Zhiqiang He | Artificial Intelligence | Best Researcher Award

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Dr. Zhiqiang He | Artificial Intelligence | Best Researcher Award 

Ph.D. at The university of Electro-Communications, China

Zhiqiang He is an emerging researcher specializing in reinforcement learning and artificial intelligence (AI), with a focus on developing and optimizing control algorithms for complex systems. He has made significant contributions to both academic research and industrial applications, demonstrating expertise in designing innovative AI solutions for real-world problems. His educational background in control science and engineering, combined with practical experiences at leading tech companies, has shaped his career and led to several impactful publications in renowned journals. Zhiqiang’s accomplishments, recognized through various academic awards and industry achievements, make him a strong candidate for the “Best Researcher Award.”

Profile

ORCID

Education

Zhiqiang pursued his Master of Science in Control Science and Engineering at Northeastern University (NEU), Shenyang, China, from September 2019 to June 2022, where he maintained a commendable GPA of 3.29/4. During his master’s program, he specialized in the development of reinforcement learning algorithms, which formed the cornerstone of his research. Prior to this, he earned his Bachelor of Science in Automation at East China Jiaotong University (ECJTU), Nanchang, China, from September 2015 to June 2019, with a GPA of 3.42/4. His undergraduate studies laid a strong foundation in automation and control systems, providing the technical skills and knowledge that fueled his passion for AI and intelligent decision-making.

Experience

Throughout his academic journey, Zhiqiang actively engaged in research and industry roles that enriched his experience in the field of AI. He served as a team leader at the Institute of Deep Learning and Advanced Intelligent Decision-Making at NEU, where he worked on the development of reinforcement learning algorithms. Leading projects from September 2020 to June 2021, he conducted research on model-based reinforcement learning, optimized algorithm performance, and supervised students in their projects. Additionally, his early experience as a team leader at the Jiangxi Province Advanced Control and Key Optimization Laboratory involved applying reinforcement learning to control problems from 2016 to 2019, where he gained hands-on skills in analyzing system behaviors and establishing Markov Decision Process (MDP) models.

In the industry, Zhiqiang took on roles that deepened his technical expertise. He was an intern at Baidu, Beijing, China, where he pioneered the development of the Expert Data-Assisted Multi-Agent Proximal Policy Optimization (EDA-MAPPO) algorithm, an innovative approach to multi-agent cooperative adversarial AI. Later, as a reinforcement learning algorithms engineer at InspirAI in Hangzhou, he led the development of AI strategies for popular card games, showcasing his ability to apply AI solutions to commercial projects and enhance algorithmic performance.

Research Interest

Zhiqiang’s research interests are centered on reinforcement learning, AI, and control systems. He focuses on designing algorithms that improve the efficiency and accuracy of AI models in decision-making tasks. His work involves exploring new methods for multi-agent reinforcement learning, optimizing algorithms for real-time applications, and addressing challenges in intelligent control. By bridging theoretical research with practical applications, he aims to push the boundaries of AI, making it more adaptable and applicable to various industries. His dedication to advancing reinforcement learning techniques aligns with the future trajectory of AI research, where automation and intelligent decision-making are key drivers of innovation.

Awards

Zhiqiang has received recognition for his academic excellence and research contributions throughout his career. He was honored as an “Outstanding Graduate” by East China Jiaotong University in 2019, acknowledging his academic achievements and leadership potential. In addition, he secured the Third Prize in the 15th “Challenge Cup” Jiangxi Division in 2017 and the Second Prize in the International Mathematical Modeling Competition for American College Students in 2018, demonstrating his problem-solving skills and competitive spirit. His active engagement in professional development is further highlighted by his certifications in network technology and programming languages, which add to his multidisciplinary skill set.

Publications

He Z, Qiu W, Zhao W, et al. Understanding World Models through Multi-Step Pruning Policy via Reinforcement Learning. Information Sciences, 2024: 121361. – Cited by 32 articles.

Chen P, He Z, Chen C, et al. Control strategy of speed servo systems based on deep reinforcement learning. Algorithms, 2018, 11(5): 65. – Cited by 15 articles.

Wang J, Zhang L, He Z, et al. Erlang planning network: An iterative model-based reinforcement learning with multi-perspective. Pattern Recognition, 2022, 128: 108668. – Cited by 27 articles.

Zhang L, He Z, Zhao Y, et al. Reinforcement Learning-based Control of Robotic Manipulators. Journal of Robotics, 2023, 12(3): 112-121. – Cited by 19 articles.

He Z, Zhao W, Zhang L, et al. Multi-Agent Deep Reinforcement Learning in Dynamic Environments. Artificial Intelligence Review, 2022, 55(2): 456-472. – Cited by 24 articles.

Chen C, He Z, Qiu W, et al. Optimal Control for Nonlinear Systems Using Reinforcement Learning. Control Theory and Applications, 2021, 59(4): 553-566. – Cited by 18 articles.

Conclusion

Zhiqiang He’s contributions to AI and reinforcement learning, coupled with his practical experience and research output, position him as a promising researcher in the field. His work not only advances the academic understanding of intelligent control but also finds applications in industry, where AI solutions are critical to technological development. By consistently pushing for excellence in his projects, he demonstrates qualities that make him a deserving candidate for the “Best Researcher Award.” His trajectory reflects a commitment to innovation, making him an asset to the research community and a potential leader in future AI advancements.

Jie Li | Artificial Intelligence | Best Researcher Award

Posted on by Academic achievements

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

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

Profile

scopus

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.

Moumita Chanda | Deep Learning | Best Researcher Award

Posted on by Academic achievements

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

Google Scholar

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).

 

 

Ms. Kumi Rani – Machine Learning – Best Researcher Award

Posted on by Academic achievements

Ms. Kumi Rani - Machine Learning - Best Researcher Award

Indian Institute of Technology BHU, Varanasi - India

Professional Profiles

Early Academic Pursuits:

Kumi Rani's academic journey began with a passion for Computer Science and Engineering at the prestigious Indian Institute of Technology (IIT) BHU, Varanasi. During her early academic pursuits, she immersed herself in a challenging curriculum, laying the foundation for a robust understanding of computational sciences. The rigorous coursework at IIT BHU introduced her to a diverse range of subjects, including Artificial Intelligence, Neural Networks, Computer Graphics, and Mathematical Modeling.

Professional Endeavors:

Post her academic journey, Kumi Rani transitioned into the realm of academia. She served as an Assistant Professor at Sharda University, Greater Noida, where she contributed to the Computer Science and Engineering department. Subsequently, she expanded her academic footprint to include the Mathematics department at Shree DKV Science and Arts College, Jamnagar. This versatility showcased her ability to navigate and contribute to different facets of academia.

Contributions and Research Focus:

Kumi Rani's contributions in academia extend to her technical skills and her research focus. Proficient in operating systems such as Windows Vista/XP/Linux and mathematical software like Matlab R2009a, she demonstrated a command over tools crucial for computational research. Her programming expertise in C, Python, C++, and Matlab reflected her commitment to staying at the forefront of technological advancements. At the heart of her research focus lies an intersection of Machine Learning, Deep Learning, and Applied Mathematics. Her Ph.D. thesis, "Handcrafted and Deep Learning Techniques for Classification of Medical and Hyperspectral Images," underscores her commitment to addressing critical challenges in medical image analysis. By amalgamating traditional handcrafted methods with cutting-edge deep learning architectures, she aimed to elevate the precision and efficiency of medical image diagnostics. Her M.Tech thesis, "A Study of Clustering Algorithms in Fuzzy Scenario," delves into the realms of unsupervised learning and statistical data analysis. The introduction of the Kernel Intuitionistic Fuzzy c-Means algorithm reflects her innovative approach to clustering, emphasizing improved performance and robustness.

Accolades and Recognition:

Kumi Rani's academic prowess has earned her notable accolades and recognition. She secured an impressive All India Rank of 199 in the National Eligibility Test (NET) for Lectureship, a joint initiative by the Council of Scientific and Industrial Research (CSIR) and University Grants Commission (UGC). Additionally, she secured an All India Rank of 83 in the Graduate Aptitude Test in Engineering (GATE), a testament to her excellence in the field. Her pursuit of continuous learning is evident through her completion of professional development programs and courses on platforms like Coursera and Oracle Academy. This commitment to staying abreast of industry-relevant skills showcases her dedication to both personal and professional growth.

Impact and Influence:

In her professional roles, Kumi Rani has not only shared her knowledge through teaching but has also left an impact on real-world projects. Her involvement in projects at ATC Labs, including the design of a real-time broadcast communicator on the Android platform, reflects her ability to apply computational skills to practical scenarios. Her guidance on B.Tech projects further extends her influence to shaping the next generation of computational professionals.

Legacy and Future Contributions:

As Kumi Rani continues her journey, her legacy at the Indian Institute of Technology BHU, Varanasi, is marked by her early academic pursuits, versatile contributions in academia, and impactful research focus. Her commitment to education, demonstrated through the diverse courses she has taught, and her ongoing research pursuits are likely to define her future contributions. In the interdisciplinary field of computational sciences and mathematics, Kumi Rani's legacy is shaped by a dedication to excellence and a vision for the continual advancement of knowledge and application.

Notable Publications:

Classification of wireless capsule endoscopy images for bleeding using deep features fusion 2022-11-16

Cyclic learning rate based HybridSN model for hyperspectral image classification 2022-09

Automated bleeding detection in wireless capsule endoscopy images based on sparse coding 2021-08