-impact publications and substantial funding, make him a strong contender. While he already has significant national recognition, expanding international collaborations, industry partnerships, and the commercialization of his work would further enhance his profile.

Publications Top Noted

  • Human eye-inspired soft optoelectronic device using high-density MoSβ‚‚-graphene curved image sensor array
    Authors: C Choi, MK Choi, S Liu, M Kim, OK Park, C Im, J Kim, X Qin, GJ Lee, …
    Year: 2017
    Citations: 520

  • Curved neuromorphic image sensor array using a MoSβ‚‚-organic heterostructure inspired by the human visual recognition system
    Authors: C Choi, J Leem, M Kim, A Taqieddin, C Cho, KW Cho, GJ Lee, H Seung, …
    Year: 2020
    Citations: 263

  • Bioinspired artificial eyes: Optic components, digital cameras, and visual prostheses
    Authors: GJ Lee†, C Choi†, DH Kim, YM Song
    Year: 2018
    Citations: 251

  • Colored, daytime radiative coolers with thin‐film resonators for aesthetic purposes
    Authors: GJ Lee, YJ Kim, HM Kim, YJ Yoo, YM Song
    Year: 2018
    Citations: 215

  • Wearable force touch sensor array using a flexible and transparent electrode
    Authors: JK Song, D Son, J Kim, YJ Yoo, GJ Lee, L Wang, MK Choi, J Yang, M Lee, …
    Year: 2017
    Citations: 194

  • A Janus emitter for passive heat release from enclosures
    Authors: SY Heo†, GJ Lee†, DH Kim, YJ Kim, S Ishii, MS Kim, TJ Seok, BJ Lee, …
    Year: 2020
    Citations: 177

  • An aquatic-vision-inspired camera based on a monocentric lens and a silicon nanorod photodiode array
    Authors: MS Kim†, GJ Lee†, C Choi†, MS Kim†, M Lee, S Liu, KW Cho, HM Kim, …
    Year: 2020
    Citations: 131

  • Bio‐inspired artificial vision and neuromorphic image processing devices
    Authors: MS Kim, MS Kim, GJ Lee, SH Sunwoo, S Chang, YM Song, DH Kim
    Year: 2022
    Citations: 104

  • Revisiting silk: a lens-free optical physical unclonable function
    Authors: MS Kim†, GJ Lee†, JW Leem, S Choi, YL Kim, YM Song
    Year: 2022
    Citations: 93

  • Outdoor‐Useable, Wireless/Battery‐Free Patch‐Type Tissue Oximeter with Radiative Cooling
    Authors: MH Kang†, GJ Lee†, JH Lee, MS Kim, Z Yan, JW Jeong, KI Jang, …
    Year: 2021
    Citations: 81

  • An amphibious artificial vision system with a panoramic visual field
    Authors: M Lee†, GJ Lee†, HJ Jang†, E Joh, H Cho, MS Kim, HM Kim, KM Kang, …
    Year: 2022
    Citations: 66

  • Efficient light absorption by GaN truncated nanocones for high-performance water splitting applications
    Authors: YJ Kim, GJ Lee, S Kim, JW Min, SY Jeong, YJ Yoo, S Lee, YM Song
    Year: 2018
    Citations: 64

Suihong Liu | Engineering | Young Scientist Award

Posted on by ScienceFather

Mr. Suihong Liu | Engineering | Young Scientist Award

Postdoc at Penn State University, United States

Dr. Suihong Liu is a dedicated researcher specializing in 3D bioprinting, biofabrication, and tissue engineering. He obtained a double Ph.D. degree in Mechanical Manufacture and Automation from Shanghai University and Biomedical Engineering from Technische UniversitΓ€t Dresden. Currently, he is a Postdoctoral Fellow at Penn State University in Prof. Ibrahim T. Ozbolat’s lab. With an impressive research portfolio, Dr. Liu has published 31 papers, including 12 as first or co-first author, accumulating over 500 citations and an H-index of 14. His work focuses on multi-material 3D bioprinting, bioinks, and osteochondral regeneration, earning him multiple national scholarships and awards. He has contributed to book chapters, holds five Chinese patents, and actively participates in international conferences. Dr. Liu is also a reviewer for prestigious journals. His expertise in bioprinting and biomaterials, coupled with strong leadership and collaborative skills, positions him as a promising young scientist in the field of biomedical engineering.

Professional ProfileΒ 

Education

Dr. Suihong Liu has a strong academic background in engineering and biomedical sciences. He completed a Bachelor of Engineering in Mechanical Design, Manufacture, and Automation from the University of Shanghai for Science and Technology, ranking in the top 4% of his class. He then pursued a Master-Ph.D. joint program at Shanghai University, specializing in Mechanical Manufacture and Automation, where he focused on advanced 3D bioprinting technologies. His academic excellence placed him in the top 5% of his cohort. Additionally, he undertook a joint Ph.D. program at Technische UniversitΓ€t Dresden in Germany, earning a double Ph.D. degree in Biomedical Engineering. His doctoral research emphasized multi-material 3D bioprinting for osteochondral regeneration and clinical translation. Dr. Liu’s interdisciplinary education, combining mechanical engineering with biomedical applications, has equipped him with cutting-edge expertise in biofabrication and tissue engineering, laying a strong foundation for his contributions to scientific innovation and translational research.

Professional Experience

Dr. Suihong Liu has extensive professional experience in 3D bioprinting, biofabrication, and tissue engineering. He is currently a Postdoctoral Fellow at Penn State University in Prof. Ibrahim T. Ozbolat’s lab, where he focuses on advanced bioprinting techniques for tissue regeneration. Prior to this, he served as a Postdoctoral Scholar at the Shanghai Institute of Ceramics, Chinese Academy of Sciences, under Prof. Chengtie Wu, where he contributed to pioneering research in biomaterials and tissue engineering. Throughout his academic and professional career, Dr. Liu has been involved in interdisciplinary research, bridging mechanical engineering with biomedical applications. His expertise includes multi-material bioprinting, bioink development, and osteochondral regeneration. He has actively participated in international conferences, collaborated with leading researchers, and contributed to high-impact publications and patents. Dr. Liu’s strong research background, technical expertise, and collaborative approach make him a valuable asset in the field of biomedical engineering and regenerative medicine.

Research Interest

Dr. Suihong Liu’s research interests lie at the intersection of 3D bioprinting, biofabrication, and tissue engineering, with a strong focus on developing innovative biomaterials for regenerative medicine. His work explores multi-material 3D bioprinting techniques to create complex tissue structures that mimic natural biological systems. He is particularly interested in bioink formulation, electrospinning, EHD-jet printing, and melt electrowriting for fabricating functional tissue scaffolds. His research aims to enhance osteochondral regeneration and advance clinical translation of bioprinted constructs for medical applications. Dr. Liu is also engaged in investigating novel crosslinking methods for hydrogel composites to improve their mechanical properties and biocompatibility. Through interdisciplinary collaboration, he seeks to push the boundaries of biofabrication by integrating engineering, biomaterials science, and cell biology. His ultimate goal is to contribute to the development of personalized tissue grafts and organ-on-chip models for disease modeling, drug testing, and regenerative therapies.

Award and Honor

Dr. Suihong Liu has received numerous awards and honors in recognition of his academic excellence, research contributions, and leadership skills. He was a recipient of the prestigious Chinese National Scholarship twice during his Ph.D., as well as the Chinese National Aspiration Scholarship. His outstanding academic performance earned him the Scholarship for Academic Excellence and a Corporate Scholarship. Dr. Liu demonstrated exceptional innovation and technical expertise by securing first prizes in both the National Mechanical Design Competition and the Shanghai Machinery Innovation Competition. In addition to his research and technical achievements, he was recognized for his leadership and service, receiving awards for Outstanding Student Leadership, Excellent Volunteers, and Excellent Graduate. Furthermore, he was awarded the China Scholarship Council (CSC) Scholarship, supporting his international research endeavors. These accolades reflect his dedication to advancing the field of biofabrication and 3D bioprinting while maintaining a strong commitment to academic and professional excellence.

Research Skill

Dr. Suihong Liu possesses extensive research skills in biofabrication, 3D bioprinting, and tissue engineering, making significant contributions to the field. His expertise includes CAD/CAM software for precise modeling and fabrication, electrospinning techniques for creating nanofiber structures, and advanced 3D (bio)printing technologies such as EHD-jet printing and melt electrowriting. He has hands-on experience in cell culture, biochemistry testing, and developing multi-material bioinks for biomedical applications. Dr. Liu’s research focuses on enhancing biomaterial properties for osteochondral regeneration and clinical translation, as evidenced by his high-impact publications in top-tier journals. Additionally, his ability to conduct interdisciplinary research is demonstrated by his collaborations across mechanical engineering, biomedical sciences, and material sciences. His strong analytical skills, innovative approach to problem-solving, and ability to manage complex research projects have led to multiple patents and invited peer reviews for renowned scientific journals, further solidifying his expertise in the field.

Conclusion

Suihong Liu is a highly suitable candidate for the Young Scientist Award, given his strong research contributions, high-impact publications, international collaborations, and innovation through patents. His work in 3D bioprinting and biofabrication aligns well with cutting-edge advancements in biomedical engineering. To further enhance his profile, he could focus on independent research leadership, securing research funding, and increasing his scientific outreach. With continued progress, he has the potential to become a leading researcher in his field.

Publications Top Noted

  • Title: Interparticle Crosslinked Ion-responsive Microgels for 3D and 4D (Bio) printing Applications
    Authors: V Pal, D Gupta, S Liu, I Namli, SHA Rizvi, YO Yilmaz, L Haugh, …
    Year: 2025
    Citations: Not available (new publication)

  • Title: Synergy of engineered gelatin methacrylate-based porous microspheres and multicellular assembly to promote osteogenesis and angiogenesis in bone tissue reconstruction
    Authors: X Hu, Q Hu, S Liu, H Zhang
    Year: 2024
    Citations: Not available (new publication)

  • Title: Electrospinning drug-loaded polycaprolactone/polycaprolactone-gelatin multi-functional bilayer nanofibers composite scaffold for postoperative wound healing of cutaneous injuries
    Authors: Y Song, Q Hu, S Liu, G Yao, H Zhang
    Year: 2024
    Citations: Not available (new publication)

  • Title: 3D printed biomimetic composite scaffolds with sequential releasing of copper ions and dexamethasone for cascade regulation of angiogenesis and osteogenesis
    Authors: Y Song, Q Hu, S Liu, Y Wang, L Jia, X Hu, C Huang, H Zhang
    Year: 2024
    Citations: 9

  • Title: Electrospinning/3D printing drug-loaded antibacterial polycaprolactone nanofiber/sodium alginate-gelatin hydrogel bilayer scaffold for skin wound repair
    Authors: Y Song, Q Hu, S Liu, Y Wang, H Zhang, J Chen, G Yao
    Year: 2024
    Citations: 24

  • Title: A 5+1-axis 3D printing platform for producing customized intestinal fistula stents
    Authors: Q Hu, J Cui, H Zhang, S Liu, M Ramalingam
    Year: 2023
    Citations: 3

  • Title: Bioinks for space missions: the influence of long‐term storage of alginate‐methylcellulose‐based bioinks on printability as well as cell viability and function
    Authors: J Windisch, O Reinhardt, S Duin, K SchΓΌtz, NJN Rodriguez, S Liu, A Lode, …
    Year: 2023
    Citations: 16

  • Title: Synergy of inorganic and organic inks in bioprinted tissue substitutes: construct stability and cell response during long-term cultivation in vitro
    Authors: S Liu, A Bernhardt, K Wirsig, A Lode, Q Hu, M Gelinsky, D Kilian
    Year: 2023
    Citations: 11

  • Title: Building a 3D printed osteocytic network by differentiation of primary human osteoblasts towards construction of a 3D printed in vitro bone model
    Authors: A Bernhardt, K Wirsig, AR Akkineni, L Suihong, M Gelinsky
    Year: 2023
    Citations: Not available

  • Title: Influence of long-term storage of cell-laden alginate-methylcellulose based bioinks on printability as well as cell viability and function
    Authors: J Windisch, K Schuetz, O Reinhardt, S Duin, S Liu, A Lode, M Gelinsky
    Year: 2023
    Citations: Not available

  • Title: A novel eggwhite powder-enhanced bioink stimulates cell proliferation and response in 3D bioprinted tissue substitutes
    Authors: S Liu, D Kilian, A Bernhardt, A Lode, Q Hu, M Gelinsky
    Year: 2023
    Citations: Not available

  • Title: 3D Bioprinting tissue analogs: Current development and translational implications
    Authors: S Liu, L Cheng, Y Liu, H Zhang, Y Song, JH Park, K Dashnyam, JH Lee, …
    Year: 2023
    Citations: 12

 

Anuj Kumar | Engineering | Best Researcher Award

Posted on by ScienceFather

Mr. Anuj Kumar | Engineering | Best Researcher Award

Assistant Professor at Management Education & Research Institute, Janakpuri, India

Anuj Kumar is an accomplished academic and researcher in Computer Science & Engineering, currently pursuing a Ph.D. in Image Processing at AKTU, Lucknow. With over a decade of teaching experience at institutions like Guru Gobind Singh Indraprastha University and IIMT College of Engineering, he has significantly contributed to education and research. His expertise spans artificial intelligence, computer graphics, and data structures, complemented by proficiency in programming languages such as Python, C++, and MATLAB. He has published research papers in Scopus-indexed journals, IEEE Explorer, and Elsevier, along with a book chapter on distributed artificial intelligence. Recognized for his contributions, he was awarded at the Smart India Hackathon 2018 and qualified GATE 2012 with an 85.04 percentile. Anuj is actively involved in academic leadership, faculty development, and university assessments. With a commitment to innovation and interdisciplinary research, he aspires to advance computational methodologies and industrial applications in artificial intelligence and image processing.

Professional ProfileΒ 

Education

Anuj Kumar has a strong academic background in Computer Science & Engineering. He is currently pursuing a Ph.D. in Image Processing from Dr. A.P.J. Abdul Kalam Technical University (AKTU), Lucknow, Uttar Pradesh, demonstrating his commitment to advanced research. He earned his M.Tech in Computer Science & Engineering from Guru Gobind Singh Indraprastha University, Delhi, in 2014, securing a first division. His undergraduate studies include a B.Tech in Computer Science & Engineering from the Institution of Electronics & Telecommunication Engineers (IETE), Delhi, in 2011, also with first-division honors. Additionally, he holds a Three-Year Diploma in Computer Science & Engineering from IETE, Delhi (2006). His early education was completed under the U.P. Board, where he finished 10th grade (2000) and 12th grade (2003) in the second division. His educational journey, enriched with technical certifications like MCAD (Microsoft Certified Application Developer) in 2006, has laid a strong foundation for his expertise in computing and research.

Professional Experience

Anuj Kumar has extensive academic experience as an Assistant Professor in Computer Science & Engineering, with a teaching career spanning over a decade across prestigious institutions. Since July 2023, he has been serving at MERI College of Engineering and Technology, Haryana. Prior to this, he worked at IIMT College of Engineering, Greater Noida (2022–2023) and Greater Noida Institute of Technology, GGSIPU (2018–2022), where he contributed to curriculum development and research initiatives. He also held academic positions at USIC&T, Guru Gobind Singh Indraprastha University (2017–2018) and Ram-Eesh Institute of Engineering & Technology (2017). Earlier in his career, he served at Baba Saheb Ambedkar Institute of Technology & Management (2014–2016) and The Institution of Electronics & Telecommunication Engineers, Delhi (2011–2012). His vast experience includes mentoring students, conducting faculty development programs, and leading academic audits, showcasing his commitment to education, research, and institutional development.

Research Interest

Anuj Kumar’s research interests lie at the intersection of computer vision, image processing, artificial intelligence, and computational methods. Currently pursuing a Ph.D. in Image Processing, he focuses on developing advanced techniques for image enhancement, noise removal, and forgery detection using deep learning algorithms. His expertise extends to computer graphics, formal language automata, database management systems (DBMS), data structures, and discrete mathematics, which serve as the foundation for his research innovations. He has actively contributed to AI-driven industrial systems, biodiversity assessment using hyperspectral imaging, and disruptive innovations in tech-business analytics. His work has been published in Scopus-indexed journals, IEEE conference proceedings, and reputed international journals, reflecting the impact of his research. Additionally, he explores the applications of distributed artificial intelligence (DAI) for document retrieval, emphasizing intelligent data processing techniques. His dedication to cutting-edge research strengthens his role as a mentor and academician in the field of computer science and engineering.

Award and Honor

Anuj Kumar has been recognized for his academic excellence and research contributions through various awards and honors. He was awarded in the Smart India Hackathon 2018, a prestigious national-level competition promoting innovation and problem-solving skills. Demonstrating strong technical acumen, he qualified GATE 2012 with an impressive 85.04 percentile and a score of 302, showcasing his expertise in computer science and engineering. His achievements extend beyond academics, as he was the runner-up in the 100m race at IETE, New Delhi, in 2005, highlighting his diverse talents. Additionally, he has played a significant role in academia as a convener of the Joint Assessment Committee (JAC) for academic audits, deputy center superintendent for examinations, and university representative in various assessment programs. His dedication to research and education is further reflected in his memberships on editorial boards and professional organizations, solidifying his reputation as a distinguished academic and researcher.

Research Skill

Anuj Kumar possesses a strong research skillset that spans multiple domains within computer science and engineering, particularly in image processing, artificial intelligence, and computational methods. His expertise in deep learning, fuzzy techniques, and hyperspectral imaging enables him to develop innovative solutions for image enhancement, noise removal, and forgery detection. He is proficient in Python, MATLAB, C++, and various database management systems (DBMS), which support his research in data analysis, automation, and intelligent computing. His ability to critically analyze complex problems, design experiments, and implement advanced algorithms has led to multiple Scopus-indexed publications, IEEE conference presentations, and book chapters. Additionally, his role in academic audits, faculty development programs, and technical training workshops demonstrates his leadership in research and education. His strong analytical thinking, problem-solving capabilities, and hands-on approach to emerging technologies make him a highly skilled researcher in the field of computer vision and artificial intelligence.

Conclusion

Anuj Kumar has a strong academic foundation, technical expertise, and a growing research portfolio in computer science and engineering. His contributions to image processing, artificial intelligence, and industrial automation position him as a promising candidate for the Best Researcher Award. However, enhancing high-impact publications, research collaborations, and funding contributions would further strengthen his profile for this recognition.

Publications Top Noted

  • P., Jaidka, Preeti, P., Upadhyay, Prashant, A., Kumar, Aman, A.S., Kumar, Anuj Shiva, S.P., Yadav, Satya Prakash (2024). Transforming Coconut Farming with Deep Learning Disease Detection. Evergreen. Citations: 0

  • D., Sharma, Deepak, A.S., Kumar, Anuj Shiva, N., Tyagi, Nitin, S.S., Chavan, Sunil S., S.M.P., Gangadharan, Syam Machinathu Parambil (2024). Towards intelligent industrial systems: A comprehensive survey of sensor fusion techniques in IIoT. Measurement: Sensors. Citations: 3

  • S., Singh, Sandeep, B.K., Singh, B. K., A.S., Kumar, Anuj Shiva (2024). Multi-organ segmentation of organ-at-risk (OAR’s) of head and neck site using ensemble learning technique. Radiography. Citations: 3

  • R., Naz, Rahat, A.S., Kumar, Anuj Shiva (2024). Surveying Quantum-Proof Blockchain Security: The Era of Exotic Signatures. Conference Paper. Citations: 1

 

Zainab Mahdi Saleh | Engineering | Women Researcher Award

Posted on by ScienceFather

Mrs. Zainab Mahdi Saleh | Engineering | Women Researcher Award

An engineer at the Iraqi Ministry of Health at University of Babylon, Iraq

Mrs. Zainab Mahdi Saleh is an accomplished mechanical engineer specializing in thermodynamics, currently pursuing a Ph.D. at the University of Babylon. She holds a Master’s degree from the University of Wasit and has conducted significant research on energy-efficient cooling systems, publishing multiple papers on desiccant wheel performance and heat transfer enhancement. With extensive experience in mechanical systems, she has held various leadership roles in hospital infrastructure management, overseeing central cooling, generators, and medical oxygen systems. Proficient in ANSYS and other engineering software, she combines theoretical expertise with practical applications. A dedicated educator, she serves as an Assistant Lecturer and is an active member of the Iraqi Engineers Union. Her strong English proficiency and technical skills make her a valuable contributor to the field. To further enhance her impact, she aims to expand her research internationally, secure funding, and mentor young engineers, particularly women in STEM.

Professional Profile

Education

Mrs. Zainab Mahdi Saleh has a strong academic background in mechanical engineering, specializing in thermodynamics. She earned her Bachelor’s degree in Mechanical Engineering from the University of Thi Qar in 2008 and later pursued a Master’s degree in Mechanical Engineering at the University of Wasit, which she completed in 2020. Currently, she is a Ph.D. candidate at the University of Babylon, focusing on advanced research in thermodynamics. Her academic journey reflects a commitment to scientific excellence and continuous learning. Throughout her studies, she has developed expertise in energy-efficient cooling systems and heat transfer enhancement, contributing to innovative research in her field. She has also undertaken specialized courses in mechanical engineering, ANSYS software, and teaching methodologies, further strengthening her technical and instructional capabilities. Her dedication to education and research positions her as a leading figure in engineering, striving to make meaningful contributions to both academia and industry.

Professional Experience

Mrs. Zainab Mahdi Saleh has extensive professional experience in mechanical engineering, specializing in thermodynamics and energy systems. She has held various leadership positions in healthcare infrastructure management, overseeing critical mechanical systems such as central cooling, generators, and medical oxygen units. Her career began as a Maintenance Unit Supervisor at Al-Hay Health Sector in 2009, followed by roles at Al-Karama Teaching Hospital and Badra Model Health Center, where she managed mechanical and generator maintenance. She later advanced to Assistant Head of the Mechanical Division at Al-Zahraa Teaching Hospital, eventually becoming the Supervisor of both the Central Cooling and Medical Oxygen Units. In addition to her technical expertise, she serves as an Assistant Lecturer, contributing to academic research and mentoring students in mechanical engineering. Her combined experience in practical engineering applications and academia positions her as a leader in the field, bridging the gap between research and real-world industrial challenges.

Research Interest

Mrs. Zainab Mahdi Saleh’s research interests lie in the fields of thermodynamics, heat transfer enhancement, and energy-efficient cooling systems. She focuses on optimizing the performance of desiccant wheel technology to reduce latent heat loads in air conditioning systems, contributing to improved energy efficiency and sustainability. Her work also explores innovative heat transfer techniques in double-pipe heat exchangers, utilizing advanced methods such as wavy edge twisted tapes with varying twist ratios and perforated diameters to enhance thermal performance. With a strong background in both theoretical and experimental studies, she aims to develop practical solutions for industrial and environmental applications. Additionally, her expertise in mechanical systems, including medical oxygen and central cooling units, allows her to bridge the gap between research and real-world engineering challenges. By expanding her studies to include renewable energy integration, she seeks to further advance sustainable thermal management technologies for future applications.

Award and Honor

Mrs. Zainab Mahdi Saleh has earned recognition for her contributions to mechanical engineering, particularly in the field of thermodynamics and energy-efficient cooling systems. As an accomplished researcher, she has published multiple scientific papers in reputable university journals, showcasing her expertise in heat transfer enhancement and desiccant wheel technology. Her dedication to academia and research has positioned her as a respected scholar in her field. In addition to her academic achievements, she has held leadership roles in various healthcare institutions, demonstrating her ability to apply engineering principles to critical infrastructure management. Her commitment to education is evident in her role as an Assistant Lecturer, where she mentors and guides students in mechanical engineering. As a member of the Iraqi Engineers Union, she actively contributes to the engineering community. While she continues to advance her research, further recognition through national and international awards would strengthen her impact and professional standing.

Research Skill

Mrs. Zainab Mahdi Saleh possesses strong research skills in thermodynamics, heat transfer, and energy-efficient cooling systems. She excels in both theoretical and experimental research, demonstrated by her studies on desiccant wheel performance and heat exchangers. Her expertise includes conducting experimental setups, data analysis, and computational simulations using ANSYS software, enhancing the accuracy and efficiency of her findings. She is skilled in designing and optimizing mechanical systems to improve energy performance, particularly in HVAC and industrial cooling applications. Her ability to integrate engineering principles with real-world applications is evident in her research on moisture adsorption materials and innovative heat transfer techniques. Additionally, she is proficient in academic writing and has successfully published her work in university journals. Her analytical approach, problem-solving abilities, and technical expertise make her a valuable contributor to the field. As she advances in her Ph.D. research, her skills continue to evolve, driving innovation in mechanical engineering.

Conclusion

Zainab Mahdi Saleh is a strong candidate for the Women Researcher Award, given her academic achievements, research contributions, technical expertise, and leadership in the field of mechanical engineering. Her work on energy-efficient cooling and heat transfer enhancement is highly relevant to sustainability and industrial advancements.

To further enhance her candidacy, she could focus on expanding her research to international platforms, securing research funding, and mentoring the next generation of engineers, particularly women in STEM. Overall, her profile reflects dedication, technical excellence, and leadership, making her a deserving contender for this prestigious award.

Publications Top Noted

  • Title: “Theoretical Performance of Silica Gel Desiccant Wheel”

    • Authors: ZM Salih, ADM Hassan, AM Al-Dabagh
    • Journal: Wasit Journal of Engineering Sciences, Volume 7, Issue 3, Pages 66-74
    • Year: 2019
    • Citations: 1

  • Title: “The Experimentally Studying of Solid Desiccant Wheel Performance Combined with the System of Air Conditioning”

    • Authors: ZM Salih, ADM Hassen, AM Al-Dabagh
    • Journal: Journal of University of Babylon for Engineering Sciences, Pages 50-59
    • Year: 2019
    • Citations: 1

 

 

Najeeb ur rehman Malik | Engineering | Best Researcher Award

Posted on by ScienceFather

Dr. Najeeb ur rehman Malik | Engineering | Best Researcher Award

Assistant Professor at DHA Suffa University, Pakistan

Dr. Najeeb Ur Rehman Malik is a dedicated researcher and electronics engineer specializing in computer vision, deep learning, and image processing. He holds a Ph.D. from Universiti Teknologi Malaysia (UTM), where his research focused on multi-view human action recognition using convolutional neural networks (CNNs) and pose features. His expertise spans artificial intelligence, embedded systems, and digital signal processing. With multiple peer-reviewed publications, including work on COVID-19 detection using X-ray images and AI-driven healthcare solutions, he has significantly contributed to applied AI research. He has industry experience as an Assistant Manager at PTCL and has led technical events at the university and national levels. His proficiency in MATLAB, Python, and embedded systems complements his research acumen. While he has made impactful contributions, further global collaborations, research funding, and high-impact citations would enhance his academic influence. Dr. Malik continues to innovate in AI and computer vision, driving advancements in intelligent systems.

Professional ProfileΒ 

Education

Dr. Najeeb Ur Rehman Malik has a strong academic background in electronics engineering and communication systems. He is currently pursuing a Ph.D. at Universiti Teknologi Malaysia (UTM), where his research focuses on multi-view human action recognition using deep learning and convolutional neural networks (CNNs). He earned his Master of Engineering (M.E.) in Communication Systems and Networks from Mehran University of Engineering and Technology (MUET), Jamshoro, Pakistan, graduating with a CGPA of 3.40. His master’s research explored speeded-up robust features (SURF) for image retrieval systems. Prior to that, he completed his Bachelor of Engineering (B.E.) in Electronics Engineering from MUET with a CGPA of 3.45, gaining expertise in power electronics, automation, digital signal processing, and embedded systems. His academic journey reflects a strong foundation in artificial intelligence, image processing, and computer vision, positioning him as a key contributor to advancements in intelligent systems and AI-driven technologies.

Professional Experience

Dr. Najeeb Ur Rehman Malik has diverse professional experience in both academia and industry, specializing in electronics engineering, communication systems, and artificial intelligence. He served as an Assistant Manager at PTCL in Hyderabad, Sindh, Pakistan, from February 2017 to June 2018, where he gained hands-on experience in telecommunications, networking, and system management. Prior to that, he completed an internship at the National Telecommunication Corporation (NTC) in Karachi during June-July 2010, where he worked on networking infrastructure and telecommunication protocols. In addition to his industry experience, he has been actively engaged in research at Universiti Teknologi Malaysia (UTM), focusing on deep learning applications for multi-view human action recognition. His technical expertise spans MATLAB, Python, embedded systems, and digital signal processing, making him a well-rounded professional. With a strong blend of research and industry exposure, Dr. Malik continues to contribute to advancements in AI, image processing, and communication technologies.

Research Interest

Dr. Najeeb Ur Rehman Malik’s research interests lie at the intersection of computer vision, deep learning, image processing, and artificial intelligence. His primary focus is on multi-view human action recognition, where he integrates convolutional neural networks (CNNs) and pose estimation techniques to enhance accuracy in real-world scenarios. He has also explored content-based image retrieval, developing robust techniques using Speeded-Up Robust Features (SURF) and Scale-Invariant Feature Transform (SIFT). His work extends to healthcare applications, including AI-driven COVID-19 detection from chest X-ray images and the role of wearable technology in pandemic management. Additionally, he is interested in embedded systems, automation, and signal processing, particularly in developing intelligent and efficient computing solutions. His expertise in MATLAB, Python, and FPGA-based system design enables him to innovate in these areas. Dr. Malik aims to contribute to the advancement of AI-driven technologies for healthcare, surveillance, and human-computer interaction.

Award and Honor

Dr. Najeeb Ur Rehman Malik has been recognized for his contributions to computer vision, deep learning, and artificial intelligence through various academic and professional honors. His research in multi-view human action recognition and AI-driven healthcare solutions has been published in reputed journals, highlighting his impact in the field. During his academic career, he actively participated in technical events, conferences, and research forums, further solidifying his reputation as a dedicated scholar. He has also played a key role in organizing and volunteering at national and university-level exhibitions and competitions, showcasing his leadership and commitment to knowledge dissemination. His work on COVID-19 detection using AI and image processing techniques has received significant attention, demonstrating real-world applications of his research. While he has made commendable contributions, further recognition in the form of best paper awards, patents, and international research grants would enhance his standing in the global research community.

Research Skill

Dr. Najeeb Ur Rehman Malik possesses advanced research skills in computer vision, deep learning, and image processing, making significant contributions to AI-driven solutions. He is proficient in MATLAB and Python, leveraging machine learning frameworks like TensorFlow and PyTorch to develop multi-view human action recognition systems using convolutional neural networks (CNNs) and pose estimation techniques. His expertise extends to content-based image retrieval, feature extraction (SURF & SIFT), and embedded system design, enabling efficient AI model deployment. He is skilled in handling large datasets, performing statistical analysis, and optimizing deep learning architectures for real-world applications, including COVID-19 detection from chest X-ray images. Additionally, he has experience in academic writing, research methodology, and experimental design, ensuring high-quality publications. His ability to analyze complex problems, design innovative solutions, and collaborate on interdisciplinary research projects positions him as a strong contributor to advancements in AI, healthcare, and intelligent automation.

Conclusion

Najeeb Ur Rehman Malik is a strong candidate for the Best Researcher Award due to his technical expertise, interdisciplinary research contributions, and published works in computer vision and AI. However, improving citation metrics, securing research funding, and enhancing global collaboration would further strengthen his profile. If he has additional awards, patents, or high-impact projects, those should be highlighted in the application to maximize competitiveness.

Publications Top Noted

  • Cascading pose features with CNN-LSTM for multiview human action recognition

    • Authors: NR Malik, SAR Abu-Bakar, UU Sheikh, A Channa, N Popescu
    • Year: 2023
    • Citations: 23

  • Robust Technique to Detect COVID-19 using Chest X-ray Images

    • Authors: A Channa, N Popescu, NUR Malik
    • Year: 2020
    • Citations: 23

  • Multi-view human action recognition using skeleton based-FineKNN with extraneous frame scrapping technique

    • Authors: NUR Malik, UU Sheikh, SAR Abu-Bakar, A Channa
    • Year: 2023
    • Citations: 18

  • Managing COVID-19 Global Pandemic With High-Tech Consumer Wearables: A Comprehensive Review

    • Authors: A Channa, N Popescu, NUR Malik
    • Year: 2020
    • Citations: 17

  • Salp swarm algorithm–based optimal vector control scheme for dynamic response enhancement of brushless double‐fed induction generator in a wind energy conversion system

    • Authors: A Memon, MWB Mustafa, TA Jumani, M Olatunji Obalowu, NR Malik
    • Year: 2021
    • Citations: 10

  • Performance comparison between SURF and SIFT for content-based image retrieval

    • Authors: NUR Malik, AG Airij, SA Memon, YN Panhwar, SAR Abu-Bakar
    • Year: 2019
    • Citations: 8

  • Multiview human action recognition system based on OpenPose and KNN classifier

    • Authors: NUR Malik, SAR Abu Bakar, UU Sheikh
    • Year: 2022
    • Citations: 5

  • Association of stride rate variability and altered fractal dynamics with ageing and neurological functioning

    • Authors: A Channa, N Popescu
    • Year: 2021
    • Citations: 3

  • Localized Background Subtraction Feature-Based Approach for Vehicle Counting

    • Authors: MA El-Khoreby, SAR Abu-Bakar, MM Mokji, SN Omar, NUR Malik
    • Year: 2019
    • Citations: 3

Danica Babic | Engineering | Best Researcher Award

Posted on by ScienceFather

Assoc. Prof. Dr. Danica Babic | Engineering | Best Researcher Award

University of Belgrade, Faculty of Transport and Traffic Engineering, Serbia

Prof. Dr. Danica Babić is an esteemed expert in air transport and traffic engineering, with extensive academic, research, and consultancy experience. She specializes in airline planning, transportation networks, and air passenger demand forecasting. With over 50 published papers in leading scientific journals and conference proceedings, she has made significant contributions to the field. Dr. Babić has been actively involved in international research projects, including FP7 and Horizon 2020, and has participated in numerous conferences and workshops worldwide. Her expertise extends to consulting in airport planning, network recovery, and aviation operations. She is also a program committee member of TRANSCODE and has delivered lectures on AI in aviation at global forums.

Professional Profile

Education

Dr. BabiΔ‡ earned her Ph.D. in Engineering (Air Transportation) from the University of Belgrade – Faculty of Transport and Traffic Engineering (UB-FTTE) in 2015, with a dissertation focused on network structure and airline scheduling optimization. Prior to that, she completed her Master’s degree in 2009 and a Bachelor’s degree in 2005, both in Air Transport Engineering from UB-FTTE. She has also participated in specialized training programs and workshops, including courses on air transport economics, risk analysis, and multimodal transport organized by leading institutions like EUROCONTROL and SESAR JU.

Professional Experience

Dr. BabiΔ‡ has been a faculty member at the University of Belgrade – Faculty of Transport and Traffic Engineering since 2005, holding positions ranging from Teaching Assistant to her current role as an Associate Professor. She has contributed to major research initiatives, including the European Commission-funded FP7 TRANSTOOLS 3 project and the Horizon 2020 SYN+AIR project. In addition to academia, she has served as a consultant on projects related to airline schedule optimization, airport design, and aviation demand modeling. Notably, she was involved in the sustainability study for Airport Konstantin Veliki in NiΕ‘ and the technical documentation for the Pljevlja Airport and Heliport project.

Research Interests

Dr. Danica Babić’s research primarily focuses on air transport planning and optimization, with a particular emphasis on airline scheduling, airport operations, and aviation demand forecasting. She explores the complexities of airline network structures, flight scheduling efficiency, and multimodal transportation integration. Her work contributes to enhancing operational resilience in the aviation industry, optimizing passenger and cargo transport flows, and improving decision-making in air transport systems. Additionally, she is deeply involved in data-driven analysis and AI applications in aviation, leveraging machine learning and advanced statistical modeling to predict air travel demand, assess airline performance, and optimize network recovery strategies. Her research extends to the role of artificial intelligence in air traffic management, disruption management, and capacity planning. Dr. BabiΔ‡ is also engaged in sustainability and environmental impact assessment within aviation, working on projects related to emissions reduction, green airport initiatives, and the integration of alternative fuels to support eco-friendly air transport development.

Awards and Honors

Dr. Danica BabiΔ‡ has received numerous academic and professional recognitions for her contributions to the field of air transport and traffic engineering. She has been honored by the University of Belgrade for her excellence in research and teaching, recognizing her significant role in advancing aviation studies. Her doctoral thesis on β€œNetwork Structure and Airline Scheduling Optimization” was highly regarded and contributed to innovations in airline operations. She has also been recognized by international organizations for her contributions to aviation research, including her involvement in prestigious EU-funded projects like FP7 Transtools 3 and Horizon 2020 SYN+AIR. As a program committee member of the International Conference on Science and Development of Transport (TRANSCODE), she has played a key role in shaping aviation research discussions.

Conclusion

Prof. Dr. Danica Babić is a highly qualified and accomplished researcher in air transport and traffic engineering. Her extensive research publications, EU project contributions, consultancy experience, and academic leadership make her a strong candidate for the Best Researcher Award. Strengthening her global collaborations, leading independent research initiatives, and acquiring additional international recognitions would further enhance her qualifications.

Overall, she is a highly deserving nominee with impactful research in transportation and aviation. πŸš€

Publications Top Noted

  1. Market share modeling in airline industry: An emerging market economies application
    • Authors: D. BabiΔ‡, J. Kuljanin, M. KaliΔ‡
    • Year: 2014
    • Citations: 27
  2. Modeling the selection of airline network structure in a competitive environment
    • Authors: D. BabiΔ‡, M. KaliΔ‡
    • Year: 2018
    • Citations: 22
  3. Integrated door-to-door transport services for air passengers: From intermodality to multimodality
    • Authors: D. BabiΔ‡, M. KaliΔ‡, M. JaniΔ‡, S. DoΕΎiΔ‡, K. KukiΔ‡
    • Year: 2022
    • Citations: 20
  4. Airport Access Mode Choice: Analysis of Passengers’ Behavior in European Countries
    • Authors: A. Colovic, S.G. Pilone, K. KukiΔ‡, M. KaliΔ‡, S. DoΕΎiΔ‡, D. BabiΔ‡, M. Ottomanelli
    • Year: 2022
    • Citations: 13
  5. The airline schedule optimization model: Validation and sensitivity analysis
    • Authors: O. BabiΔ‡, M. KaliΔ‡, D. BabiΔ‡, S. DoΕΎiΔ‡
    • Year: 2011
    • Citations: 11
  6. An AHP approach to airport choice by freight forwarder
    • Authors: S. DoΕΎiΔ‡, D. BabiΔ‡, M. KaliΔ‡, S. Ε½ivojinoviΔ‡
    • Year: 2023
    • Citations: 9
  7. Airline route network expansion: Modelling the benefits of slot purchases
    • Authors: D. BabiΔ‡, M. KaliΔ‡
    • Year: 2012
    • Citations: 9
  8. Recent trends in assessment of proposed consolidations in EU airline industry – From discretion to arbitrariness
    • Authors: D. PavloviΔ‡, D. BabiΔ‡
    • Year: 2018
    • Citations: 8
  9. IMPACT OF COVID-19 ON THE AVIATION INDUSTRY: An overview of global and some local effects
    • Authors: M. KaliΔ‡, D. BabiΔ‡, S. DoΕΎiΔ‡, J. Kuljanin, N. MijoviΔ‡
    • Year: 2022
    • Citations: 6
  10. Predicting air travel demand using soft computing: Belgrade airport case study
  • Authors: M. KaliΔ‡, S. DoΕΎiΔ‡, D. BabiΔ‡
  • Year: 2012
  • Citations: 6
  1. Efikasnost aviokompanija u Evropskoj uniji: Primena AHP i DEA metoda
  • Authors: S. DoΕΎiΔ‡, D. BabiΔ‡
  • Year: 2015
  • Citations: 4
  1. Modelling the estimation of the airline profit in case of purchasing new slots for increasing flight frequency
  • Authors: D. BabiΔ‡, M. KaliΔ‡
  • Year: 2011
  • Citations: 4
  1. Introduction to the air transport system
  • Authors: M. KaliΔ‡, S. DoΕΎiΔ‡, D. BabiΔ‡
  • Year: 2022
  • Citations: 3

Masoud Yaghini | Engineering | Best Researcher Award

Posted on by ScienceFather

Assoc Prof Dr Masoud Yaghini | Engineering | Best Researcher Award

Faculty Member at Iran University of Science and Technology, Iran

Dr. Masoud Yaghini is a distinguished faculty member in the Department of Rail Transportation at the Iran University of Science and Technology. Born on December 8, 1966, he holds an extensive academic and professional background in rail transportation planning and optimization techniques. With over two decades of experience, Dr. Yaghini has made substantial contributions to the fields of transportation logistics, network design, and data mining, particularly within the railway industry. His innovative approaches to complex rail transportation problems have earned him a reputation as a leading researcher in the field. Dr. Yaghini is widely published and continues to shape the future of transportation with cutting-edge research.

Professional Profile

Education

Dr. Yaghini received his Ph.D. in Rail Transportation Planning and Engineering from Northern Jiaotong University, Beijing, China, in 2003, with a focus on dynamic service network design. He also holds an MSc and BSc in Industrial Management from Islamic Azad University, Tehran. His master’s thesis on resource assignment optimization in preventive maintenance laid the foundation for his interest in large-scale optimization problems. Additionally, he furthered his knowledge with specialized training in Ergonomics and Human Factors for Railways from the University of Birmingham, UK, in 2005. This diverse educational background has equipped Dr. Yaghini with both theoretical and practical expertise in optimizing transportation systems.

Professional Experience

Dr. Yaghini has over 20 years of professional experience, primarily as a faculty member at the Iran University of Science and Technology. He teaches a wide range of courses, from advanced computer programming to railway operations management and data mining in transportation. His professional experience extends beyond academia into consultancy work in optimization and transportation planning. Dr. Yaghini has also conducted numerous short courses and workshops in data mining, information management, and metaheuristic algorithms for both academic institutions and private companies. His role as an educator and consultant has allowed him to bridge the gap between academic research and real-world transportation challenges.

Research Interests

Dr. Yaghini’s research primarily focuses on optimization problems in rail transportation, including train scheduling, fleet sizing, and locomotive scheduling. He has a strong interest in metaheuristics such as Genetic Algorithms, Tabu Search, and Ant Colony Optimization, as well as exact solution methods like Column Generation and Branch and Cut. His work also explores data mining techniques applied to railway systems, such as the prediction of train delays and analysis of accident data. His research is driven by the need to optimize and improve efficiency in transportation systems, particularly in large-scale rail networks. His work has significant practical implications for enhancing railway operations and minimizing costs.

Awards and Honors

Dr. Yaghini’s contributions to transportation research have earned him multiple accolades, though his recognition mainly stems from his published works in high-impact journals such as Applied Mathematical Modelling and Journal of Transportation Engineering. He has been recognized for his work on solving complex railway optimization problems through innovative algorithms like Ant Colony Optimization and Simulated Annealing. In addition to his publications, Dr. Yaghini has been invited to present his findings at numerous international conferences. While he has not widely publicized any specific awards, his ongoing research contributions have earned him a solid reputation in the global transportation research community, marking him as a key figure in rail transportation planning and optimization.

Conclusion

Dr. Masoud Yaghini’s research portfolio is impressive, with a strong emphasis on rail transportation and optimization problems. His consistent contributions to both academic knowledge and practical railway systems demonstrate his potential for recognition as a top researcher. By broadening his collaborative network and impact beyond academia, he could further strengthen his candidacy for prestigious awards like the Best Researcher Award.

Publication top noted

  1. Online prediction of arrival and departure times in each station for passenger trains using machine learning methods
    • Vafaei, S., Yaghini, M.
    • Transportation Engineering, 2024
    • πŸ“– 0 citations
  2. Analysis of the relationship between geometric parameters of railway track and twist failure by using data mining techniques
    • Izadi Yazdan Abadi, E., Khadem Sameni, M., Yaghini, M.
    • Engineering Failure Analysis, 2023
    • πŸ“– 2 citations
  3. A mathematical formulation and an LP-based neighborhood search matheuristic solution method for the integrated train blocking and shipment path problem
    • Yaghini, M., Mirghavami, M., Zare Andaryan, A.
    • Networks, 2021
    • πŸ“– 5 citations
  4. Efficient algorithms to minimize makespan of the unrelated parallel batch-processing machines scheduling problem with unequal job ready times
    • Zarook, Y., Rezaeian, J., Mahdavi, I., Yaghini, M.
    • RAIRO – Operations Research, 2021
    • πŸ“– 10 citations
  5. An adaptive structure on a new local branching algorithm using instantaneous dimensions and convergence speed: a case study for multi-commodity network design problems
    • Hajiyan, H., Yaghini, M.
    • SN Applied Sciences, 2020
    • πŸ“– 1 citation
  6. Optimization of embedded rail slab track with respect to environmental vibrations
    • Esmaeili, M., Yaghini, M., Moslemipour, S.
    • Scientia Iranica, 2020
    • πŸ“– 0 citations
  7. An Effective Improvement to Main Non-periodic Train Scheduling Models by a New Headway Definition
    • Jafarian-Moghaddam, A.R., Yaghini, M.
    • Iranian Journal of Science and Technology – Transactions of Civil Engineering, 2019
    • πŸ“– 2 citations
  8. Optimizing headways for urban rail transit services using adaptive particle swarm algorithms
    • Hassannayebi, E., Zegordi, S.H., Amin-Naseri, M.R., Yaghini, M.
    • Public Transport, 2018
    • πŸ“– 26 citations
  9. Train timetabling at rapid rail transit lines: a robust multi-objective stochastic programming approach
    • Hassannayebi, E., Zegordi, S.H., Amin-Naseri, M.R., Yaghini, M.
    • Operational Research, 2017
    • πŸ“– 48 citations
  10. Timetable optimization models and methods for minimizing passenger waiting time at public transit terminals
  • Hassannayebi, E., Zegordi, S.H., Yaghini, M., Amin-Naseri, M.R.
  • Transportation Planning and Technology, 2017
  • πŸ“– 35 citations