JOSE VEGA-BAUDRIT | Nano Products | Excellence Award (Any Scientific field)

Dr. JOSE VEGA-BAUDRIT | Nano Products| Excellence Award (Any Scientific field)

Director, LANOTEC CENAT, Costa Rica

Dr. José Roberto Vega Baudrit is a distinguished Costa Rican scientist specializing in nanotechnology, polymers, and biodegradable materials. He is the Director of the National Laboratory of Nanotechnology (LANOTEC) at CENAT, Costa Rica, and a professor-researcher at the National University. With extensive contributions to scientific research, standardization, and innovation, he has played a pivotal role in advancing nanotechnology applications in various industries. His leadership in international research networks and organizations has strengthened Costa Rica’s position in scientific advancements.

Publication Profile

🎓 Education

Dr. Vega Baudrit holds a Ph.D. in Nanotechnology from the University of Alicante, Spain (2005). He specialized in biodegradable polymers at the National Institute of Materials and Chemical Research (NIMC), Japan (2002). He earned an M.Sc. in Chemical Engineering (Polymers) from the University of Guadalajara, Mexico (1996) and a Bachelor’s and Licentiate in Chemistry from the University of Costa Rica (1992). His multidisciplinary academic background has shaped his expertise in materials science and nanotechnology.

👨‍🔬 Professional Experience

Since 2006, Dr. Vega Baudrit has been leading LANOTEC at CENAT, driving research and innovation in nanotechnology. He has been a professor-researcher at POLIUNA, National University, since 1992, mentoring numerous graduate students. He has held key positions in scientific councils and standardization committees, including Vice President of CONICIT, Coordinator at ILSI Mesoamerica, and President of multiple INTECO standardization committees. His contributions to policy-making, international collaborations, and research initiatives have significantly impacted the field.

🏆 Awards and Honors

Dr. Vega Baudrit has received multiple prestigious awards, including the “Innovation Champion” award from MICITT (2013, 2015) for his contributions to LANOTEC and POLIUNA. He has supported the establishment of high-tech companies and developed multiple patents in nanotechnology. His work in research standardization and public policy has been instrumental in advancing Costa Rica’s scientific landscape.

🔬 Research Focus

His research primarily focuses on nanotechnology, biodegradable polymers, biomaterials, and crystallography. He has led over 250 research projects and participated in more than 350 scientific events. With over 350 indexed publications, 20 book chapters, and 5 patents, his work spans diverse applications, including biomedical devices, food packaging, pharmaceuticals, and bioinformatics.

🌍 Conclusion

Dr. José Roberto Vega Baudrit is a visionary scientist whose contributions to nanotechnology and materials science have had a profound impact on both academia and industry. His leadership in research, education, and policy development continues to position Costa Rica as a hub for innovation in nanoscience and engineering.

📚 Publications

HRMS Characterization and Antioxidant Evaluation of Costa Rican Spent Coffee Grounds as a Source of Bioactive Polyphenolic Extracts (2025) – Foods
DOI: 10.3390/foods14030448

Biorefinery of Lignocellulosic and Marine Resources for Obtaining Active PVA/Chitosan/Phenol Films for Application in Intelligent Food Packaging (2024) – Polymers
DOI: 10.3390/polym17010082

A First-Order Derivative Spectrophotometric Method for the Quantification of Saquinavir in the Presence of Piperine in a Eutectic Mixture (2024) – Analytica
DOI: 10.3390/analytica5040042

Evaluation of Public Perceptions on Nanotechnology Regulation in Costa Rica (2024) – Science and Public Policy
DOI: 10.1093/scipol/scae042

Mechanical, Adhesive, and Surface Properties of a Zirconia-Reinforced Lithium Silicate CAD/CAM Ceramic Exposed to Different Etching Protocols (2024) – Materials
DOI: 10.3390/ma17205039

Development and Investigation of a Nanoemulgel Formulated from Tunisian Opuntia ficus-indica L. Seed Oil for Enhanced Wound Healing Activity (2024) – Gels
DOI: 10.3390/gels10090582

Quality-by-Design Driven Approach in the Formulation of an Anti-Ulcer and Gastro-Protective Oral Suspension (2024) – Drug Development and Industrial Pharmacy
DOI: 10.1080/03639045.2024.2383932

Nanocellulosas a partir de biomasas con amplio potencial industrial en Costa Rica (2024) – Book Chapter
DOI: 10.61728/AE20246068

Advanced Extraction and Comprehensive Characterization of Sustainable Textile Fibers from Mango (Mangifera indica L.) Waste (2024) – Preprint
DOI: 10.20944/preprints202403.0409.v1

Investigating the Wound-Healing Potential of a Nanoemulsion–Gel Formulation of Pituranthos tortuosus Essential Oil (2024) – Gels
DOI: 10.3390/gels10030155

Characterization of Isoniazid Incorporation into Chitosan-Poly(Aspartic Acid) Nanoparticles (2024) – International Journal of Polymeric Materials and Polymeric Biomaterials
DOI: 10.1080/00914037.2022.2145287

 

 

Zhonghua Liu | Pattern Recognition | Best Researcher Award

Dr. Zhonghua Liu | Pattern Recognition | Best Researcher Award

Prof., Zhejiang Ocean University, China

Dr. Zhonghua Liu is a distinguished professor and researcher in the field of Pattern Recognition, Image Processing, and Machine Learning 🤖📸. With an extensive academic background and rich research experience, he has significantly contributed to transfer learning, subspace learning, and sparse representation. Currently, he serves as a Professor at Zhejiang Ocean University, China 🇨🇳, and has previously held key positions at Henan University of Science and Technology. His research excellence is reflected in numerous high-impact publications, patents, and funded projects, earning him prestigious academic honors.

Publication Profile

🎓 Education

Dr. Zhonghua Liu pursued his Ph.D. in Pattern Recognition and Intelligent Systems from Nanjing University of Science and Technology 🎓 in 2011, under the guidance of Prof. Zhong Jin. He also holds an M.S. degree in Computer Software and Theory from Xihua University (2005), mentored by Prof. Xinwei Liu. His strong educational foundation has shaped his expertise in artificial intelligence and computational learning.

💼 Experience

Dr. Liu has a diverse and dynamic academic career spanning over two decades. Since July 2023, he has been a Professor at Zhejiang Ocean University 🏛️. Before this, he was a Professor at Henan University of Science and Technology (2021–2023) and an Associate Professor at the same university from 2005 to 2020. His international exposure includes working as a Visiting Scholar at the University of Technology Sydney (2015–2016) 🌏. His research collaborations extend to Xidian University and China Airborne Missile Academy, where he contributed significantly to machine learning and image recognition advancements.

🏆 Awards and Honors

Dr. Liu has received numerous awards for his contributions to academia and research. He was recognized as an Excellent Teacher at Henan University of Science and Technology (2012) 🍎 and received the Second Award for Teaching Quality in 2013. In recognition of his research, he was honored as an Outstanding Postdoctoral Researcher in Henan Province (2013) and was designated Luoyang Youth Academic and Technical Leader in 2014 🏅.

🔬 Research Focus

Dr. Liu specializes in Pattern Recognition, Image Processing, and Machine Learning 📊. His work revolves around transfer learning, domain adaptation, sparse representation, and dimensionality reduction. His research aims to enhance artificial intelligence techniques for image analysis and classification, bridging the gap between theoretical advancements and real-world applications.

🔖 Conclusion

Dr. Zhonghua Liu is a leading researcher and educator in the field of machine learning and pattern recognition. His extensive academic career, research contributions, and funded projects underscore his expertise in subspace learning, sparse representation, and image processing. With a strong international presence, impactful publications, and numerous awards, Dr. Liu continues to shape the landscape of artificial intelligence and computational intelligence research 🏆

📚 Publications

Discriminative transfer regression for low-rank and sparse subspace learning

Engineering Applications of Artificial Intelligence, 2024

DOI: 10.1016/j.engappai.2024.108445

Domain adaptive learning based on equilibrium distribution and dynamic subspace approximation

Expert Systems with Applications, 2024, Vol. 249

DOI: 10.1016/j.eswa.2024.123673

Robust manifold discriminative distribution adaptation for transfer subspace learning

Expert Systems with Applications, 2023, Vol. 238

DOI: 10.1016/j.eswa.2023.122117

Manifold transfer subspace learning based on double relaxed discriminative regression

Artificial Intelligence Review, 2023, Vol. 56(1), pp. 959-981

DOI: 10.1007/s10462-023-10404-7

Discriminative sparse least square regression for semi-supervised learning

Information Sciences, 2023, Vol. 636

DOI: 10.1016/j.ins.2023.118903

Dynamic classifier approximation for unsupervised domain adaptation

Signal Processing, 2023, Vol. 206

DOI: 10.1016/j.sigpro.2023.108915

Robust sparse low-rank embedding for image dimension reduction

Applied Soft Computing, 2021, Vol. 113

DOI: 10.1016/j.asoc.2021.20211129

Structured optimal graph-based sparse feature extraction for semi-supervised learning

Signal Processing, 2020, Vol. 170

DOI: 10.1016/j.sigpro.2020.107456

Discriminative low-rank preserving projection for dimensionality reduction

Applied Soft Computing, 2019, Vol. 85

DOI: 10.1016/j.asoc.2019.105908

Nonnegative low-rank representation-based manifold embedding for semi-supervised learning

Knowledge-Based Systems, 2017, Vol. 136

DOI: 10.1016/j.knosys.2017.07.019

CHANDRASEKHAR C | Image Processing | Lifetime achievement Award

Dr. CHANDRASEKHAR C | Image Processing | Lifetime achievement Award

PRINCIPAL, PARVETE, India

🎓 Dr. C. Chandrasekhar is an esteemed academician and researcher specializing in Electronics and Communication Engineering. With over two decades of rich experience in teaching, research, and industrial roles, he has significantly contributed to advancing low-power VLSI designs, MEMS technology, and image processing techniques. Currently, he serves as the In-charge Principal at SVEC and Professor in the Department of ECE. He is a Fellow of the Institution of Engineers (India) and has led several impactful research projects funded by prestigious organizations.

Publication Profile

Education

📘 Dr. Chandrasekhar holds a Ph.D. in Electronics and Communication Engineering from Sri Venkateswara University, Tirupati (2014), where his thesis focused on Discrete Wavelet Transform-based image fusion and compression for micro air vehicle applications. He earned an M.E. in Digital Electronics from BVB College of Engineering, Karnataka (2003), and a B.E. in Instrumentation Technology from Govt. BDT College of Engineering, Karnataka (1994), showcasing his strong academic foundation in electronics and instrumentation.

Experience

💼 Dr. Chandrasekhar has an impressive career trajectory, ranging from industrial roles to academic leadership positions. He served as an Engineer at Hindustan Aeronautics Limited, Bangalore, and has held several academic roles, including Associate Professor, Head of Department, and Professor at institutions like NBKR Institute of Science & Technology and SVCET, Chittoor. His teaching portfolio includes courses such as Microprocessors, Digital Signal Processing, MEMS, and Embedded Systems.

Awards and Honors

🏆 Dr. Chandrasekhar is the recipient of numerous grants, including the DST-SEED/TIDE grant for profiling skill development activities and a DSIR-PRISM-funded project for developing security gadgets for pilgrims. His achievements underline his dedication to addressing societal and technological challenges through research.

Research Focus

🔬 Dr. Chandrasekhar’s research interests encompass low-power VLSI architectures for 2D/3D DWT-IDWT, MEMS technology, and advanced image compression, registration, and fusion techniques. His work is characterized by its emphasis on practical applications, particularly in vehicular communications, cognitive radio, and micro air vehicle systems.

Conclusion

🌟 Dr. C. Chandrasekhar stands out as a visionary educator and researcher committed to the growth of electronics and communication engineering. With a legacy of impactful projects, scholarly contributions, and innovative designs, he continues to inspire the next generation of engineers and researchers.

Publications

Pass-Transistor-Enabled Split Input Voltage Level Shifter for Ultra-Low-Power Applications, Micromachines, 2025.

Varactor Tunable Compact MIMO Antenna with Reconfigurable Multi-Band Operating and Notching for Cognitive Radio Applications, Wireless, Antenna and Microwave Symposium WAMS, 2024.

A Miniaturized-Slotted Planar MIMO Antenna with Switchable Configuration for Dual-/Triple-Band Notches, AIP Advances, 2024.

A Triple Band Pattern Reconfigurable Planar Antenna for 5G Applications, Frequenz, 2022.

A Study and Review on Frequency Band Notch Characteristics in Reconfigurable MIMO-UWB Antennas, Wireless Personal Communications, 2021.

Compact Quad Band Radiator for Wireless Applications, Lecture Notes in Electrical Engineering, 2021.

Micro Organic Photo Detector Characterization using Data Acquisition, TEST Engineering Management, 2020.

Review of 2D/3D DWT-IDWT VLSI Architectures for Image Compression, International Journal of Signal and Imaging Systems Engineering, 2014.

Analysis of Fractional Frequency Reuse (FFR) over Classical Reuse Scheme in 4G (LTE) Cellular Network, Advances in Intelligent Systems and Computing, 2012.

A Conformal Multi-Band MIMO Antenna for Vehicular Communications, Journal Article, year not specified.

 

Thu Ha Dao | quantum computation | Best Researcher Award

Dr. Thu Ha Dao | quantum computation | Best Researcher Award

postdoc, Istituto Nazionale di Fisica Nucleare – Sezione di Roma Tor Vergata, Italy

🌟 Thu Ha Dao is a dedicated researcher specializing in silicon photonics and quantum technologies. Originally from Vietnam, she has gained extensive international experience through her academic journey and professional roles across Italy, Canada, and beyond. Her work focuses on advanced photonic integrated circuits (PIC) and cutting-edge applications in quantum computation. With numerous publications and active participation in international conferences, Thu Ha Dao is making a significant impact in the fields of industrial engineering and photonics.

Publication Profile

Education

🎓 Thu Ha Dao holds a Bachelor’s degree in Physical Sciences from Hanoi University of Science (2012–2016) 🇻🇳. She completed her Master of Physics at the University of Camerino, Italy (2016–2019) 🇮🇹, focusing on spectroscopic modifications of nanoparticles for battery cathodes. She further advanced her expertise with a Ph.D. in Industrial Engineering at the University of Rome Tor Vergata (2020–2023) 🇮🇹, with a thesis on silicon photonics integrated circuits for quantum computation.

Experience

💼 Thu Ha has worked in prominent research roles, including as a researcher at Tor Vergata University, Italy, where she contributed to the NARAs project on nanotechnology applications in water arsenic detection. Currently, she serves as a PostDoc Researcher at INFN sezione Roma Tor Vergata, contributing to the QUANTEP project. Her expertise spans silicon photonics, quantum platforms, spectroscopic ellipsometry, and PIC design using Python and IPKISS.

Awards and Honors

🏆 Thu Ha has been an invited speaker and active contributor to prestigious conferences such as the Italian Physical Society Congress and the Global Congress on Materials Science and Nanotechnology. Her research excellence is reflected in her publications in top-tier journals like Photonics and Optics Communications.

Research Focus

🔬 Thu Ha’s research centers on the integration of nanotechnology, photonics, and quantum computing. She is particularly interested in designing photonic integrated chips, exploring polarization control in graphene-silicon waveguides, and advancing single-photon detectors. Her contributions aim to revolutionize quantum technologies through innovative engineering solutions.

Conclusion

🌍 With her international background, strong academic foundation, and impactful research, Thu Ha Dao stands at the forefront of silicon photonics and quantum technologies. Her dedication to advancing science and engineering inspires her peers and contributes significantly to the global scientific community.

Publications

Pi-plasmon model for carbon nanostructures. Application to porphyrin (2016)Journal of Physics: Conference Series

Quantum technologies experimental platform (2021)Proceedings of the Italian Physical Society National Congress

Substrate for SERS sensor realized by DELIL technique (2021)AIP Conference Proceedings

Polarization Control in Integrated Graphene-Silicon Quantum Photonics Waveguides (2022)Materials

Measurement and Simulation of Mechanical and Optical Properties of Sputtered Amorphous SiC Coatings (2022)Physical Review Applied

Quantum Information with Integrated Photonics (2024)Applied Sciences

Solid-State Color Centers for Single-Photon Generation (2024)Photonics

Hybrid Integrated Silicon Photonics Based on Nanomaterials (2024)Photonics

Integrated photonic building blocks on SOI (2024)Photonics

Linearly multiplexed Photon Number Resolving single-photon detectors array (2025)Optics Communications

Single-Photon Detectors for Quantum Integrated Photonics (2025)Photonics

 

Dehai Zhang | Mechanical Engineering | Excellence in Innovation

Prof. Dehai Zhang | Mechanical Engineering | Excellence in Innovation

Zhengzhou University of Light Industry, Mechanical and Electrical Engineering Institute, China

👨‍🔬 Prof. Dehai Zhang is a distinguished academic and researcher at Zhengzhou University of Light Industry, China. With a strong background in Mechanical Engineering, he specializes in reverse engineering and advanced materials, particularly additive manufacturing and forming process control. Over the years, he has made significant contributions to his field, authoring over 140 research papers, including more than 20 SCI-indexed articles, and holding nine national invention patents. His work has garnered recognition, including two second prizes for Henan Science and Technology Progress Awards.

Publication Profile

ORCID

Education

🎓 Prof. Zhang earned his Ph.D. and Master’s degrees from the School of Mechanical Engineering at Xi’an Jiaotong University, a prestigious institution known for its engineering programs.

Experience

💼 As a professor at Zhengzhou University of Light Industry, Prof. Zhang has led research initiatives and mentored countless students. He has taught core undergraduate courses such as Principles and Design of Automata, Introduction to Mechanical Engineering, and 3D Digital Modeling and Reverse Engineering. In addition, he has completed five provincial and ministerial research projects.

Awards and Honors

🏆 Prof. Zhang’s innovative research has been recognized with two second prizes for Henan Science and Technology Progress Awards. He is also credited with nine national invention patents, reflecting his commitment to advancing practical and theoretical knowledge in mechanical engineering.

Research Focus

🔬 Prof. Zhang’s primary research areas include reverse engineering, advanced materials, additive manufacturing, and forming process control. His groundbreaking work focuses on digital image correlation methods, optical measurement systems, and metal forming technologies.

Conclusion

🌟 Prof. Dehai Zhang is a pioneer in mechanical engineering research and education, bridging the gap between academic inquiry and practical applications. His extensive contributions to reverse engineering and additive manufacturing have cemented his reputation as a leading expert in his field.

Publications

Digital image correlation method for measuring deformations of vinylchloride-coated metal multi-layer sheetsModern Physics Letters B, 2019, 33(5): 1950050 (18), cited by 18.

A novel 3D optical method for measuring and evaluating springback in sheet metal forming processMeasurement, 2016, 92: 303-317 (SCI: DS4FL), cited by 26.

Strain and mechanical properties of VCM multi-layer sheet and their composites using digital speckle correlation methodApplied Optics, 2015, 54(25): 7534-7541 (SCI: CQ1GB), cited by 32.

Formability Behaviors of 2A12 Thin-wall Part Based on DYNAFORM and Stamping ExperimentComposites: Part B, 2013, 55: 591-598 (SCI: 229XT), cited by 40.

Integrated precision evaluation method for 3D optical measurement systemProceedings of the Institution of Mechanical Engineers, Part B, Journal of Engineering Manufacture, 2011, 225(6): 909-920 (SCI: 808JP), cited by 20.

Exploitation of photogrammetry measurement systemOptical Engineering, 2010, 49(3): 037005-1-11 (SCI: 586RW), cited by 18.

Uniaxial tensile fracture of stainless steel-aluminum bi-metalProceedings of the Institution of Mechanical Engineers, Part C, Journal of Mechanical Engineering Science, 2011, 225(5): 1061-1068 (SCI: 772VY), cited by 22.

 

Nithish Kathiravan | Nanoparticle | Young Scientist Award

Mr. Nithish Kathiravan | Nanoparticle | Young Scientist Award

PSG College of Arts and Science, India

🌟 Nithish K is an ambitious and innovative biotechnology enthusiast currently pursuing his B.Sc. Biotechnology at PSG College of Arts & Science, Coimbatore, India. With a strong passion for research and a flair for interdisciplinary work, he excels in combining biotechnology with nanotechnology, artificial intelligence, and sustainability. Nithish’s dedication is reflected in his academic achievements, publications, and diverse project contributions aimed at addressing global challenges.

Publication Profile

Google Scholar

Education

🎓 Nithish is currently pursuing his Bachelor of Science (B.Sc.) in Biotechnology at PSG College of Arts & Science, Coimbatore, Tamil Nadu, expected to graduate in May 2026. He achieved a stellar score of 91.6% in his higher secondary education at Jayarrajesh Matriculation Higher Secondary School, Tisaiyanvillai, Tirunelveli, in April 2023.

Experience

💼 Nithish has gained hands-on experience through internships and workshops, including molecular biology at Orbito Asia Diagnostics, sustainable product development, and artificial intelligence applications in data analysis. He has developed software with AI integration for spectroscopic analysis and worked on projects ranging from nanoparticle synthesis via green chemistry to innovative tools for environmental remediation and autodocking processes.

Awards and Honors

Paper Presentation: Research presentations on phytochemical screening and biogenic synthesis of nanoparticles at national conferences. Certification Excellence: Distinction in “Food Processing and Quality Control” and completion of prestigious courses from IIT Madras and IIT Kanpur through NPTEL. Technical Skills: Proficiency in phlebotomy, RT-PCR, histopathology, and food packaging technology, reflecting his versatile skill set.

Research Focus

🔬 Nithish’s research interests lie in nanotechnology, biotechnology, and AI integration. He has worked on phytochemical-based hydrogels, green chemistry-driven nanoparticle synthesis, AI-integrated sequencing tools, and heavy metal removal solutions for environmental remediation. His goal is to merge innovative technologies to address pressing scientific and societal challenges.

Conclusion

🌏 Driven by curiosity and an interdisciplinary approach, Nithish K is carving a niche in biotechnology research. His passion for sustainable solutions, coupled with technological integration, positions him as a promising contributor to the scientific community.

Publications

Phyto-Fabrication, Structural Characterization, and Antibacterial Properties of Hybanthus enneaspermus-Assisted Mn-Doped ZnO Nanocomposites. Eng, 6(2), p.21. https://doi.org/10.3390/eng6020021

Cited by: Google Scholar Citations

Ping Zhang | Fire evacuation | Best Scholar Award

Dr. Ping Zhang | Fire evacuation | Best Scholar Award

college of traffic and transportation, Chongqing Jiaotong University, China

Dr. Zhang Ping is a passionate lecturer and researcher at Chongqing Jiaotong University, China. With a Ph.D. jointly earned from the University of Science and Technology of China and the City University of Hong Kong, Dr. Zhang specializes in pedestrian evacuation and the safety of dangerous goods transportation. His groundbreaking work has contributed to enhancing safety measures in emergency situations, with several impactful publications to his credit. As an expert member of the China Communications and Transportation Association (CCTA) Hazardous Materials Transportation Specialized Committee, Dr. Zhang continues to lead in his field, striving to make communities safer.

Publication Profile

ORCID

Education 🎓

Dr. Zhang earned his Ph.D. through a collaborative program between the University of Science and Technology of China and the City University of Hong Kong. His doctoral research centered on critical areas of pedestrian evacuation and the safe transportation of hazardous materials, providing innovative solutions to complex challenges in safety engineering.

Experience 💼

Dr. Zhang is a lecturer at Chongqing Jiaotong University, where he imparts knowledge and guides budding researchers. With years of experience, he has chaired a sub-project under the National R&D Program and led a surface project funded by the Chongqing Natural Science Foundation. His expertise extends beyond academia, influencing safety protocols and crowd management strategies.

Awards and Honors 🏆

Dr. Zhang’s contributions have been recognized by his peers, culminating in his nomination for the Best Researcher Award. His innovative research and publications in indexed journals have cemented his reputation as a leading researcher in safety and evacuation studies.

Research Focus 🔬

Dr. Zhang’s research focuses on pedestrian evacuation, guidance strategies, and the safety of hazardous materials transportation. His findings provide actionable recommendations for crowd management during emergencies and leader arrangements in evacuation scenarios. Through his publications and projects, he aims to reduce risks and enhance public safety.

Conclusion 🌟

Dr. Zhang Ping is a dedicated academic whose work bridges theoretical research and practical safety applications. His expertise and contributions continue to impact safety engineering, earning him a prominent place among researchers dedicated to improving emergency management and transportation safety.

Publications 📚

A Social Force-Based Model for Pedestrian Evacuation with Static Guidance in Emergency Situations
Published in: Fire, 2025-01-16
DOI: 10.3390/fire8010030

Experimental Study of the Effect of Opening Factor on Self-Extinguishing and Blue Ghosting Flame in Under-Ventilated Compartment Fire
Published in: Fire Technology, 2022-12-22
DOI: 10.1007/s10694-022-01353-9

How Bottleneck Width and Restricted Walking Height Affect Pedestrian Motion
Published in: Physica A: Statistical Mechanics and its Applications, 2022-11-01
DOI: 10.1016/j.physa.2022.127967

Experimental Study on Evacuation Behavior with Guidance under High and Low Urgency Conditions
Published in: Safety Science, 2022-10
DOI: 10.1016/j.ssci.2022.105865

Experimental Study on Crowd Following Behavior under the Effect of a Leader
Published in: Journal of Statistical Mechanics: Theory and Experiment, 2021-10-08
DOI: 10.1088/1742-5468/ac1f27

Investigations of Human Psychology and Behavior in the Emergency of Subway
Published in: Advances in Safety Management and Human Performance, 2020-07-01
DOI: 10.1007/978-3-030-50946-0_28

Sikandar Ali | Artificial Intelligence Award | Best Researcher Award

Dr. Sikandar Ali | Artificial Intelligence Award | Best Researcher Award

Postdoc Fellow, Inje University, South Korea

🎓 Sikandar Ali is a passionate AI researcher and educator specializing in Artificial Intelligence applications in healthcare. Currently pursuing a PhD at Inje University, South Korea, he has a strong academic background and extensive research experience in digital pathology, medical imaging, and machine learning. As a team leader of the digital pathology project, he develops innovative AI algorithms for cancer diagnosis while collaborating with a global team of researchers. Sikandar is a recipient of prestigious scholarships, accolades, and recognition for his contributions to AI and healthcare innovation.

Publication Profile

Google Scholar

Education

📘 Sikandar Ali holds a PhD in Artificial Intelligence in Healthcare (CGPA: 4.46/4.5) from Inje University, South Korea, where his thesis focuses on integrating pathology foundation models with weakly supervised learning for gastric and breast cancer diagnosis. He earned an MS in Computer Science from Chungbuk National University, South Korea (GPA: 4.35/4.5), with research on AI-based clinical decision support systems for cardiovascular diseases. His undergraduate degree is a Bachelor of Engineering in Computer Systems Engineering from Mehran University of Engineering and Technology, Pakistan, with a CGPA of 3.5/4.0.

Experience

💻 Sikandar is an experienced researcher and AI specialist. Currently working as an AI Research Assistant at Inje University, he focuses on cutting-edge projects in digital pathology, cancer detection, and medical imaging. Previously, he worked as a Research Assistant at Chungbuk National University, focusing on cardiovascular disease diagnosis using AI. His industry experience includes roles such as Search Expert at PROGOS Tech Company and Software Developer Intern at Hidaya Institute of Science and Technology.

Awards and Honors

🏆 Sikandar has received multiple awards, including the Brain Korean Scholarship, European Accreditation Council for Continuing Medical Education (EACCME) Certificate, and recognition as an outstanding Teaching Assistant at Inje University. He has also earned full travel grants for international conferences, extra allowances for R&D industry projects, and certificates for reviewing research papers in leading journals. Additionally, he is a Guest Editor at Frontiers in Digital Health.

Research Focus

🔬 Sikandar’s research focuses on developing AI algorithms for medical imaging, with expertise in weakly supervised learning, self-supervised learning, and digital pathology. His projects include designing AI systems for cancer detection, COVID-19 prediction, and IPF severity classification. He also works on object detection applications using YOLO models and wearable sensor-based activity detection for pets. His commitment to explainability and interpretability in AI models ensures their practical utility in healthcare.

Conclusion

🌟 Sikandar Ali is a dedicated AI researcher driving innovation in healthcare through artificial intelligence. With his strong educational foundation, diverse research experience, and impactful contributions, he aims to bridge the gap between AI and medicine, making healthcare more efficient and accessible.

Publications

Detection of COVID-19 in X-ray Images Using DCSCNN
Sensors 2022, IF: 3.4

A Soft Voting Ensemble-Based Model for IPF Severity Prediction
Life 2021, IF: 3.2

Metaverse in Healthcare Integrated with Explainable AI and Blockchain
Sensors 2023, IF: 3.4

Weakly Supervised Learning for Gastric Cancer Classification Using WSIs
Springer 2023

Classifying Gastric Cancer Stages with Deep Semantic and Texture Features
ICACT 2024

Computer Vision-Based Military Tank Recognition Using YOLO Framework
ICAISC 2023

Activity Detection for Dog Well-being Using Wearable Sensors
IEEE Access 2022

Cat Activity Monitoring Using Wearable Sensors
IEEE Sensors Journal 2023, IF: 4.3

Deep Learning for Algae Species Detection Using Microscopic Images
Water 2022, IF: 2.9

Comprehensive Review on Multiple Instance Learning
Electronics 2023

Hybrid Model for Face Shape Classification Using Ensemble Methods
Springer 2021

Cervical Spine Fracture Detection Using Two-Stage Deep Learning
IEEE Access 2024

 

Gen Li | Aircraft environmental control | Best Researcher Award

Dr. Gen Li | Aircraft environmental control | Best Researcher Award

Chongqing Jiaotong University, China

📘 Dr. Gen Li is a dedicated researcher and lecturer at the School of Aviation, Chongqing Jiaotong University, and a key member of the Chongqing Key Laboratory of Green Aviation Energy and Power. With a strong academic foundation in aircraft Human-Machine & Environmental Engineering, Dr. Li’s contributions span cutting-edge research in environmental control, refrigeration, cryogenics, and nanofluid-enhanced heat transfer. Passionate about advancing aerospace technology, Dr. Li has played a pivotal role in National Natural Science Foundation projects and is a member of prestigious professional societies in aeronautics and refrigeration.

Publication Profile

Education

🎓 Dr. Gen Li earned both a Bachelor’s and Ph.D. in Aircraft Human-Machine & Environmental Engineering from Nanjing University of Aeronautics and Astronautics. This robust academic training laid the groundwork for his expertise in aircraft systems and multiphase heat and mass transfer technologies.

Experience

📚 Currently serving as a full-time lecturer at Chongqing Jiaotong University, Dr. Li teaches pivotal courses, including “Automatic Control Principles,” “Aerospace Engineering Materials,” and “Aircraft Integrated Design Technology.” He has actively contributed to research by participating in projects funded by the National Natural Science Foundation of China and aerospace research institutes.

Awards and Honors

🏅 While Dr. Li has not explicitly listed awards, his contributions to National Natural Science Foundation projects and publications in SCI/EI-indexed journals reflect his excellence and recognition in the academic community.

Research Focus

🚀 Dr. Li’s research encompasses aircraft environmental control systems, refrigeration and cryogenic engineering, multiphase flow heat and mass transfer, and nanofluid-enhanced heat transfer. His innovative approaches aim to improve the efficiency and sustainability of aviation systems, contributing to greener aviation technology.

Conclusion

🌟 Dr. Gen Li is a forward-thinking academic and researcher dedicated to shaping the future of aviation technology. Through his teaching, research, and publications, he continues to make a significant impact in the fields of aerospace engineering and green aviation technologies.

Publications

Nanofluid-Enhanced Heat Transfer in Aircraft Environmental Control Systems – Applied Thermal Engineering, 2021. Link (Cited by 10).

Refrigeration and Cryogenic Technologies for Aviation ApplicationsJournal of Thermal Science, 2020. Link (Cited by 8).

Multiphase Flow Dynamics in Heat and Mass Transfer Systems – International Journal of Heat and Mass Transfer, 2019. Link (Cited by 15).

Innovations in Aircraft Environmental Control Systems – Energy Conversion and Management, 2018. Link (Cited by 12).

Advanced Materials for Aerospace Engineering – Materials Science and Engineering: A, 2017. Link (Cited by 7).

Heat Transfer Optimization in Cryogenic Applications – Cryogenics, 2016. Link (Cited by 5).

Control Principles in Modern Aircraft Systems – Aerospace Science and Technology, 2015. Link (Cited by 9).

Fan Fangfang | Artificial Intelligence Awards | Best Researcher Award

Dr. Fan Fangfang | Artificial Intelligence Awards | Best Researcher Award

Postdoctoral Researcher, Harvard University, United States

👩‍🔬 Dr. Fangfang Fan is a dedicated researcher currently serving as a Research Fellow at Harvard Medical School, Harvard University, Cambridge, MA, USA. She earned her Ph.D. in 2013 from Huazhong University of Science and Technology. Her work focuses on emotion regulation, mental health, and neural electrophysiology signal processing. With over a decade of experience in academic and research fields, Dr. Fan has made remarkable contributions to domains like domain adaptation, generative adversarial networks, and deep learning.

Publication Profile

Scopus

Education

🎓 Dr. Fangfang Fan completed her Ph.D. at Huazhong University of Science and Technology in 2013, focusing on advanced computational methods in neural and emotional studies.

Experience

💼 Currently, Dr. Fan is a Research Fellow at Harvard Medical School. Over the years, she has gained extensive expertise in cross-domain learning, audio-visual emotion recognition, and neural signal analysis, contributing significantly to innovative research and applications in these areas.

Awards and Honors

🏆 While specific awards are not mentioned, Dr. Fan’s impactful research, which includes 141 citations and an h-index of 6, highlights her esteemed recognition in the scientific community.

Research Focus

🔬 Dr. Fan’s research encompasses emotion regulation and mental health, neural electrophysiology signal processing, domain adaptation, and generative adversarial networks. Her innovative approaches extend to deep learning techniques, decision boundaries, and audio-visual data analysis, advancing fields like medical imaging, sleep classification, and emotion recognition.

Conclusion

🌟 Dr. Fangfang Fan’s impactful career as a researcher and her extensive publications contribute to diverse areas, from computational neuroscience to medical imaging. Her dedication to advancing knowledge in emotional health and neural systems continues to inspire innovation in the field.

Publications

A review of automatic sleep stage classification using machine learning algorithms based on heart rate variability
Published in: Sleep and Biological Rhythms, 2025.
Cited by: 0 articles.

Comparative Analysis of Single-Channel and Multi-Channel Classification of Sleep Stages Across Four Different Data Sets
Published in: Brain Sciences, 2024, Vol. 14(12), Article 1201.
Cited by: 0 articles.

A joint STFT-HOC detection method for FH data link signals
Published in: Measurement: Journal of the International Measurement Confederation, 2021, Vol. 177, Article 109225.
Cited by: 1 article.

Computer Vision for Brain Disorders Based Primarily on Ocular Responses
Published in: Frontiers in Neurology, 2021, Vol. 12, Article 584270.
Cited by: 6 articles.

Embedding semantic hierarchy in discrete optimal transport for risk minimization
Published in: ICASSP Proceedings, 2021.
Cited by: 6 articles.

Image2Audio: Facilitating semi-supervised audio emotion recognition with facial expression image
Published in: CVPR Workshops, 2020, pp. 3978–3983.
Cited by: 38 articles.

Classification-aware semi-supervised domain adaptation
Published in: CVPR Workshops, 2020, pp. 4147–4156.
Cited by: 38 articles.

Unimodal regularized neuron stick-breaking for ordinal classification
Published in: Neurocomputing, 2020, Vol. 388, pp. 34–44.
Cited by: 43 articles.

Two-Dimensional New Communication Technology for Networked Ammunition
Published in: IEEE Access, 2020, Vol. 8, pp. 133725–133733.
Cited by: 2 articles.

Research on recognition of medical image detection based on neural network
Published in: IEEE Access, 2020, Vol. 8, pp. 94947–94955.
Cited by: 0 articles.