Dilek Sönmezer Açıkgöz | Tissue engineering | Best Researcher Award

Dr. Dilek Sönmezer Açıkgöz | Tissue engineering | Best Researcher Award

Phd at Çukurova University, Turkey

Dr. Dilek Sönmezer Açıkgöz is a Lecturer at Çukurova University’s Department of Biomedical Engineering, specializing in biomaterials, tissue engineering, and regenerative medicine. She holds a PhD from Erciyes University and has contributed to cutting-edge research on pericardial fluid applications in tissue engineering. Dr. Sönmezer has published extensively in SCI-indexed journals and presents regularly at international conferences.

Publication Profile

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🎓 Education

PhD: Biomedical Engineering, Erciyes University (2012-2022)MSc: Biomedical Engineering, Erciyes University (2008-2011)BSc: Biology, Erciyes University (2004-2008)Internship: Eindhoven University of Technology (2010-2011)

💼 Experience

Lecturer: Çukurova University (2014-present)Research: Tissue engineering, pericardial fluid characterization, biomaterial developmentPatent Holder: Ultrasonic system for coronary bypass surgery

🏆 Awards & Honors

Patent: Ultrasonic vascular measurement system (2015)Key Publications: Bio-Medical Materials and Engineering, Biotechnology Applied BiochemistryRecognitions: Frequent presenter at international biomedical conferences

🔬 Research Focus

Biomedical Engineering: Biomaterials, tissue engineering, pericardial fluid studiesBioprinting: Developing biocompatible bioinks for 3D printingRegenerative Medicine: Exploring extracellular matrix applications for tissue regeneration

Publications 📖

Applications of a Biocompatible Alginate/Pericardial Fluid-Based Hydrogel for the Production of a Bioink in Tissue Engineering
Biotechnology and Applied Biochemistry | 2024-12-02
DOI: 10.1002/bab.2697
Contributors: Dilek Sönmezer Açıkgöz, Fatma Latifoğlu, Güler Toprak, Münevver Baran

Production of Hydrogel with Alginate and Pericardial Fluid for Use in Tissue Engineering Applications
Çukurova Üniversitesi Mühendislik Fakültesi Dergisi | 2023-12-28
DOI: 10.21605/cukurovaumfd.1410697
Contributors: Dilek Sönmezer, Fatma Latifoğlu

A Native Extracellular Matrix Material for Tissue Engineering Applications: Characterization of Pericardial Fluid
Journal of Biomedical Materials Research Part B: Applied Biomaterials | 2023-09
DOI: 10.1002/jbm.b.35260
Contributors: Dilek Sönmezer, Fatma Latifoğlu, Güler Toprak, Münevver Baran

 

Conclusion

Dr. Dilek Sönmezer Açıkgöz stands out as a highly qualified candidate for the Best Researcher Award, with substantial contributions to biomedical engineering, tissue engineering, and biomaterials. Her dedication to research, publications in top journals, and development of patented technology make her a strong contender. Strengthening international partnerships and focusing on high-impact translational research can further enhance her candidacy for future recognitions.

Jinxia Zhang | Defect detection | Best Researcher Award

Assoc Prof Dr. Jinxia Zhang | Defect detection | Best Researcher Award

 Associate Professor at Southeast University, China

Assoc Prof Dr. Jinxia Zhang is an Associate Professor at Southeast University, Nanjing, China, specializing in saliency detection, visual attention, computer vision, and deep learning. With a Ph.D. in Pattern Recognition and Intelligent Systems from Nanjing University of Science and Technology, he has extensive experience in artificial intelligence research. His journey includes time as a visiting scholar at Harvard Medical School and numerous prestigious research projects funded by national foundations. Assoc Prof Dr. Jinxia Zhang leads key AI initiatives, driving innovations in multimodal understanding, defect analysis, and object detection. His academic and professional contributions have positioned him as a prominent researcher in visual computing and AI.

Publication Profile

scholar

Education 🎓

Assoc Prof Dr. Jinxia Zhang  earned his M.Sc. and Ph.D. in Pattern Recognition and Intelligent Systems from Nanjing University of Science and Technology in 2015. His doctoral research laid a foundation for his interest in artificial intelligence, particularly in areas like visual attention and computer vision. Prior to his postgraduate work, he completed his B.Sc. in Computer Science and Technology at the same institution in 2009, where he developed a solid understanding of computational theories and applications. His education has provided him with both theoretical knowledge and practical skills that are central to his current research on AI and deep learning.Assoc Prof Dr. Jinxia Zhang  is currently an Associate Professor at Southeast University, Nanjing, a role he has held since 2019. From 2016 to 2019, he served as a Lecturer at the same university, where he significantly contributed to AI teaching and research. His early career included a prestigious stint as a Visiting Scholar at Harvard Medical School, USA, between 2012 and 2014, where he collaborated on cutting-edge AI-driven healthcare projects. His international exposure and academic roles have enriched his teaching and research, particularly in computer vision and AI, making him a key figure in the field.

Awards and Honors  🏆

Assoc Prof Dr. Jinxia Zhang  has received numerous accolades for his research excellence and contributions to the field of AI. He was awarded the National Natural Science Foundation of China grant in 2018 for his project on salient object detection. In 2017, he secured the Jiangsu Natural Science Foundation Grant for his innovative research on visual cognitive characteristics. Additionally, his work in defect diagnosis for photovoltaic modules was recognized as part of the National Key Research and Development Plan. These prestigious awards underscore his pioneering contributions in artificial intelligence and computer vision research.

Research Focus  🔬

Assoc Prof Dr. Jinxia Zhang ‘s research focuses on the intersection of visual attention, saliency detection, and deep learning within artificial intelligence. He leads projects on multimodal understanding and e-commerce applications, and is a Principal Investigator for research into AI-based fruit and vegetable recognition. His earlier work in defect diagnosis for photovoltaic modules and salient object detection in complex scenes has been supported by prominent grants. His innovative approach combines perceptual grouping and visual attention to develop cutting-edge solutions in computer vision, making significant advancements in how machines perceive and interact with visual data.

Conclusion

The candidate demonstrates an impressive body of work across several domains of artificial intelligence, particularly in salient object detection, visual cognition, and multimodal learning. Their academic achievements, project leadership, and dedication to advancing AI make them a strong contender for the Best Researcher Award. By continuing to broaden their industry collaborations and expanding the scope of their research impact, they can become a globally recognized leader in AI and computer vision.

Publication  Top Notes

  • Towards the Quantitative Evaluation of Visual Attention Models (2015)
    • Citation: 75
    • Journal: Vision Research
    • Key Contributors: Z. Bylinskii, E.M. DeGennaro, R. Rajalingham, H. Ruda, J. Zhang, J.K. Tsotsos
    • Highlights: Focuses on quantitative approaches to evaluate visual attention models, essential for improving saliency detection.
  • A Novel Graph-Based Optimization Framework for Salient Object Detection (2017)
    • Citation: 63
    • Journal: Pattern Recognition
    • Key Contributors: J. Zhang, K.A. Ehinger, H. Wei, K. Zhang, J. Yang
    • Highlights: Presents a new graph-based optimization method for enhancing the accuracy of salient object detection.
  • Salient Object Detection by Fusing Local and Global Contexts (2020)
    • Citation: 60
    • Journal: IEEE Transactions on Multimedia
    • Key Contributors: Q. Ren, S. Lu, J. Zhang, R. Hu
    • Highlights: This paper integrates both local and global visual contexts to refine salient object detection in multimedia applications.
  • Inter-Hour Direct Normal Irradiance Forecast with Multiple Data Types and Time-Series (2019)
    • Citation: 36
    • Journal: Journal of Modern Power Systems and Clean Energy
    • Key Contributors: T. Zhu, H. Zhou, H. Wei, X. Zhao, K. Zhang, J. Zhang
    • Highlights: Introduces a time-series forecasting model for direct normal irradiance, benefiting renewable energy systems.
  • Winter is Coming: How Humans Forage in a Temporally Structured Environment (2015)
    • Citation: 35
    • Journal: Journal of Vision
    • Key Contributors: D. Fougnie, S.M. Cormiea, J. Zhang, G.A. Alvarez, J.M. Wolfe
    • Highlights: Examines human visual foraging behavior in dynamically changing environments.
  • Domain Adaptation for Epileptic EEG Classification Using Adversarial Learning and Riemannian Manifold (2022)
    • Citation: 25
    • Journal: Biomedical Signal Processing and Control
    • Key Contributors: P. Peng, L. Xie, K. Zhang, J. Zhang, L. Yang, H. Wei
    • Highlights: This paper explores domain adaptation techniques to improve epileptic EEG classification through adversarial learning.
  • A Lightweight Network for Photovoltaic Cell Defect Detection in Electroluminescence Images (2024)
    • Citation: 23
    • Journal: Applied Energy
    • Key Contributors: J. Zhang, X. Chen, H. Wei, K. Zhang
    • Highlights: Develops a lightweight neural network for detecting defects in photovoltaic cells using knowledge distillation.
  • Salient Object Detection via Deformed Smoothness Constraint (2018)
    • Citation: 21
    • Journal: IEEE International Conference on Image Processing (ICIP)
    • Key Contributors: X. Wu, X. Ma, J. Zhang, A. Wang, Z. Jin
    • Highlights: Proposes a deformed smoothness constraint approach for improving salient object detection.
  • Character Recognition via a Compact Convolutional Neural Network (2017)
    • Citation: 20
    • Conference: International Conference on Digital Image Computing
    • Key Contributors: H. Zhao, Y. Hu, J. Zhang
    • Highlights: Develops a compact CNN for robust character recognition in natural scene images.
  • A Prior-Based Graph for Salient Object Detection (2014)
    • Citation: 23
    • Conference: IEEE International Conference on Image Processing (ICIP)
    • Key Contributors: J. Zhang, K.A. Ehinger, J. Ding, J. Yang
    • Highlights: Uses a prior-based graph model to enhance the performance of salient object detection algorithms.

Zhenghui Luo | organic solar cells | Best Researcher Award

Assoc Prof Dr. Shenzhen University, China

Dr. Luo Zhenghui, born in October 1991 in Wuhan, Hubei Province, is an Associate Professor at Shenzhen University, specializing in organic optoelectronic functional materials. He completed his PhD in Organic Chemistry at Wuhan University under the supervision of Professor Yang Chuluo, with joint training at the Institute of Chemistry, Chinese Academy of Sciences. Dr. Luo has published over 100 SCI papers, with 26 recognized as ESI Highly Cited Papers. His research focuses on the design and synthesis of non-fullerene acceptor materials and organic photovoltaic devices. He has received multiple awards, including recognition as a Clarivate Analytics Highly Cited Scientist.

 

Professional Profiles:

Education:

PhD in Organic Optoelectronic Functional Materials, Wuhan UniversitySupervisor: Professor Yang ChuluoJoint Training: Institute of Chemistry, Chinese Academy of Sciences (Academician Li Yongfang)Research Direction: Design, synthesis, and photovoltaic device research of non-fullerene acceptor materials

Research Focus:

Organic photovoltaic materials and devicesPreparation and optimization of organic photovoltaic devicesDesign and synthesis of non-fullerene acceptor materials

Key Achievements:

Published over 100 SCI papers since May 2016.26 papers selected as ESI Highly Cited Papers and 26 as ESI Hot Topics.Total citations exceed 8,000 (H-index: 51 on Google Scholar).First author or corresponding author on 54 papers, including top journals like Joule, Advanced Materials, Angewandte Chemie International Edition, and Energy & Environmental Science.Awarded for outstanding research contributions, including the 2020 Cell Press Chinese Scientist Best Paper Award in Material Science and selection as a Clarivate Analytics Highly Cited Scientist for multiple years.

Awards:

Top 2% of the world’s top scientists in Environment, Energy, and Sustainability journals for three consecutive years (2021-2023).Second prize winner in Guangdong Province and Shenzhen City Natural Science Award in 2022.

Strengths for the Award

1. Exceptional Publication Record: Luo Zhenghui has published over 100 SCI papers since May 2016, with 26 being selected as ESI Highly Cited Papers and 26 as ESI Hot Topics. His research output demonstrates both quality and impact, with a Google Scholar H-index of 51 and over 8,000 citations. His work in high-impact journals such as Advanced Materials, Angewandte Chemie, Joule, and Nature Communications underscores his contributions to the field of organic optoelectronic functional materials.

2. Expertise in Organic Photovoltaic Materials: Luo’s research focuses on organic photovoltaic materials and devices, particularly the design, synthesis, and application of non-fullerene acceptor materials. His innovative work in this area has led to significant advancements, including the development of polymer solar cells with efficiencies exceeding 17%. His expertise in molecular design and device engineering is evident in his numerous high-impact publications.

3. Recognition and Awards: Luo has received several prestigious awards, including the Cell Press Chinese Scientist Best Paper Award (First Place in Material Science) and the Outstanding Paper Award from Science China Chemistry. His recognition as a Clarivate Analytics Highly Cited Scientist and inclusion in the top 2% of the world’s top scientists further solidifies his standing in the scientific community.

4. Collaborative and Interdisciplinary Research: Luo has successfully collaborated with leading researchers and institutions, including joint training with the Institute of Chemistry, Chinese Academy of Sciences, and research at the Hong Kong University of Science and Technology. His interdisciplinary approach has contributed to his success in advancing organic optoelectronics and photovoltaic research.

Areas for Improvement

1. Diversification of Research Focus: While Luo’s focus on organic photovoltaic materials has yielded significant results, diversifying his research portfolio could enhance his contributions to other emerging areas within organic optoelectronics. Expanding into related fields such as organic light-emitting diodes (OLEDs) or organic semiconductors could further strengthen his overall research impact.

2. Increased Industry Collaboration: To translate his research into practical applications, Luo could benefit from increased collaboration with industry partners. Engaging in technology transfer and commercialization efforts could amplify the societal impact of his research, particularly in the development and deployment of organic photovoltaic technologies.

3. Outreach and Mentorship: Luo could consider increasing his involvement in outreach and mentorship activities. Guiding the next generation of researchers and actively participating in scientific outreach could enhance his visibility and influence within the broader scientific community.

 

✍️Publications Top Note :

Fine-tuning energy levels via asymmetric end groups – This paper reports on polymer solar cells achieving efficiencies over 17% through the fine-tuning of energy levels using asymmetric end groups. Published in Joule in 2020, it has been cited 367 times.

Improving open-circuit voltage by a chlorinated polymer donor – This study demonstrates how a chlorinated polymer donor can improve the efficiency of binary organic solar cells to over 17%. Published in Science China Chemistry in 2020, with 328 citations.

A layer-by-layer architecture for printable organic solar cells – This research addresses the challenge of module efficiency in organic solar cells by using a layer-by-layer architecture. It was published in Joule in 2020 and has 317 citations.

Precisely controlling the position of bromine on the end group – This work explores how the precise positioning of bromine on polymer acceptors can lead to solar cells with efficiencies over 15%. It was published in Advanced Materials in 2020 and has been cited 311 times.

Fine-tuning molecular packing and energy level through methyl substitution – This paper focuses on methyl substitution for fine-tuning molecular packing, leading to efficient nonfullerene polymer solar cells. Published in Advanced Materials in 2018, it has 292 citations.

Use of two structurally similar small molecular acceptors – The study shows how using two structurally similar acceptors can enable high-efficiency ternary organic solar cells. Published in Energy & Environmental Science in 2018, it has 280 citations.

Asymmetrical ladder-type donor-induced polar small molecule acceptor – This research promotes fill factors approaching 77% in high-performance nonfullerene polymer solar cells. Published in Advanced Materials in 2018, it has 273 citations.

16% efficiency all-polymer organic solar cells – The paper reports on achieving a 16% efficiency in all-polymer organic solar cells via a finely tuned morphology. Published in Joule in 2021, with 243 citations.

Simultaneous enhanced efficiency and thermal stability – This work demonstrates enhanced efficiency and thermal stability in organic solar cells using a polymer acceptor additive. Published in Nature Communications in 2020, it has 239 citations.

A nonfullerene acceptor with a 1000 nm absorption edge – This study discusses the development of a nonfullerene acceptor leading to improved efficiencies in organic solar cells. Published in Energy & Environmental Science in 2019, with 229 citations.

Conclusion

Luo Zhenghui is an outstanding candidate for the Best Researcher Award, with a proven track record of high-impact research, numerous accolades, and significant contributions to the field of organic optoelectronic functional materials. His expertise in organic photovoltaic materials, coupled with his collaborative and interdisciplinary approach, positions him as a leader in his field. While there is potential for further growth in diversifying his research focus and increasing industry collaboration, Luo’s achievements to date make him a highly deserving recipient of this prestigious award.