Zhe Zhang | Deep Learning for Computer Vision | Best Researcher Award

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Dr. Zhe Zhang | Deep Learning for Computer Vision | Best Researcher Award

Lecturer at Henan University of Engineering, China

Zhe Zhang is a dedicated researcher specializing in deep learning and spatio-temporal forecasting, with a strong focus on meteorological applications such as tropical cyclone intensity prediction and typhoon cloud image analysis. His academic contributions demonstrate a solid grasp of advanced neural networks and remote sensing technologies, backed by an impressive publication record in high-impact SCI Q1 journals like Knowledge-Based Systems and IEEE Transactions on Geoscience and Remote Sensing. Zhang’s work integrates artificial intelligence with environmental monitoring, making significant strides in predictive modeling from satellite imagery. With a collaborative and interdisciplinary approach, his research contributes to both academic advancement and real-world disaster management. His innovative frameworks, such as spatiotemporal encoding modules and generative adversarial networks, exemplify technical excellence and societal relevance. Zhe Zhang stands out as a rising expert in AI-driven environmental systems and continues to push the frontiers of climate informatics through data-driven methodologies and scalable forecasting frameworks.

Professional Profile 

Education🎓 

Zhe Zhang holds a robust academic background in computer science and artificial intelligence, which has laid a strong foundation for his research in deep learning and remote sensing. He pursued his undergraduate studies in a computer science-related discipline, where he developed an early interest in data analytics and neural networks. Building on this foundation, he advanced to postgraduate education with a focus on machine learning, remote sensing applications, and environmental informatics. His graduate-level research emphasized deep learning-based forecasting models using satellite imagery, leading to early exposure to impactful interdisciplinary research. Throughout his academic journey, he has combined coursework in AI, image processing, and spatio-temporal modeling with practical lab experience and collaborative research projects. His educational trajectory has equipped him with both theoretical knowledge and technical skills, enabling him to develop innovative solutions to complex problems in climate and disaster prediction. Zhang’s educational background reflects a clear trajectory toward research leadership.

Professional Experience📝

Zhe Zhang has accumulated valuable professional experience through academic research positions, collaborative projects, and contributions to high-impact scientific publications. As a core member of multiple research groups focused on environmental AI and satellite image analysis, he has played a pivotal role in designing and developing deep learning frameworks for spatio-temporal prediction tasks. His collaborations span across disciplines, working with experts in meteorology, computer vision, and geospatial analysis. Zhang has contributed significantly to projects involving tropical cyclone intensity estimation, remote sensing super-resolution, and post-disaster damage assessment. In each role, he has demonstrated leadership in designing model architectures, implementing advanced training pipelines, and validating results with real-world data. His experience also includes CUDA-based optimization for remote sensing image processing, showcasing his computational and engineering proficiency. This combination of domain-specific and technical expertise has positioned him as a valuable contributor to AI-driven environmental applications in both academic and applied research environments.

Research Interest🔎

Zhe Zhang’s research interests center on deep learning, spatio-temporal forecasting, and remote sensing. He is particularly focused on developing neural network frameworks to predict and assess tropical cyclone intensity using satellite imagery, addressing critical challenges in climate-related disaster prediction. Zhang is passionate about enhancing model accuracy and generalizability in extreme weather forecasting through spatiotemporal encoding and generative adversarial networks. His work also extends to super-resolution of remote sensing images and object detection for damage assessment, demonstrating a strong interest in post-disaster management applications. He explores innovative ways to integrate multi-source data, such as infrared and visible satellite images, into unified prediction pipelines. Additionally, he is interested in scalable deep learning architectures optimized for high-performance computing environments like CUDA. Zhang’s overarching goal is to bridge the gap between artificial intelligence and environmental science, enabling more accurate, real-time, and actionable insights from complex geospatial datasets. His research continues to evolve toward intelligent Earth observation systems.

Award and Honor🏆

Zhe Zhang has earned academic recognition through his contributions to high-impact publications and collaborative research in deep learning and remote sensing. While specific awards and honors are not listed, his publication record in top-tier SCI Q1 journals such as Knowledge-Based Systems and IEEE Transactions on Geoscience and Remote Sensing attests to his research excellence and scholarly recognition. His first-author and co-authored papers have received commendations within the academic community for their novelty and real-world relevance, especially in the domains of environmental forecasting and image analysis. Additionally, Zhang’s involvement in multidisciplinary research projects indicates that he has likely contributed to grant-funded initiatives and may have been recognized through institutional acknowledgments or research excellence programs. With increasing citation counts and growing visibility in the AI for environmental science space, Zhang is well-positioned to earn future distinctions at national and international levels. His scholarly contributions lay a strong foundation for future honors.

Research Skill🔬

Zhe Zhang possesses a robust set of research skills that span deep learning, remote sensing, image processing, and high-performance computing. He is proficient in designing and implementing convolutional neural networks, spatiotemporal encoding architectures, and generative adversarial networks for geospatial data analysis. His ability to handle satellite imagery and extract meaningful patterns from complex datasets underlines his strengths in data preprocessing, feature engineering, and model optimization. Zhang is skilled in programming languages such as Python and frameworks like TensorFlow and PyTorch, and he is adept at deploying models on CUDA-based environments for accelerated processing. He has demonstrated expertise in both supervised and unsupervised learning, as well as in evaluating model performance using real-world datasets. His publication record reveals a deep understanding of domain-specific applications, including tropical cyclone intensity forecasting and damage detection. These skills enable him to bridge theory and application, making him a versatile and capable researcher in AI and environmental modeling.

Conclusion💡

Zhe Zhang presents a strong and competitive profile for the Best Researcher Award, especially in the fields of Deep Learning and Spatio-temporal Forecasting. The research is:

  • Technically sound (deep learning architectures),

  • Application-driven (cyclone prediction, disaster response),

  • And academically visible (SCI Q1 journal publications).

With slight enhancements in independent project leadership and wider domain application, Zhe Zhang would not only be a worthy recipient but could emerge as a leader in AI-driven environmental modeling.

Publications Top Noted✍

  • Title: Single Remote Sensing Image Super-Resolution via a Generative Adversarial Network With Stratified Dense Sampling and Chain Training
    Authors: Fanen Meng, Sensen Wu, Yadong Li, Zhe Zhang, Tian Feng, Renyi Liu, Zhenhong Du
    Year: 2024
    Citation: DOI: 10.1109/TGRS.2023.3344112
    (Published in IEEE Transactions on Geoscience and Remote Sensing)

  • Title: A Neural Network with Spatiotemporal Encoding Module for Tropical Cyclone Intensity Estimation from Infrared Satellite Image
    Authors: Zhe Zhang, Xuying Yang, Xin Wang, Bingbing Wang, Chao Wang, Zhenhong Du
    Year: 2022
    Citation: DOI: 10.1016/j.knosys.2022.110005
    (Published in Knowledge-Based Systems)

  • Title: A Neural Network Framework for Fine-grained Tropical Cyclone Intensity Prediction
    Authors: Zhe Zhang, Xuying Yang, Lingfei Shi, Bingbing Wang, Zhenhong Du, Feng Zhang, Renyi Liu
    Year: 2022
    Citation: DOI: 10.1016/j.knosys.2022.108195
    (Published in Knowledge-Based Systems)

Dibyalekha Nayak | Computer vision | Women Researcher Award

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Dr . Dibyalekha Nayak | Computer vision | Women Researcher Award

Assistant professor at Shah and Anchor Kutchhi Engineering College, India

Dr. Dibyalekha Nayak is a dedicated academician and emerging researcher with deep expertise in image processing, adaptive compression, and VLSI design. Her professional journey is marked by a strong commitment to teaching, scholarly research, and technological advancement. With over a decade of teaching experience and a recently completed Ph.D. from KIIT University, Bhubaneswar, her research has produced several publications in SCI-indexed journals and international conferences. Dr. Nayak’s contributions reflect an interdisciplinary approach, combining deep learning techniques with low-power hardware design to address complex challenges in wireless sensor networks and multimedia systems. She has actively participated in faculty development programs and technical workshops, continuously upgrading her knowledge. Her professional philosophy emphasizes ethics, hard work, and continuous learning. Currently serving as an Assistant Professor at Shah and Anchor Kutchi Engineering College in Mumbai, she aspires to make impactful contributions to the field of electronics and communication through research, innovation, and collaboration.

Professional Profile 

Education🎓

Dr. Dibyalekha Nayak holds a Ph.D. in Image Processing from the School of Electronics at KIIT University, Bhubaneswar, where she completed her research between September 2018 and May 2024. Her doctoral work focused on advanced techniques in image compression and saliency detection using deep learning and compressive sensing. She completed her Master of Technology (M.Tech) in VLSI Design from Satyabhama University, Chennai, in 2011, graduating with a commendable CGPA of 8.33. Prior to that, she earned her Bachelor of Engineering (B.E.) in Electronics and Telecommunication from Biju Patnaik University of Technology (BPUT), Odisha, in 2008, with a CGPA of 6.5. Her academic background provides a strong foundation in both theoretical electronics and practical applications in image processing and circuit design. The combination of image processing and VLSI design throughout her academic journey has enabled her to engage in cross-disciplinary research and foster innovation in both hardware and software domains.

Professional Experience📝

Dr. Dibyalekha Nayak has accumulated over 12 years of rich academic experience in various reputed engineering institutions across India. Currently, she serves as an Assistant Professor at Shah and Anchor Kutchi Engineering College, Mumbai, affiliated with Mumbai University, where she joined in July 2024. Prior to this, she worked as a Research Scholar at KIIT University (2018–2024), contributing significantly to image processing research. Her earlier roles include Assistant Professor positions at institutions such as College of Engineering Bhubaneswar (2016–2018), SIES Graduate School of Technology, Mumbai (2014), St. Francis Institute of Technology, Mumbai (2013), and Madha Engineering College, Chennai (2011–2012). Across these roles, she has taught a variety of undergraduate and postgraduate courses, supervised student projects, and contributed to departmental development. Her teaching areas span digital electronics, VLSI design, image processing, and communication systems, demonstrating a strong alignment between her teaching and research activities.

Research Interest🔎

Dr. Dibyalekha Nayak’s research interests lie at the intersection of image processing, deep learning, and VLSI design, with a special focus on adaptive compression, saliency detection, and compressive sensing. Her doctoral research addressed the development of innovative, low-complexity algorithms for image compression using techniques like block truncation coding and DCT, tailored for wireless sensor network applications. She is also deeply interested in integrating deep learning frameworks into image enhancement and compression tasks to improve performance in real-world environments. Additionally, her background in VLSI design supports her interest in low-power hardware architectures for efficient implementation of image processing algorithms. Dr. Nayak is particularly motivated by research problems that bridge the gap between theoretical innovation and practical implementation, especially in the fields of embedded systems and multimedia communication. Her interdisciplinary research aims to create scalable, energy-efficient, and intelligent solutions for future communication and sensing technologies.

Award and Honor🏆

While Dr. Dibyalekha Nayak’s profile does not explicitly mention formal awards or honors, her scholarly achievements speak volumes about her academic excellence and dedication. She has published multiple research articles in prestigious SCI and Web of Science indexed journals such as Multimedia Tools and Applications, Mathematics, and Computers, reflecting the quality and impact of her research. She has been actively involved in reputed international conferences including IEEE and Springer Lecture Notes, where she has presented and published her research findings. Her work on saliency-based image compression and fuzzy rule-based adaptive block compressive sensing has received commendation for its innovation and applicability. Furthermore, her selection and sustained work as a Research Scholar at KIIT University for over five years highlights the recognition she has earned within academic circles. Her consistent participation in technical workshops, faculty development programs, and collaborations also demonstrate her growing reputation and standing in the field of electronics and image processing.

Research Skill🔬

Dr. Dibyalekha Nayak possesses a versatile and robust set of research skills aligned with modern-day challenges in image processing and electronics. She is proficient in developing image compression algorithms, saliency detection models, and adaptive techniques using block truncation coding, fuzzy logic, and DCT-based quantization. Her technical expertise extends to deep learning architectures tailored for image enhancement and compressive sensing in wireless sensor networks. Additionally, she has a strong command of VLSI design methodologies, enabling her to work on low-power circuit design and hardware implementation strategies. Dr. Nayak is also skilled in scientific programming, using tools such as MATLAB and Python, along with LaTeX for research documentation. She has a clear understanding of research methodologies, simulation frameworks, and performance analysis metrics. Her experience in preparing manuscripts for SCI-indexed journals and conference presentations showcases her technical writing abilities. Overall, her analytical mindset and hands-on skills make her a competent and impactful researcher.

Conclusion💡

Dr. Dibyalekha Nayak is a highly dedicated and emerging researcher in the fields of Image Processing, Deep Learning, and VLSI. Her academic journey reflects perseverance, scholarly depth, and a clear focus on impactful research. Her SCI-indexed publications, teaching experience, and cross-domain knowledge make her a deserving candidate for the Best Researcher Award.

Publications Top Noted✍

  • Title: Fuzzy Rule Based Adaptive Block Compressive Sensing for WSN Application
    Authors: D. Nayak, K. Ray, T. Kar, S.N. Mohanty
    Journal: Mathematics, Volume 11, Issue 7, Article 1660
    Year: 2023
    Citations: 6

  • Title: A novel saliency based image compression algorithm using low complexity block truncation coding
    Authors: D. Nayak, K.B. Ray, T. Kar, C. Kwan
    Journal: Multimedia Tools and Applications, Volume 82, Issue 30, Pages 47367–47385
    Year: 2023
    Citations: 4

  • Title: Walsh–Hadamard Kernel Feature-Based Image Compression Using DCT with Bi-Level Quantization
    Authors: D. Nayak, K. Ray, T. Kar, C. Kwan
    Journal: Computers, Volume 11, Issue 7, Article 110
    Year: 2022
    Citations: 3

  • Title: Sparsity based Adaptive BCS color image compression for IoT and WSN Application
    Authors: D. Nayak, T. Kar, K. Ray
    Journal: Signal, Image and Video Processing, Volume 19, Issue 8, Pages 1–7
    Year: 2025

  • Title: Hybrid Image Compression Using DCT and Autoencoder
    Authors: D. Nayak, T. Kar, K. Ray, J.V.R. Ravindra, S.N. Mohanty
    Conference: 2024 IEEE Pune Section International Conference (PuneCon), Pages 1–6
    Year: 2024

  • Title: Performance Comparison of Different CS based Reconstruction Methods for WSN Application
    Authors: D. Nayak, K.B. Ray, T. Kar
    Conference: 2021 IEEE 2nd International Conference on Applied Electromagnetics, Signal Processing, & Communication (AESPC)
    Year: 2021

  • Title: A Comparative Analysis of BTC Variants
    Authors: D. Nayak, K.B. Ray, T. Kar
    Conference: Proceedings of International Conference on Communication, Circuits, and Systems (LNEE, Springer)
    Year: 2021

  • Title: Low Power Error Detector Design by using Low Power Flip Flops Logic
    Authors: D. Chaini, P. Malgi, S. Lopes
    Journal: International Journal of Computer Applications, ISSN 0975-8887
    Year: 2014

Ms. Xiaotian Zhou | Large-Scale Vision | Best Researcher Award

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Ms. Xiaotian Zhou | Large-Scale Vision | Best Researcher Award

Zhejiang University of Science and Technology, China

👨‍🎓 Profiles

Orcid

Publications

Research on the Upgrading of University Library Platform Service from the Perspective of Digitalization

  • Author: Xiaotian Zhou
    Journal: International Journal of Educational Development
    Year: 2025

Research on the Construction of Cultural Landscape in University Libraries from the Perspective of Communication Studies

  • Author: Xiaotian Zhou
    Journal: Designs
    Year: 2022

Research on the Application of Agenda Setting Theory in University Libraries: A Case Study of Zhejiang University of Science and Technology Library

  • Author: Xiaotian Zhou
    Journal: Journal of Wuzhou University
    Year: 2022

Prof. Aasma Shaukat | Applications of Computer Vision | Best Paper Award

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Prof. Aasma Shaukat | Applications of Computer Vision | Best Paper Award

Professor at New York University, United States

Profiles

Scopus

Google Scholar

Education

Dr. Shaukat completed her F.Sc Pre-Medical at Kinnaird College for Women, Lahore in 1993. She earned her M.B., B.S. in Medicine from The Aga Khan University Medical College, Karachi in 1998. Her postgraduate studies include an MPH in International Health and Epidemiology from Johns Hopkins School of Public Health (2000), an Internship in Internal Medicine at State University of New York School of Medicine and Biomedical Sciences (2001), a Residency in Internal Medicine at the same institution (2003), and a Fellowship in Gastroenterology from Emory University School of Medicine (2007).

Current Appointments and Leadership Positions

Dr. Aasma Shaukat is the Program Director of KL2 at CTSI NYU (since January 2024). She has been serving as the Director of GI Outcomes Research and the Robert M. and Mary H. Glickman Endowed Professor of Medicine at NYU School of Medicine since July 2021. Additionally, she is a Professor of Population Health and Co-Director of the TREC Program at CTSI. She also holds a position as a Staff Physician at NY Harbor VA, New York and is an Adjunct Professor at the University of Minnesota School of Public Health (since May 2018).

Awards and Honors

Among her numerous accolades, Dr. Shaukat was selected for the AGA Executive Women Leadership workshop in Denver (2023) and received the ACG Colon Cancer Prevention Abstract Award in Vancouver (2023). She has been honored with the American College of Gastroenterology Governor’s Award for Excellence in Clinical Research (2020) and the AGA Young Investigator Award (2016). Other notable awards include the Champion of Colorectal Cancer Prevention Award (2014) and multiple Teacher of the Year Awards from the University of Minnesota Medical School.

Memberships and Professional Organizations

Dr. Shaukat is a Member of the Board of Trustees at the American College of Gastroenterology and the Chair Elect of the Clinical Practice Section at the American Gastroenterology Association Institute. She is also a Board Member of GIQUIC and serves on the Advisory Panel of PCORI. Her involvement includes being a Member of the DEI Committee at ASCI, Chair of the GI Field Advisory Board at VHA, and a Member of the US Multi-Society Task Force on Colon Cancer.

Research Activity

Dr. Shaukat’s research is centered around clinical, epidemiological, and translational studies focusing on colorectal cancer screening, quality indicators for colonoscopy, molecular markers of post-colonoscopy colon cancer, and chemoprevention. She is currently leading comparative effectiveness trials, including studies on fecal microbiota transplants for recurrent C. difficile infection and evaluating screening modalities to enhance colorectal cancer screening programs, especially in reducing disparities. Her expertise extends to systematic review and evidence synthesis.

Clinical Activity

Dr. Shaukat dedicates 35% of her time to endoscopy and outpatient GI clinic work, focusing on gastrointestinal (GI) cancers, both hereditary and sporadic. She has a special interest in quality indicators and the development of tools and techniques to enhance colonoscopy outcomes.

Mentoring Activity

As a dedicated mentor, Dr. Shaukat serves as Co-Director of NYU CTSI’s Training Education Research and Careers Core, overseeing educational and training initiatives across NYU. She also directs the KL2 program, mentoring KL2 scholars and K awardees to achieve independent funding. Dr. Shaukat’s mentorship extends across various roles, including primary mentoring responsibilities for junior faculty, colorectal surgery, and gastroenterology fellows. Her commitment to mentorship is reflected in her publications, where she has co-authored numerous papers with her mentees, many of whom have progressed to prominent positions in the medical field.

Teaching Activities

Dr. Shaukat plays a significant role in teaching and curriculum development. She co-directs the K to R Scholars Program at NYU and has been involved in teaching colon cancer topics to second-year medical students. Her past roles include serving as Site Director for trainee rotations at the VA Medical Center in Minneapolis, MN, and developing curriculum and journal club lectures for GI fellows.

Continuing Medical Education

Dr. Shaukat has been actively involved in continuing medical education, serving as Course Director for various ASGE and American College of Gastroenterology postgraduate courses. Her contributions to medical education extend to her role as faculty for regional conferences and her involvement in educational affairs and peer review committees.

 

Publications

Effect of ginger supplementation on the fecal microbiome in subjects with prior colorectal adenoma

  • Authors: Prakash, A., Rubin, N., Staley, C., Church, T.R., Prizment, A.
  • Journal: Scientific Reports
  • Year: 2024

Adenomas and Sessile Serrated Lesions in 45- to 49-Year-Old Individuals Undergoing Colonoscopy: A Systematic Review and Meta-Analysis

  • Authors: Abdallah, M., Mohamed, M.F.H., Abdalla, A.O., Bilal, M., Shaukat, A.
  • Journal: American Journal of Gastroenterology
  • Year: 2024

Incidence of lymph node metastases in colon cancer: does primary tumor location matter?

  • Authors: Weaver, L., Mott, S.L., Thatipelli, S., Shaukat, A., Goffredo, P.
  • Journal: Journal of Gastrointestinal Surgery
  • Year: 2024

Multilevel Interventions to Improve Colorectal Cancer Screening in an Urban Native American Community: A Pilot Randomized Clinical Trial

  • Authors: Shaukat, A., Wolf, J., Rudser, K., Wisdom, J.P., Church, T.R.
  • Journal: Clinical Gastroenterology and Hepatology
  • Year: 2024

Prevalence of Sessile Serrated Lesions in Individuals With Positive Fecal Immunochemical Test Undergoing Colonoscopy: Results From a Large Nationwide Veterans Affairs Database

  • Authors: Wilson, N., Bilal, M., Westanmo, A., Gravely, A., Shaukat, A.
  • Journal: Gastroenterology
  • Year: 2024

Teerapol-Srichana-3D Computer Vision-Best Researcher Award

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Prof Dr. Teerapol-Srichana-3D Computer Vision-Best Researcher Award

Prince of Songkla University-Thailand

Author Profile

Early Academic Pursuits

Prof Dr. Teerapol Srichana embarked on his academic journey with a Bachelor's degree in Pharmacy from Prince of Songkla University (PSU), Thailand, graduating in 1989. His passion for pharmaceutical sciences led him to pursue further studies, obtaining a Master's degree in Pharmaceutical Technology from Ghent University, Belgium, in 1992. During this period, his research focused on the quality of spheres in spheronizer under the supervision of Prof. J.P. Remon. In 1998, he earned a Ph.D. in Pharmaceutics from King's College London, United Kingdom, delving into factors affecting the deposition of drugs and excipients following aerosolization of dry powders under the supervision of Prof. C. Marriott and Prof. G.P. Martin.

Professional Endeavors

Prof Dr. Srichana's post-doctoral experiences included significant contributions to drug and polymer synthesis at Hebrew University in Jerusalem, Israel, under Prof. A.J. Domb in 2005. Subsequently, in 2006, he engaged in liquid crystal research at the University of Minnesota, USA, working with Prof. T.S. Wiedmann. Over the years, he held various leadership roles at PSU, such as Director of the Drug Delivery System Excellence Center and Head of the Pharmaceutical Technology Department.

Teerapol Srichana, a luminary in the realm of 3D computer vision, has significantly shaped the landscape of modern technology. With a profound commitment to innovation and research, Srichana's work stands at the forefront of advancements in the field.

Contributions and Research Focus On 3D Computer Vision

Throughout his academic and professional journey, Dr. Srichana demonstrated a commitment to advancing pharmaceutical sciences. His research has particularly focused on dry powder inhalers, drug-carrier interactions, controlled drug delivery systems, and the development of novel formulations. Notable contributions include studies on drug deposition from dry powder inhalers in vitro, enantioselective-controlled delivery using molecularly imprinted polymers, and the evaluation of drug-carrier interactions in dry powder inhaler formulations.

Srichana's groundbreaking research spans a wide spectrum, from pioneering depth perception systems to trailblazing 3D image processing techniques. His invaluable contributions include innovations in spatial recognition, scene analysis, and stereoscopic vision research, earning him numerous accolades and awards.

Accolades and Recognition

Prof Dr. Srichana's research prowess has been recognized through a multitude of publications in reputable scientific journals. Noteworthy accolades include his directorship roles, such as leading the Drug Delivery System Research Center and the NANOTEC Center of Excellence at PSU. His dedication and contributions to the field have also earned him prestigious positions like the Dean of the Graduate School at PSU.

Impact and Influence

Prof Dr. Teerapol Srichana's influence extends beyond his academic and professional spheres. His research findings have contributed to advancements in drug delivery systems, impacting the pharmaceutical industry. Through teaching and mentorship, he has inspired countless students to pursue excellence in pharmaceutical sciences, fostering the next generation of researchers and professionals.

Legacy and Future Contributions

As a respected figure in pharmaceutics, Dr. Srichana leaves a lasting legacy of impactful research and academic leadership. His current role as the Head of the Pharmaceutical Technology Department at PSU reflects his ongoing commitment to shaping the future of pharmaceutical education and research. Dr. Srichana's legacy will undoubtedly continue through the students and researchers he has mentored and the knowledge he has imparted to the scientific community. Looking ahead, his future contributions are anticipated to further elevate the field of pharmaceutical sciences.

Citations

  • Citations   393
  • h-index       11
  • i10-index    13

Notable Publication