Shahzeb Khan | AI in Healthcare | Best Researcher Award

Published on by Innovation Technologist

Mr. Shahzeb Khan | AI in Healthcare | Best Researcher Award

Assistant professor at Sharda University, India

Shahzeb Khan šŸŽ“āœØ is a passionate Data Scientist and Assistant Professor with a flair for innovation and research. With expertise in AI, ML, and data science, he blends academic rigor with practical problem-solving skills. He has been recognized for his research excellence, including the prestigious Best Researcher Award (2024), and holds qualifications like GATE 2020 and UGC-NET 2023. Beyond his professional pursuits, Shahzeb enjoys reading, writing, cooking, solo traveling, swimming, and singing. šŸŒšŸ“–šŸŽ¤

Publication Profile :Ā 

Google Scholar

Educational Background šŸŽ“

Shahzeb Khan is a dedicated Data Scientist and educator with a strong background in information systems analysis, programming, teaching, and research. He earned his M.Tech in Computer Science from Mahatma Gandhi Central University, Bihar, in 2023 with an impressive 8.5 CGPA, after completing his B.Tech from AKTU Uttar Pradesh in 2020 with a 6.8 CGPA. Shahzeb demonstrated academic excellence from an early age, achieving 9.2 CGPA in matriculation (CBSE) in 2013 and 75% in his intermediate studies in 2015.

Professional Experience šŸ’¼

Shahzeb is currently serving as an Assistant Professor in Computer Science and Applications at Sharda University, Greater Noida, where he teaches Artificial Intelligence, Machine Learning, Big Data Analytics, Data Science, and Data Analytics (since September 2023). His professional journey also includes a web development internship at IIY Software Pvt. Ltd. in 2019 and key coordination roles, such as the TSML (Time Series Machine Learning) Summer Training Program at MGCUB in 2023. Shahzeb is actively involved in conducting workshops and seminars, including those at IIT Delhi, where he engaged in IoT and Machine Learning training.

Research Interests šŸ”¬

Shahzeb’s research interests lie at the intersection of Artificial Intelligence, Machine Learning, Deep Learning, and Statistical Modeling. He is particularly focused on predictive modeling, hybrid model development, and comparative analysis of advanced algorithms for time-series data. His notable work includes a publication on a novel Hybrid GRU-CNN model for PTB diagnostic ECG time series data in the Biomedical Signal Processing and Control journal, which boasts a 5.9 impact factor.

Publications šŸ“š

  1. Khan, S. (2024). A Novel Hybrid GRU-CNN and Residual Bias (RB) Based RB-GRU-CNN Models for Prediction of PTB Diagnostic ECG Time Series Data. Biomedical Signal Processing and Control, Impact Factor: 5.9.

 

 

Muhammad Ahsan Saleem | Additive Manufacturing | Best Researcher Award

Published on by Innovation Technologist

Mr. Muhammad Ahsan Saleem | Additive Manufacturing | Best Researcher Award

Ph.D. Student at Nanjing University of Science and Technology, China

Muhammad Ahsan Saleem is an innovative Mechatronics Engineer currently pursuing a Doctorate in Mechanical Engineering at Nanjing University of Science and Technology. With expertise in data-driven applications for 3D printing and machine learning, he works at the cutting edge of material science, electronics, and mechanical systems. Passionate about interdisciplinary collaboration, he applies his technical expertise to solving complex engineering challenges. His hands-on experience includes projects in servo motor control, smart applications, and multi-material 3D printing. Muhammad’s work contributes to significant advancements in the fields of automation, manufacturing, and functional electronics. šŸ› ļøšŸ”¬šŸ“

Publication Profile :Ā 

Scopus

Educational Background šŸŽ“

Muhammad Ahsan Saleem holds a Doctor of Engineering in Mechanical Engineering (ongoing, since 2020) from Nanjing University of Science and Technology, China. He completed his Master of Engineering in Mechanical Engineering in 2018 and his Bachelor of Science in Mechatronics Engineering in 2013, both from the same institution in Nanjing, China, and University of Engineering and Technology (UET) Taxila, Pakistan, respectively.

Professional Experience šŸ’¼

Currently, Muhammad is a Researcher at Nanjing University of Science and Technology (2020-present), where he collaborates on building plans, timelines, and proposal writing for product development in the fields of 3D printing, inkjet printing, and data-driven approaches for high-viscosity inks. His role involves experiment design for optimizing inkjet printing processes and the development of multi-material ink applications. Prior to this, he worked as a Mechatronics Engineer at Enginesound Automation Technology in Shanghai (2019), where he designed and implemented a Flexible Bend Control (FBC) device for textile machine calibration and developed an android app for wireless data transfer using Bluetooth. His work also includes performance analysis of electric motors and the design of test benches for comprehensive motor analysis. Earlier, he interned as a Trainee Engineer at Attock Refinery Limited, Pakistan, in 2015, working on HVAC equipment installation and maintenance.

Research Interests šŸ”¬

Muhammadā€™s research spans 3D printing, machine learning, and materials science, with particular focus on inkjet printing technology, piezoelectric inks, and multi-material composites. He explores data-driven methodologies to improve the precision of 3D-printed electronic circuits and has contributed to studies on the jetting behaviors of high-viscosity inks and functional electronics printing.

Publications šŸ“š

Rehman, A. U., Saleem, M. A., Liu, T., Pitir, F., & Salamci, M. U. (2022). Influence of Silicon Carbide on Direct Powder Bed Selective Laser Process (Sintering/Melting) of Alumina. Materials, 15(2), 637. https://doi.org/XXXXXX

Aslam, M. S., Qaisar, I., & Saleem, M. A. (2020). Quantized Event-triggered feedback control under fuzzy system with time-varying delay and actuator fault. Nonlinear Analysis: Hybrid Systems, 35, 100823. https://doi.org/XXXXXX

 

 

 

Kanneboina Ashok | Internet of Medical Things | Best Researcher Award

Published on by Innovation Technologist

Dr. Kanneboina Ashok | Internet of Medical Things | Best Researcher Award

Assistant professor at Mallareddy university, India

Dr. Kanneboina Ashok is an Assistant Professor at Mallareddy University, Hyderabad, where he applies his expertise in IoT and healthcare. With 9 publications, 1 book, and 2 patents, his research aims to improve healthcare systems using IoT technologies, focusing on efficiency, energy, and security. šŸŒšŸ“ššŸ’”

Publication Profile :Ā 

Scopus

Educational Background šŸŽ“

Dr. Kanneboina Ashok is an Assistant Professor at Mallareddy University, Hyderabad, specializing in the intersection of healthcare and technology. With a solid academic foundation, he has made significant contributions in the field of Remote Health Monitoring using the Internet of Medical Things (IoMT). He holds a wealth of research experience, having published 9 research papers in prestigious journals (SCI, Scopus) and authored a book currently under review. His research focuses on optimizing IoMT systems in healthcare to overcome challenges such as delays, energy inefficiencies, and security vulnerabilities, all while maintaining scalability. Dr. Ashok has filed one patent in 2023 and has another ready for publication.

Professional Experience šŸ’¼

Dr. Ashok has significant teaching and research experience in the field of engineering and healthcare technologies. His expertise extends beyond the classroom, having worked on several ongoing research projects that aim to revolutionize healthcare through the use of IoT. He collaborates with global researchers to address pressing challenges in healthcare technology. Dr. Ashok is dedicated to advancing the potential of IoT in healthcare systems for more efficient, real-time patient monitoring.

Research Interests šŸ”¬

  • Remote Health Monitoring
  • Internet of Medical Things (IoMT)
  • Healthcare System Optimization
  • IoT-based Security and Energy Efficiency in Healthcare

Publications šŸ“š

  1. Ashok, K., & Gopikrishnan, S. (2024). A hybrid secure signcryption algorithm for data security in an Internet of Medical Things environment. Journal of Information Security and Applications, 85, 103836. [Link Disabled]
  2. Kanneboina, A., & Sundaram, G. (2024). Improving security performance of the Internet of Medical Things using a hybrid metaheuristic model. Multimedia Tools and Applications. [Link Disabled]
  3. Ashok, K., & Gopikrishnan, S. (2024). Q-learning model for blockchain security in Internet of Medical Things networks. International Journal of Computer Networks and Communications, 16(1), 33ā€“50. [Link Disabled]
  4. Ashok, K., & Gopikrishnan, S. (2024). A framework provides authorized personnel with secure access to their electronic health records. In Lecture Notes in Networks and Systems (Vol. 894, pp. 137ā€“148). [Link Disabled]
  5. Ashok, K., & Gopikrishnan, S. (2023). Improving security performance of healthcare data in the Internet of Medical Things using a hybrid metaheuristic model. International Journal of Applied Mathematics and Computer Science, 33(4), 623ā€“636. [Open Access]
  6. Ashok, K., & Gopikrishnan, S. (2023). Statistical analysis of remote health monitoring-based IoT security models & deployments from a pragmatic perspective. IEEE Access, 11, 2621ā€“2651. [Open Access]

 

 

 

Anita Gehlot | Sustainable Development Goals | Women Researcher Award

Published on by Innovation Technologist

Prof. Dr. Anita Gehlot | Sustainable Development Goals | Women Researcher Award

Professor at Uttaranchal University, India

Dr. Anita is an experienced educator, researcher, and innovator with a strong background in electronics and communication engineering. She is highly regarded for her work in AI, IoT, and sensor networks, with over 350+ published papers and 47 granted patents. She has mentored multiple Ph.D. students, contributing to advancements in technology and innovation. Dr. Anita was also ranked 6th among Indiaā€™s top inventors (2010ā€“2020) by Clarivate Analytics in March 2021. With a passion for mentoring and innovation, she continues to inspire students and researchers to push the boundaries of technology. šŸŒŸšŸ“ššŸ’”šŸ”¬

Publication Profile :Ā 

Scopus

Orcid

Educational Background šŸŽ“

  • Ph.D. in Electronics Engineering, University of Petroleum and Energy Studies, Dehradun (2018)
    Thesis: Modelling, Optimization, and Implementation of Sensor Nodes for Authentication of Two-Wheeler Ignition
  • M.E. in Electronics & Communication Engineering, Panjab University, Chandigarh (2009)
    Title: Performance Analysis of Neural Network-Based Particle Swarm Optimization Algorithm for Wireless Sensor Networks
  • B.Tech in Electronics & Communication Engineering, Guru Jambheshwar University, Hisar (2005)

Professional Experience šŸ’¼

Dr. Anita has over 16 years of experience in academia, with a notable leadership role as Professor & Head of Research & Innovation at Uttaranchal University since 2021. She has previously held significant teaching and administrative roles at esteemed institutions such as Lovely Professional University, University of Petroleum and Energy Studies, and Baddi University. Her experience spans across assistant professor to lecturer roles, where she has contributed to the growth of engineering education and research. Dr. Anita has supervised numerous research projects and Ph.D. candidates, including topics in machine learning, IoT, and sensor networks.

Research Interests šŸ”¬

  • Embedded Systems
  • Artificial Intelligence (AI)
  • Machine Learning (ML)
  • Wireless Sensor Networks (WSN)
  • Automation
  • Internet of Things (IoT)

Dr. Anitaā€™s research primarily focuses on the modeling and optimization of sensor networks, machine learning applications, and IoT-based systems. She is particularly interested in AI algorithms, wireless communication, and smart technologies for real-time applications.

Publications šŸ“š

  • Vaish, K., Sharma, M., Kathuria, S., Akram, S.V., Malik, P.K. (2024). Leveraging wireless technology and IoT in developing a smart judiciary system with smart dust sensors. Intelligent Networks: Techniques, and Applications, 129ā€“151.
  • Tiwari, S., Gehlot, A., Singh, R., Twala, B., Priyadarshi, N. (2024). Design of an iterative method for disease prediction in finger millet leaves using graph networks, dyna networks, autoencoders, and recurrent neural networks. Results in Engineering, 24, 103301.
  • Swami, S., Singh, R., Gehlot, A., Kumar, D., Shah, S.K. (2024). Vision-based approach for human motion detection and smart appliance control. IAES International Journal of Robotics and Automation, 13(4), 445ā€“451.
  • Kumar, V., Singh, R., Gehlot, A., Priyadarshi, N., Twala, B. (2024). Various computational methods for highway health monitoring in terms of detection of black ice: a sustainable approach in Indian context. Discover Sustainability, 5(1), 245.
  • Bhatt, H., Bahuguna, R., Swami, S., Priyadarshi, N., Twala, B. (2024). Integrating industry 4.0 technologies for the administration of courts and justice dispensationā€”a systematic review. Humanities and Social Sciences Communications, 11(1), 1076.
  • Gopichand, G., Sarath, T., Dumka, A., Priyadarshi, N., Twala, B. (2024). Use of IoT sensor devices for efficient management of healthcare systems: a review. Discover Internet of Things, 4(1), 8.
  • Pachouri, V., Chandramauli, A., Singh, R., Priyadarshi, N., Twala, B. (2024). Removal of contaminants by chlorella species: an effort towards sustainable remediation. Discover Sustainability, 5(1), 19.
  • Krishna, G., Singh, R., Gehlot, A., Akram, S.V. (2024). An IoT-based predictive model for improved battery management system using advanced LSTM model. Journal of Energy Storage, 101, 113694.
  • Singh, R., Gehlot, A., Joshi, K. (2024). Revolutionizing health services: Industry 4.0 aligned systems for the future. In Advanced Technologies for Realizing Sustainable Development Goals: 5G, AI, Big Data, Blockchain, and Industry 4.0 Application (pp. 231ā€“237).
  • Singh, R., Gehlot, A., Joshi, K. (2024). The integration of robotics in advancing smart health echo systems. In Advanced Technologies for Realizing Sustainable Development Goals: 5G, AI, Big Data, Blockchain, and Industry 4.0 Application (pp. 238ā€“243).

 

 

Rajesh Singh | Engineering | Best Researcher Award

Published on by Innovation Technologist

Prof. Dr. Rajesh Singh | Engineering | Best Researcher Award

Professor at Uttaranchal University, India

Rajesh Singh, Ph.D., is an accomplished academician and researcher with over 20 years of experience in engineering and innovation. He currently serves as the Director of Research & Innovation at Uttaranchal University, as well as the Head of Innovation & Entrepreneurship at Lovely Professional University and Head of the Robotics Research Centre at the University of Petroleum & Energy Studies. Dr. Singh has been instrumental in driving various research and innovation initiatives, with notable accomplishments in the fields of Wireless Sensor Networks, Embedded Systems, Robotics, Artificial Intelligence, Machine Learning, Automation, IoT, and Raspberry Pi.

Publication Profile :Ā 

Scopus

Educational Background šŸŽ“

  • Ph.D. in Electronics Engineering from the University of Petroleum and Energy Studies, Dehradun (2016).
  • M.Tech in Electronics & Communication Engineering from Rajiv Gandhi Technical University (2009).
  • B.E. in Electronics & Communication Engineering from Dr. B.R Ambedkar University, Agra (2002).

Professional Experience šŸ’¼

Held various positions in academia, including Associate Professor, Assistant Professor, and Director, with a focus on innovation, research, and entrepreneurship across multiple institutions, including Uttaranchal University, Lovely Professional University, and University of Petroleum & Energy Studies.

Research Interests šŸ”¬

  • Wireless Sensor Networks
  • Embedded Systems
  • Robotics
  • Artificial Intelligence
  • Machine Learning
  • Internet of Things (IoT)
  • Automation

Awards & Recognition

  • Award of Excellence for Research and Innovation in Science, conferred by the State Minister of Uttarakhand, India
  • Recognized for significant contributions to innovation, technology, and academic excellence both nationally and internationally.

Publications šŸ“š

  • Title: Lumpy skin disease virus identification using image-based and deep learning approach
  • Authors: Sharma, S., Joshi, K., Singh, R., Sharma, G., Kumar, G.
  • Conference: Computational Methods in Science and Technology – Proceedings of the 4th International Conference on Computational Methods in Science and Technology, ICCMST 2024
  • Year: 2025
  • Volume: 2
  • Pages: 30ā€“35
  • Title: Leveraging wireless technology and IoT in developing a smart judiciary system with smart dust sensors
  • Authors: Vaish, K., Sharma, M., Kathuria, S., Akram, S.V., Malik, P.K.
  • Book: Intelligent Networks: Techniques, and Applications
  • Year: 2024
  • Pages: 129ā€“151
  • Title: Design of an iterative method for disease prediction in finger millet leaves using graph networks, dyna networks, autoencoders, and recurrent neural networks
  • Authors: Tiwari, S., Gehlot, A., Singh, R., Twala, B., Priyadarshi, N.
  • Journal: Results in Engineering
  • Year: 2024
  • Volume: 24
  • Article ID: 103301
  • Title: Vision-based approach for human motion detection and smart appliance control
  • Authors: Swami, S., Singh, R., Gehlot, A., Kumar, D., Shah, S.K.
  • Journal: IAES International Journal of Robotics and Automation
  • Year: 2024
  • Volume: 13(4)
  • Pages: 445ā€“451
  • Title: Various computational methods for highway health monitoring in terms of detection of black ice: a sustainable approach in Indian context
  • Authors: Kumar, V., Singh, R., Gehlot, A., Priyadarshi, N., Twala, B.
  • Journal: Discover Sustainability
  • Year: 2024
  • Volume: 5(1)
  • Article ID: 245
  • Title: The Image Classification Method for Eddy Current Inspection of Titanium Alloy Plate Based on Parallel Sparse Filtering and Deep Forest
  • Authors: Yidan, Z., Zou, H., Li, Z., Singh, R., Abbas, M.
  • Journal: Journal of Nondestructive Evaluation
  • Year: 2024
  • Volume: 43(4)
  • Article ID: 103
  • Title: Unleashing the power of advanced technologies for revolutionary medical imaging: pioneering the healthcare frontier with artificial intelligence
  • Authors: Chauhan, A.S., Singh, R., Priyadarshi, N., Suthar, S., Swami, S.
  • Journal: Discover Artificial Intelligence
  • Year: 2024
  • Volume: 4(1)
  • Article ID: 58
  • Title: Integrating industry 4.0 technologies for the administration of courts and justice dispensationā€”a systematic review
  • Authors: Bhatt, H., Bahuguna, R., Swami, S., Priyadarshi, N., Twala, B.
  • Journal: Humanities and Social Sciences Communications
  • Year: 2024
  • Volume: 11(1)
  • Article ID: 1076
  • Title: Use of IoT sensor devices for efficient management of healthcare systems: a review
  • Authors: Gopichand, G., Sarath, T., Dumka, A., Priyadarshi, N., Twala, B.
  • Journal: Discover Internet of Things
  • Year: 2024
  • Volume: 4(1)
  • Article ID: 8
  • Title: Detailed-based dictionary learning for low-light image enhancement using camera response model for industrial applications
  • Authors: Goyal, B., Dogra, A., Jalamneh, A., Singh, R., Jyoti Saikia, M.
  • Journal: Scientific Reports
  • Year: 2024
  • Volume: 14(1)
  • Article ID: 17122

 

 

 

Yi Gou | Medicinal Chemistry | Best Researcher Award

Published on by Innovation Technologist

Mr. Yi Gou | Medicinal Chemistry | Best Researcher Award

Associate Researcher at Guilin Medical University, China

Yi Gou is a distinguished researcher in anticancer drug chemistry with a strong academic background and a track record of innovation. He has authored over 40 SCI papers, with a significant number of first-author publications. His groundbreaking research has led to multiple patents and contributions to international scientific literature. Yi has also served as a guest editor for renowned journals such as Frontiers in Pharmacology and Drug Development Research. His expertise and research are recognized globally, contributing to advancements in cancer therapy.

Publication Profile :Ā 

Scopus

Educational Background šŸŽ“

Yi Gou earned a Ph.D. in Inorganic Chemistry in 2016. During his doctoral research, he specialized in the field of anticancer drug chemistry, laying the foundation for his subsequent work. His extensive education and training have provided him with a solid understanding of both inorganic chemistry and medicinal chemistry, particularly in designing and synthesizing anticancer small molecule agents. This expertise has guided his research in the development of novel drug candidates, and his academic achievements include numerous publications in high-impact journals.

Professional Experience šŸ’¼

Yi Gou is currently serving as an Associate Researcher at Guilin Medical University, where he continues his pioneering research on anticancer drug chemistry. His professional career includes both independent research projects and collaborative work, notably contributing to the National Natural Science Foundation of China (NSFC) projects. He has led one completed NSFC project (Project No. 22007023) and is actively conducting another (Project No. 22267004). In addition to his research, Yi Gou has also been recognized for his editorial contributions, serving as a guest editor for journals such as Frontiers in Pharmacology and Drug Development Research. Over the years, his work has resulted in numerous publications, patents, and positive evaluations in the international research community.

Research Interests šŸ”¬

Yiā€™s primary research focus is on the design and synthesis of small molecule anticancer agents, particularly those involving metal-based complexes. His work merges the fields of inorganic chemistry and medicinal chemistry, with a focus on developing novel therapeutics to combat cancer. Yi has received significant funding for his research, completing one National Natural Science Foundation of China project (Project No. 22007023) and currently leading another (Project No. 22267004). His work has led to eight Chinese invention patents and multiple collaborations, including research on metal-antitumor complexes based on traditional Chinese medicine components.

Key Achievements

šŸ”¬ Over 40 published SCI papers, with an h-index of 24
šŸ“œ 8 Chinese invention patents granted, 6 in the process of application
šŸ”— Collaborations with leading researchers and national projects
šŸŒ Recognized as a guest editor for prominent journals
šŸŽ“ Member of the Chinese Chemical Society

Publications šŸ“š

  • Li, A., Pan, W., Zhang, Z., Zhang, Y., & Ma, L. (2025). Hydrazone copper(II) complexes suppressed lung adenocarcinoma by activating multiple anticancer pathways. Bioorganic Chemistry, 154, 107994.
  • Li, A., Huang, K., Pan, W., Ma, L., & Gou, Y. (2024). Thiosemicarbazone mixed-valence Cu(I/II) complex against lung adenocarcinoma cells through multiple pathways involving cuproptosis. Journal of Medicinal Chemistry, 67(11), 9091ā€“9103.

  • Wu, Y., Wu, D., Lan, J., Xu, Y., & Gou, Y. (2024). Assessment of mononuclear/dinuclear copper acylhydrazone complexes for lung cancer treatment. Bioorganic Chemistry, 144, 107122.

  • Deng, J., Wu, Y., Li, A., Yang, F., & Gou, Y. (2023). Dithiocarbazate-Zn(II) complexes for photodynamic therapy and chemotherapy against lung cancer. Inorganic Chemistry Frontiers, 10(22), 6526ā€“6536.

  • Wu, Y., Hou, L., Lan, J., Liu, W., & Gou, Y. (2023). Mixed-ligand copper(II) hydrazone complexes: Synthesis, structure, and anti-lung cancer properties. Journal of Molecular Structure, 1279, 134986.
  • Gou, Y., Liu, L., & Liang, H. (2022). Editorial: The developments of metal-based agents against lung cancer. Frontiers in Pharmacology, 13, 1101890.
  • Chen, M., Chen, X., Huang, G., Gou, Y., & Deng, J. (2022). Synthesis, anti-tumour activity, and mechanism of benzoyl hydrazine Schiff base-copper complexes. Journal of Molecular Structure, 1268, 133730.
  • Deng, J., Peng, C., Hou, L., Huang, G., & Gou, Y. (2022). Dithiocarbazate-copper complex loaded thermosensitive hydrogel for lung cancer therapy via tumor in situ sustained-release. Inorganic Chemistry Frontiers, 9(23), 6190ā€“6201.
  • Guo, J., Li, A., Guo, R., Jin, J., & Huang, G. (2022). C1orf74 positively regulates the EGFR/AKT/mTORC1 signaling in lung adenocarcinoma cells. PeerJ, 10, e13908.
  • Gou, Y., Jia, X., Hou, L. X., Jiang, H. W., & Yang, F. (2022). Dithiocarbazate-Fe(III), -Co(III), -Ni(II), and -Zn(II) complexes: Design, synthesis, structure, and anticancer evaluation. Journal of Medicinal Chemistry, 65(9), 6677ā€“6689.

 

 

 

Ding Qi | Precancerous Cervical Lesions | Best Researcher Award

Published on by Innovation Technologist

Mrs. Ding Qi | Precancerous Cervical Lesions | Best Researcher Award

Physician at The Second Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, China

Ding Qi is a dedicated physician with extensive experience in natural medicine research. Currently working at The Second Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, her primary focus is on developing innovative natural treatments to block the progression of cervical precancerous lesions and improve the outcomes for female reproductive system cancers. With a strong background in oncology, Dr. Qi is committed to enhancing patient quality of life through natural therapies. Her pioneering work includes developing a new natural preparation for cervical precancerous lesions.

Publication Profile :Ā 

Scopus

Orcid

Educational Background šŸŽ“

Ding Qi has completed rigorous academic training in the medical field, obtaining a degree in medicine from a prestigious institution. Throughout their academic journey, they have specialized in fields related to traditional Chinese medicine and oncology, developing a deep understanding of medical research, clinical practices, and tumor-related treatments. This educational foundation has played a pivotal role in shaping their current focus on the development of new natural medicines for the treatment of female reproductive system tumors and precancerous lesions.

Professional Experience šŸ’¼

Ding Qi has extensive experience as a physician at The Second Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine. Over the years, Dr. Qi has focused on research into cervical precancerous lesions and their progression to cervical cancer, as well as the therapeutic potential of natural medicines in treating endometrial cancer. Their professional experience has also involved building animal models to study continuous cervical lesions, contributing to the field of reproductive system tumors. Dr. Qiā€™s work is deeply committed to advancing medical research and improving patient outcomes through innovative, natural therapeutic approaches.

Research Interests šŸ”¬

Qiā€™s research is focused on tumors of the female reproductive system, particularly how natural medicines can prevent the progression of precancerous lesions. Her recent work is centered around the therapeutic effects of natural medicines on endometrial cancer, and she is also developing an animal model for spontaneous cervical lesions. Her ultimate goal is to develop new treatments that improve patient outcomes and quality of life in the field of gynecological oncology.

Achievements šŸŒŸ

  • Ongoing Research: The therapeutic effect of natural medicines on endometrial cancer.
  • Patents: Animal model construction for spontaneous cervical continuous lesions.
  • Innovation: Developed a natural preparation to treat precancerous lesions of the cervix.

Publications šŸ“š

  • Han, B., Yuan, M., Gong, Y., Sun, Y., & Liu, L. (2023). The clinical course of untreated CIN2 (HPV16/18+) under active monitoring: A protocol of systematic reviews and meta-analysis. Medicine (United States), 102(6), e32855. https://doi.org/[DOI]
  • Qi, D., Li, H., Wang, S., Han, B., & Liu, L. (2022). Construction of ceRNA network and key gene screening in cervical squamous intraepithelial lesions. Medicine (United States), 101(48), E31928. https://doi.org/[DOI]

 

 

 

Dehong Gao | Artificial Intelligence | Outstanding Scientist Award

Published on by Innovation Technologist

Assoc. Prof. Dr. Dehong Gao | Artificial Intelligence | Outstanding Scientist Award

Associate Professor at Northwestern Polytechnical University, China

Dehong Gao is a distinguished expert in the fields of natural language processing, machine learning, and large language models. With over a decade of research and practical experience, he has made significant contributions to advertising technologies, multimodal AI models, and AI-driven e-commerce solutions. Gao currently leads groundbreaking work on multimodal pre-training models, including the award-winning 70B-FashionGPT model. As an associate professor at Northwestern Polytechnical University and a distinguished researcher at Zhejiang University of Technology, Gao continues to advance AI research, particularly in the areas of large language models, multimodal learning, and cross-lingual search. šŸš€šŸ“ššŸ’”

Publication Profile :Ā 

Scopus

Educational Background šŸŽ“

  • Ph.D. in Computer Science from Hong Kong Polytechnic University (2014-2022), under the supervision of Li Wenjie.
  • Master’s in Automation from Northwestern Polytechnical University (2010).
  • Bachelor’s in Automation from Northwestern Polytechnical University (2007).

Professional Experience šŸ’¼

Dehong Gaoā€™s career spans both academia and industry. He is currently an Associate Professor at the School of Cyberspace Security at Northwestern Polytechnical University. He also serves as a Distinguished Researcher at the Zhejiang University of Technology Artificial Intelligence Innovation Institute. Gao previously held the position of Senior Algorithm Expert (P8) at Alibaba Group, where he led a team of over 20 full-time algorithm engineers and contributed to the development of large-scale machine translation and AI-driven e-commerce solutions. As an expert in Alibaba AIR Project, Gao has been instrumental in technical breakthroughs related to large model technologies, fine-tuning multimodal models, and advancing AI-based search and advertising systems. šŸ’»šŸ“ˆ

Research Interests šŸ”¬

Gao’s research interests are focused on:

  • Large Language Models (LLMs) and Multimodal Learning šŸŒšŸ¤–
  • Natural Language Processing: Information retrieval, recommendation systems, sentiment analysis, and automated summarization šŸ“‘šŸ”
  • E-commerce AI: Developing search algorithms and multilingual representation learning for cross-border e-commerce applications šŸŒšŸ›’
  • Federated Learning and AI-driven personalization in business settings šŸ”’šŸ¤–

He has authored and co-authored several influential papers and has been a leading figure in the development of multimodal AI models for industries such as fashion, e-commerce, and healthcare. His work continues to push the boundaries of AI application in real-world environments. šŸ†šŸ“š

Publications šŸ“š

  1. Gao, D., Chen, K., Chen, B., et al. (2024). LLMs-based Machine Translation for E-commerce. Expert Systems with Applications, Volume 258 (SCI Zone 1, Top Journal).
  2. Chen, K., Chen, B., Gao, D., Dai, H., et al. (2024). General2Specialized LLMs Translation for E-commerce. The Web Conference (WWW), short paper (CCF-A).
  3. Shen, G., Sun, S., Gao, D., Yang, L., et al. (2023). EdgeNet: Encoder-decoder generative Network for Auction Design in E-commerce Online Advertising. The 32nd ACM International Conference on Information & Knowledge Management (CIKM), (CCF-B).
  4. Gao, D., Ma, Y., Liu, S., Song, M., Jin, L., et al. (2024). FashionGPT: LLM Instruction Fine-tuning with Multiple LoRA-adapter Fusion. Knowledge-Based Systems, Volume 299 (SCI, Top Journal).
  5. Chen, B., Jin, L., Wang, X., Gao, D., et al. (2023). Unified Vision-Language Representation Modeling for E-Commerce Same-Style Products Retrieval. Industry Track of The Web Conference (WWW), (CCF-A).
  6. Mei, X., Yang, L., Jiang, Z., Cai, X., Gao, D., et al. (2024). An Inductive Reasoning Model Based on Interpretable Logical Rules Over Temporal Knowledge Graphs. Neural Networks, Volume 174, Pages (SCI Zone 1, Top Journal).
  7. Liang, Z., Chen, B., Ran, Z., Wang, Z., Gao, D., et al. (2024). Self-Renewal Prompt Optimizing with Implicit Reasoning. The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP) findings (CCF-A).
  8. Yang, Z., Gao, H., Gao, D., Yang, L., et al. (2024). MLoRA: Multi-Domain Low-Rank Adaptive Network for CTR Prediction. The 18th ACM Conference on Recommender Systems (RecSys), (CCF-B).
  9. Zhang, X., Wang, D., Gao, D., Jiang, W., et al. (2022). Revisiting Cold-Start Problem in CTR Prediction: Augmenting Embedding via GAN. The 31st ACM International Conference on Information & Knowledge Management (CIKM), (CCF-B).
  10. Zhang, F., Zhang, Z., Gao, D., Zhuang, F., et al. (2022). Mind the Gap: Cross-lingual Information Retrieval with Hierarchical Knowledge Enhancement. The 36th AAAI Conference on Artificial Intelligence (AAAI), (CCF-A).

 

 

 

Ihtesham Arshad | Biotechnology | Young Scientist Award | 1335

Published on by Innovation Technologist

Mr. Ihtesham Arshad | Biotechnology | Young Scientist Award

Mr. Ihtesham Arshad, Dalian University of Technology, Pakistan

Mr. Ihtesham Arshad is a researcher at Dalian University of Technology, Pakistan. His research interests include materials science, nanotechnology, and renewable energy. With a strong academic background, Ihtesham is committed to producing high-quality research that contributes to the advancement of knowledge in his field.

Profile

Scopus

Educational Qualification šŸ“š

Mr. Ihtesham Arshad’s academic journey began with a strong foundation in science and technology. He pursued his Bachelor of Science in Biotechnology from the University of Okara, Pakistan, graduating with a CGPA of 3.39/4.0. He then enrolled in a Joint Master’s Program in Bioengineering offered by Dalian University of Technology and Beijing Genomics Institute, China.

Professional Experience šŸ’¼

Mr. Arshad’s professional endeavors began with research positions in renowned institutions in Pakistan. He worked as a Research Assistant at the Muhammadan Laboratory of Computational Biology, Punjab, Pakistan, from September 2022 to July 2024. During this tenure, he actively contributed to various projects, significantly enhancing microalgal oil for advanced biofuel production through leveraging bioinformatics for hybrid ORF protein construction.

Contributions and Research Focus šŸ”

Mr. Arshad’s research focus areas include Industrial Biotechnology, Environmental Biotechnology, Bioinformatics, and Microbial Biotechnology. His contributions to these fields have been significant, with several publications in reputable journals. His research has explored the development of new materials and technologies for energy applications, including solar cells and fuel cells.

Accolades and Recognition šŸ†

Mr. Arshad’s research has been recognized with several awards and honors. He has received certificates of completion for various courses and conferences, including the “Certificate Course on Right to Health” and the “International Symposium On Biopolymer and Derivatives.”

Impact and Influence šŸŒŸ

Mr. Arshad’s research has had a significant impact on the field of biotechnology. His work has been cited by numerous researchers, and he has contributed to the advancement of knowledge in the field.

Legacy and Future Contributions šŸ”œ

Mr. Arshad’s legacy in the field of biotechnology is already evident, and his future research plans include continuing to explore new areas of research and contributing to the advancement of knowledge in the field.

Courses, Conferences, and Workshops Attended šŸ“š

Mr. Arshad has attended several courses, conferences, and workshops, including:

Certificate Course on Right to Health
International Symposium On Biopolymer and Derivatives
Hands-on Training on Systematic Review and Meta-Analysis
Hands-on Training on Pharmacophore Generation & High Throughput Virtual Screening

Publication Top NotesšŸ“„

Mr. Arshad has published several papers in reputable journals, including:

1. Multifunctional role of nanoparticles for the diagnosis and therapeutics of cardiovascular diseases

Author: Ihtesham Arshad, Ayesha Kanwal, Imran Zafar, Ahsanullah Unar, Hanane Mouada, IashiaTur Razia, Safina Arif, MuhammadAhsan, Mohammad Amjad Kamal, Summya Rashid, Khalid Ali Khan, Rohit Sharma

Journal: Environmental Research

Year: 2024

2. Bioinformatics approaches in upgrading microalgal oil for advanced biofuel production through hybrid ORF protein construction

Author: Ihtesham Arshad, Muhammad Ahsan, Imran Zafar, Muhammad Sajid, Sheikh Arslan Sehgal*, Waqas Yousaf, Amna
Noor, Summya Rashid, Somenath Garai, Meivelu Moovendhan, Rohit Sharma

Journal: Biomass Conversion and Biorefinery

Year: 2023

3. Toxic effects of nanomaterials on aquatic animals and their future prospectives

Author: Imran Zafar, Arfa Safder, Quratul Ain, Mouada Hanane, Ihtesham Arshad, Mohd Ashraf Rather,
Mohammad Amjad Kamal

Journal: A book chapter was published in the book Xenobiotics in Aquatic Animals

Year: 2023

4. Biosensors for environmental pollution detection and monitoring: A Review

Author: Ihtesham Arshad*, Ayesha Siddiqua, Waseem Sarwar, Ghazala Ramzan, Arslan Habib, Amna Noor, Ramish Raza,
Mehmood Ul Hussan, Amina Anwer, Virdah Ijaz Muhammad Ahsan

Journal: Agricultural sciences journal

Year: 2022

5. A comprehensive review on the role of nanotechnology in soil pollutants remediation

Author: Ihtesham Arshad*, Amna Noor, Hamza Rashid, Mehmood Ul Hussan, Muhammad Waqas, Noor Fatima, Amina
Anwer, Virdah Ijaz, Adiba Qayyum, Fiza Arshad, Shanza Choudhry

Journal: Agricultural sciences journal

Year: 2022

 

Hongjie Zhou | Agricultural | Best Researcher Award

Published on by Innovation Technologist

Prof. Hongjie Zhou | Agricultural | Best Researcher Award

Professor at Yunnan Agricultural University, China

Professor Hongjie Zhou is renowned as one of theĀ Top Ten Outstanding Figures of Pu-erh TeaĀ globally. He is celebrated for his contributions to the tea industry and academia, receiving theĀ National “Outstanding Contribution Award for Promoting Tea Culture”Ā in 2010. He was named aĀ National Excellent TeacherĀ in 2019 and has received numerous accolades, includingĀ China Science and Technology ProgressĀ awards. As a leader inĀ tea science and technology, he has been pivotal in shaping the future of tea research and its cultural significance. šŸŒšŸƒ

Publication Profile :Ā 

Scopus

Educational Background šŸŽ“

Hongjie Zhou earned his academic credentials in the field of Tea Science and Technology, with a focus on Pu-erh tea processing and utilization. His extensive expertise and research contributions have led him to become a renowned national professor and doctoral supervisor in China.

Professional Experience šŸ’¼

Prof. Hongjie Zhou has a distinguished career in both academic research and tea industry innovation. He currently holds a position atĀ Yunnan Agricultural University, where he leads research projects on tea quality, tea processing, and the development of functional teas. With overĀ 33 research projectsĀ headed andĀ 27 research projectsĀ participated in, he has publishedĀ over 200 scientific papers, includingĀ 10+ SCI-indexed articles. His work has garnered multiple accolades, including theĀ National Outstanding Contribution AwardĀ and recognition as theĀ Leader in Tea Science and Technology Innovation. Prof. Zhou has also been grantedĀ 27 patentsĀ and authoredĀ 16 textbooksĀ andĀ 30 monographs. His research has greatly contributed to the promotion of tea culture in China and beyond, establishing him as a pivotal figure in the tea industry.

Research Interests šŸ”¬

Professor Zhou’s research is centered aroundĀ tea qualityĀ šŸŒæ,Ā tea processingĀ šŸƒ, and the development ofĀ functional teas. His work onĀ Pu-erh teaĀ and its comprehensive utilization is globally recognized. He also focuses onĀ tea germplasm resourcesĀ and aims to innovate within theĀ tea cultureĀ of China. His projects extend beyond academia, withĀ 22 industry collaborationsĀ and a significant impact onĀ tea technology. In 2014, he was honored as theĀ leader of tea science and technology innovation in Western China.

Publications šŸ“š

  1. Ma, C., Wang, Q., Tian, D., Li, Y., & Zhou, H.Ā (2024). HS-SPME-GC-MS combined with relative odor activity value identify the key aroma components of flowery and fruity aroma in different types of GABA tea.Ā Food Chemistry: X,Ā 24, 101965.Ā https://doi.org/10.xxxx/xxxxx
  2. Zhou, X., Tian, D., Zhou, H., Wang, B., & Li, Y.Ā (2024). Effects of different fermentation methods on flavor quality of Liupao tea using GC-Q-TOF-MS and electronic nose analyses.Ā Foods,Ā 13(16), 2595.Ā https://doi.org/10.xxxx/xxxxx
  3. Tian, D., Huang, G., Ren, L., Li, Y., & Zhou, H.Ā (2024). Effects ofĀ Monascus purpureusĀ on ripe Pu-erh tea in different fermentation methods and identification of characteristic volatile compounds.Ā Food Chemistry,Ā 440, 138249.Ā https://doi.org/10.xxxx/xxxxx
  4. Chen, Z., Dai, W., Xiong, M., Chen, D., & Li, Y.Ā (2024). Metabolomics investigation of the chemical variations in white teas with different producing areas and storage durations.Ā Food Chemistry: X,Ā 21, 101127.Ā https://doi.org/10.xxxx/xxxxx
  5. Yan, X., Tian, Y., Zhao, F., Shan, Z., Zhang, C., & Li, Y.Ā (2024). Analysis of the key aroma components of Pu’er tea by synergistic fermentation with three beneficial microorganisms.Ā Food Chemistry: X,Ā 21, 101048.Ā https://doi.org/10.xxxx/xxxxx