Jie Li | Artificial Intelligence | Best Researcher Award

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Assoc Prof Dr. Jie Li | Artificial Intelligence | Best Researcher Award 

Assoc Prof Dr. Jie Li, Chongqing University of Science & Technology, China

Profile

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Dr. Jie Li is an Associate Professor at the School of Computer Science and Engineering, Chongqing University of Science and Technology. With a PhD from Chongqing University (2011), she has held roles as an assistant researcher at the Chongqing Green Intelligent Technology Research Institute and a post-doctoral fellow at Chongqing Qingshan Industrial Company Limited. Her research has led to numerous patents and influential publications in top journals like IEEE Transactions. Dr. Li has also been involved in significant university-enterprise cooperative projects, highlighting her leadership and innovation in artificial intelligence and machine learning.

Strengths for the Award:

  1. Significant Research Contributions: Dr. Jie Li has made substantial contributions to artificial intelligence, machine learning, and fault diagnosis. Her work, published in top-tier journals like IEEE Transactions, demonstrates high-impact research in these fields.
  2. Extensive Patent Portfolio: With over 40 invention patents applied for and 18 authorized, Dr. Li’s innovative approaches are translating into practical technologies and solutions, showcasing her role as a leading inventor and researcher.
  3. Leadership in Projects: She has successfully led 16 national and provincial research projects and 7 enterprise-level projects. Her leadership in university-enterprise cooperative projects further underscores her ability to bridge academia and industry effectively.
  4. Academic and Industry Impact: Her book “Artificial Intelligence” has received industry praise, and her publications, totaling over 40 papers, reflect a broad and impactful research portfolio.

Areas for Improvement:

  1. Broader Citation Metrics: While Dr. Li has a respectable citation count, expanding her citation index could enhance her visibility and recognition in the global research community. Increasing collaboration with international researchers might help achieve this.
  2. Research Dissemination: Although Dr. Li has published extensively, further dissemination through high-impact conferences and workshops could elevate her work’s visibility and influence, potentially leading to more collaborative opportunities.
  3. Diverse Research Areas: Diversifying her research focus beyond her core areas could open new avenues for innovation and impact. Exploring emerging trends in AI and machine learning might strengthen her research portfolio.

Education🎓

Dr. Jie Li completed her PhD in Computer Science at Chongqing University in December 2011. Her doctoral studies laid the foundation for her extensive research in artificial intelligence and machine learning. During her academic career, she has broadened her expertise through postdoctoral research and academic visits to prestigious institutions like Tsinghua University and the University of Rhode Island. These experiences have enriched her academic perspective and research capabilities, significantly contributing to her professional achievements.

Experience💼

Dr. Jie Li began her career as an assistant researcher at the Chongqing Green Intelligent Technology Research Institute from February 2012 to April 2014. She later worked as a post-doctoral fellow at Chongqing Qingshan Industrial Company Limited from April 2017 to January 2020. Her academic tenure at Chongqing University of Science and Technology includes significant roles, such as being rated as an associate professor in September 2019. Additionally, she has led numerous national and provincial research projects and has been actively involved in university-enterprise cooperation initiatives.

Research Focus🔬

Dr. Jie Li’s research encompasses Deep Learning, Machine Learning, Fault Diagnosis, and Artificial Intelligence. Her work focuses on advancing these fields through innovative algorithms and practical applications. She has led and participated in several high-impact projects funded by national and provincial bodies. Her research has significantly contributed to the development of new technologies and solutions, reflected in her extensive patent portfolio and publications in prestigious journals such as IEEE Transactions.

Publications Top Notes

Polyacrylonitrile-based 3D N-rich activated porous carbon synergized with Co-doped MoS2 for promoted electrocatalytic hydrogen evolution (Huang, Z., Li, J., Guo, S., Zeng, J., Yuan, F., Separation and Purification Technology, 2025, 354, 129011) 📄

In-situ construction of nano-multifunctional interlayer to obtain intimate Li/garnet interface for dendrite-free all solid-state battery (Yu, S., Gong, Z., Gao, M., Li, Y., Chen, Y., Journal of Materials Science and Technology, 2025, 206, pp. 248–256) 📄

Advanced cathode materials for metal ion hybrid capacitors: Structure and mechanisms (Li, J., Liu, C., Momen, R., Zou, G., Ji, X., Coordination Chemistry Reviews, 2024, 517, 216018) 📖

Unraveling the delithiation mechanism of air-stabilized fluorinated lithium iron oxide pre-lithiation material (Wen, N., Li, J., Zhu, B., Guo, J., Zhang, Z., Chemical Engineering Journal, 2024, 497, 154536) 📄

Dual ion regulation enables High-Coulombic-efficiency lithium metal batteries (Huang, X., Wang, M., Zhou, Y., Li, J., Lai, Y., Nano Energy, 2024, 129, 110031) 📄

In-Situ Construction of Electronically Insulating and Air-Stable Ionic Conductor Layer on Electrolyte Surface and Grain Boundary to Enable High-Performance Garnet-Type Solid-State Batteries (Zhou, X., Liu, J., Ouyang, Z., Li, J., Jiang, L., Small, 2024, 20(34), 2402086) 📄

Enhancing the Efficient Utilization of Li2S in Lithium-Sulfur Batteries via Functional Additive Diethyldiselenide (Li, Z., Wang, M., Yang, J., Lai, Y., Li, J., Energy and Fuels, 2024, 38(16), pp. 15762–15770) 📄

Emerging polyoxometalate clusters-based redox flow batteries: Performance metrics, application prospects, and development strategies (Han, M., Sun, W., Hu, W., Zhang, C., Li, J., Energy Storage Materials, 2024, 71, 103576) 📖

Conductivity behavior of Na5YSi4O12 and its typical structural analogues by solution-assisted solid-state reaction for solid-state sodium battery (Liu, L., Xu, Y., Zhou, X., Guo, X., Jiang, Y., Journal of Solid State Chemistry, 2024, 336, 124781) 📄

Preparation of Hard-Soft Carbon via Co-Carbonization for the Enhanced Plateau Capacity of Sodium-Ion Batteries (Li, J., Zheng, H., Du, B., Li, D., Chen, Y., Energy and Fuels, 2024, 38(14), pp. 13398–13406) 📄

Conclusion:

Dr. Jie Li’s exceptional achievements in artificial intelligence and machine learning, marked by a robust patent portfolio, significant publications, and leadership in high-impact projects, position her as a strong candidate for the Best Researcher Award. Her innovative contributions and ability to lead and execute complex research projects highlight her outstanding capabilities and potential for furthering advancements in her field. Addressing the areas for improvement could further enhance her already impressive research profile and global impact.

Xinyu Gu | Artificial Intelligence | Excellence in Research

Posted on by Academic achievements

Dr. Xinyu Gu | Artificial Intelligence | Excellence in Research 

Researcher | The University of Wollongong | Australia

Based on the provided details about Xinyu Gu, here’s an analysis of their suitability for a Research for Excellence in Research award with a focus on “Strengths for the Award, Areas for Improvement, and Conclusion”:

Strengths for the Award

  1. Advanced Expertise in Machine Learning and AI:
    • Xinyu Gu has a solid proficiency in various machine learning and deep learning models (e.g., SVM, RNN, LSTM, CNN, BERT), which demonstrates a high level of technical expertise in the field.
    • Their skill set includes Python programming and familiarity with popular frameworks like PyTorch and TensorFlow, which are crucial for cutting-edge research in AI.
  2. Relevant Academic Background:
    • Xinyu holds a Ph.D. in Artificial Intelligence and a Master’s degree in the same field from prestigious universities (University of Wollongong and University of New South Wales). Their academic credentials are complemented by awards such as the University Postgraduate Scholarship and China National Scholarship.
  3. Strong Publication Record:
    • The individual has published multiple high-impact papers in SCI Q1 journals and conferences. This includes first-author papers in journals with high impact factors like Energy, Journal of Power Sources, and International Journal of Rock Mechanics and Mining Sciences. This track record indicates significant contributions to the field and recognition by peers.
  4. Diverse Research Experience:
    • Xinyu’s work history includes substantial research experience in industry and academia, with contributions to projects involving advanced lithium-ion battery technologies and innovative power solutions for mining applications.
    • Their involvement in research projects with renowned institutions like CSIRO and UNSW reflects strong collaborative skills and the ability to work on impactful research.
  5. Technical and Soft Skills:
    • They exhibit strong skills in data analysis, visualization, and literature review, essential for conducting high-quality research.
    • Their effective communication in English, both in writing and speaking, is supported by a high IELTS score and active engagement in academic conferences.

Areas for Improvement

  1. Broader Research Impact:
    • While Xinyu has an impressive publication record, expanding research contributions to more diverse areas within AI or interdisciplinary fields could further enhance their profile. Exploring applications in emerging areas such as quantum computing or ethical AI could be beneficial.
  2. Leadership and Mentorship Experience:
    • There is limited information on leadership roles or mentoring experience. Taking on more leadership responsibilities in research projects or guiding junior researchers could strengthen their profile as a leading researcher.
  3. Grant Acquisition:
    • Experience in securing research grants or funding is not highlighted. Demonstrating success in obtaining research grants could add a valuable dimension to their research profile.
  4. Broader Dissemination and Outreach:
    • Increasing efforts in public engagement, such as participating in outreach activities or public science communication, could enhance the societal impact of their research and increase visibility.

Short Bio

Xinyu Gu is a skilled researcher specializing in artificial intelligence, with a profound expertise in machine learning and deep learning techniques. Currently a Research Associate at Azure Mining Technology Pty Ltd in Sydney, Xinyu excels in applying advanced AI models to solve real-world problems in energy and mining industries. With a Ph.D. in Artificial Intelligence from the University of Wollongong, Xinyu has made significant contributions to the field through both academic research and industry projects, showcasing a strong commitment to innovation and problem-solving.

Profile

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Education

Xinyu Gu completed a Ph.D. in Artificial Intelligence at the University of Wollongong in November 2023, where they were awarded the University Postgraduate Scholarship and Tuition Fees Waiver Award. Prior to this, they earned a Master’s degree in Artificial Intelligence from the University of New South Wales in December 2020, and a Bachelor’s degree in Mechanical Engineering from Nanjing Technology University, China, in June 2018. Xinyu’s academic journey has been marked by excellence and recognition, including the China National Scholarship Award.

Experience

In their current role as a Research Associate at Azure Mining Technology Pty Ltd since February 2020, Xinyu Gu has managed and coordinated numerous research projects in collaboration with top academic and research institutions, such as the University of New South Wales and CSIRO. Their work involves developing advanced power solutions for mining applications and managing cybersecurity and website development for the company. Previously, Xinyu interned as a Data Analyst at Dr Aha Data & AI Technology, where they honed their skills in data visualization and machine learning.

Research Interest

Xinyu Gu’s research interests lie at the intersection of machine learning, deep learning, and their applications in energy and mining sectors. They focus on enhancing the performance and safety of energy storage systems, particularly lithium-ion batteries, and applying AI techniques to predict and manage power sources in challenging environments. Their work includes exploring novel methods for state-of-charge estimation, state-of-health prediction, and improving safety in mining technologies.

Awards

Xinyu Gu has been recognized with several prestigious awards throughout their academic and professional career. These include the University Postgraduate Scholarship and Tuition Fees Waiver Award from the University of Wollongong, the China National Scholarship Award, and various acknowledgments for research excellence in publications and conferences.

Publication

  1. Energies, SCI Q2, Impact Factor: 3.2 (2023)
    • X. Gu, K.W. See, Y. Wang, L. Zhao, W. Pu. The sliding window and SHAP theory—an improved system with a long short-term memory network model for state of charge prediction in electric vehicle application.
    • Cited by: 15
  2. Energy, SCI Q1, Impact Factor: 9.2 (2023)
    • X. Gu, K.W. See, P. Li, K. Shan, Y. Wang, L. Zhao, K.C. Lim, N. Zhang. A novel state-of-health estimation for the lithium-ion battery using a convolutional neural network and transformer model.
    • Cited by: 22
  3. Journal of Power Sources, SCI Q1, Impact Factor: 9.72 (2023)
    • X. Gu, K.W. See, Y. Liu, B. Arshad, L. Zhao, Y. Wang. A time-series Wasserstein GAN method for state-of-charge estimation of lithium-ion batteries.
    • Cited by: 18
  4. International Journal of Rock Mechanics and Mining Sciences, SCI Q1, Impact Factor: 7.1 (2023)
    • X. Gu, C. Zang, K.W. See, B. Arshad, Y. Sun, Z. Liu, G. Xu, Y. Wang, S. Dai, X. Zhou, Y. Niu. Machine learning approaches for short-term and long-term prediction of strata pressure for coal mining applications.
    • Cited by: 12
  5. IEEE Conference 2023 (Accepted)
    • X. Gu, K.W. See, X. Wu, Y. Wang, C. Zang. Data preprocessing and machine learning approaches in battery’s state of charge and state of health estimation: a review.
    • Cited by: 7
  6. International Journal of Coal Science and Technology, SCI Q1, Impact Factor: 5.79 (2023)
    • K.W. See, G. Wang, Y. Zhang, Y. Wang, L. Meng, X. Gu*, N. Zhang, K.C. Lim, L. Zhao, B. Xie. Critical review and functional safety of a battery management system for large-scale lithium-ion battery pack technologies.
    • Cited by: 10
  7. Industrial & Engineering Chemistry Research, SCI Q1, Impact Factor: 4.2 (2023)
    • Z. Xie, X. Gu, Y. Shen. A machine learning study of predicting mixing and segregation behaviors in a bidisperse solid-Liquid Fluidized Bed.
    • Cited by: 9
  8. Journal of Environmental Management, SCI Q1, Impact Factor: 8.70 (2023)
    • X. Wu, P. Li, X. Gu*, K.W. See, J. Li. A Bpnn-Transformer for air quality index prediction.
    • Cited by: 8

Conclusion

Xinyu Gu shows strong qualifications for the Research for Excellence in Research award, with notable strengths in technical expertise, academic achievements, and research impact. Their extensive publication record and experience with advanced machine learning techniques position them as a strong candidate for recognition.

Moumita Chanda | Deep Learning | Best Researcher Award

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Ms.Moumita Chanda | Deep Learning | Best Researcher Award

Lecturer IUBAT – International University of Business Agriculture and Technology  Bangladesh

Moumita Chanda is a passionate researcher and lecturer at the International University of Business Agriculture and Technology (IUBAT). She specializes in computer science and engineering, focusing on emerging technologies like machine learning, artificial intelligence, and IoT. With a robust academic background and a keen interest in interdisciplinary research, Moumita strives to contribute significantly to technological advancements and innovation.

Profile

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Education

🎓 Moumita Chanda earned her M.Sc. in Information and Communication Technology (ICT) from the Institute of Information Technology (IIT), Jahangirnagar University, Dhaka, with a stellar CGPA of 3.71/4.00, securing the 1st position among her peers in 2022-2023. She also holds a B.Sc. in Information Technology from the same institution, achieved in 2022, with a commendable CGPA of 3.53/4.00. Prior to her university education, she completed her Higher Secondary School at Cumilla Government Women’s College and her Secondary School Certificate at Cumilla Modern High School, both with excellent academic records.

Experience

💼 Since December 2023, Moumita has been imparting knowledge and skills as a Lecturer in the Department of Computer Science and Engineering at IUBAT. Her professional journey is marked by her commitment to teaching and research, where she integrates her extensive knowledge of modern technologies and practical experience to educate and inspire her students.

Research Interest

🔍 Moumita Chanda’s research interests are diverse and interdisciplinary, encompassing Machine Learning, Artificial Intelligence, Internet of Things (IoT), Augmented Reality (AR), Explainable Artificial Intelligence (XAI), Metaverse, Computer Vision, Image Processing, Wearable Sensor Networks, and Human-Computer Interaction (HCI). She is dedicated to exploring and advancing these fields to drive innovation and practical applications in various domains.

Awards and Achievements

🏆 Moumita’s dedication to learning and research has been recognized through various awards. She has completed several online non-credit courses from prestigious institutions, including the University of California, University of Michigan, Macquarie University, and Duke University. Additionally, she was a finalist in the Mujib 100 Idea Contest 2021, where her innovative idea “BongoDecor” aimed at reducing plastic consumption problems, was highly appreciated.

Publications

📄 Moumita Chanda has a commendable list of publications, showcasing her contributions to the field of technology and research. Some of her notable works include:

  • “A review of emerging technologies for IoT-based smart cities” in Sensors, 2022. Read more
  • “Deep learning-based human activity recognition using CNN, ConvLSTM, and LRCN” in International Journal of Cognitive Computing in Engineering, 2024. Read more
  • “Impact of Internet Connectivity on Education System in Bangladesh during Covid-19” in International Journal of Advanced Networking and Applications, 2022. Read more
  • “Smoker Recognition from Lung X-ray Images using ML” in 2023 26th International Conference on Computer and Information Technology (ICCIT), IEEE. Read more
  • “Does VGG-19 Road Segmentation Method is better than the Customized UNET Method?” Accepted in 2024 9th International Conference on Machine Learning Technologies (ICMLT 2024).