Preeti Sharma | Deep Learning | Women Researcher Award

Posted on by Academic achievements

Mrs . Preeti Sharma | Deep Learning | Women Researcher Award 

Assistant Professor , DIT University, Dehradun, Uttrakhand , India

Preeti Sharma is a dedicated researcher and educator currently pursuing a Ph.D. in Computer Science and Engineering at the University of Petroleum and Energy Studies, Dehradun. With a distinguished academic background including gold medals and high honors in her MTech and MCA degrees, Preeti has demonstrated excellence in her field. She is passionate about advancing the field of artificial intelligence and machine learning, focusing on generative adversarial networks (GANs) and deepfake detection.

Profile

Google Scholar

Education 

Preeti Sharma is pursuing a Ph.D. in Computer Science and Engineering at the University of Petroleum and Energy Studies, Dehradun, with her thesis submitted. She holds an MTech in Computer Science and Engineering from Uttarakhand Technical University, where she graduated as a gold medalist with an impressive 85%. Preeti completed her M.C.A. from M.D.U. (Campus), Rohtak, with a strong academic record of 82%.

Experience 

Preeti Sharma currently serves as a Junior Research Fellow and Teaching Assistant at the University of Petroleum and Energy Studies, Dehradun, where she has been contributing since April 2021. Prior to this, she was a Non-Teaching Staff member at the same university from September 2015 to March 2021. She also gained valuable experience as a Guest Lecturer at Arihant Institute of Technology, Haldwani, and an intern at the National Informatics Center (NIC).

Research Interests 

Preeti Sharma’s research interests include the application of Generative Adversarial Networks (GANs) in image and deepfake detection, robust CNN models, and advancements in digital forensics. Her work explores innovative methods for deepfake detection and image forgery using GAN-based models, contributing significantly to the field of multimedia tools and applications.

Awards 

Preeti Sharma has been recognized for her exceptional research and presentations. She received a certification for the best oral presentation at the International Young Researcher Conclave (IYRC-2024). Her paper on generative adversarial networks won first prize in the Research Conclave IYRC 2024 at UPES.

Publications 

  • Sharma, P., Kumar, M., Sharma, H.K. et al. Generative adversarial networks (GANs): Introduction, Taxonomy, Variants, Limitations, and Applications. Multimedia Tools and Applications (2024). Link
  • Sharma, P., Kumar, M., & Sharma, H.K. Robust GAN-Based CNN Model as Generative AI Application for Deepfake Detection, EAI Endorsed Trans IoT, vol. 10 (2024).
  • Sharma, P., Kumar, M., & Sharma, H.K. A generalized novel image forgery detection method using a generative adversarial network. Multimedia Tools and Applications (2023). Link
  • Sharma, P., Kumar, M., & Sharma, H.K. A GAN-based model of deepfake detection in social media. Procedia Computer Science, 218, 2153-2162 (2023).
  • Sharma, P., Kumar, M., & Sharma, H.K. Comprehensive analyses of image forgery detection methods from traditional to deep learning approaches: an evaluation. Multimedia Tools and Applications, 82(12), 18117-18150 (2023).
  • Sharma, P., Kumar, M., & Sharma, H.K. A Guide to Digital Forensic: Theoretical to Software-Based Investigations. Perspectives on Ethical Hacking and Penetration Testing, IGI Global (2023). Link
  • Sharma, P., Kumar, M., & Sharma, H.K. CNN-based Facial Expression Recognition System Using Deep Learning Approach. Conference on Computational Intelligence and Information Retrieval CIIR (2021).
  • Sharma, P. Real Time Tracking System for Object Tracking using the Internet of Things (IoT). Conference on Computational Intelligence and Information Retrieval CIIR (2021).
  • Sharma, P. Leach and Improved Leach: A Review. International Journal of Advanced Research in Computer Science, Vol 10 (2019).

Conclusion

Preeti Sharma’s profile shows a strong foundation in research and technical expertise, with notable contributions to GANs and deepfake detection. Her academic achievements, innovative patents, and recognition in the field underscore her qualifications. To strengthen her candidacy for the Research for Women Researcher Award, she could emphasize the broader impact of her research and highlight her leadership or mentorship roles. Overall, her qualifications and achievements make her a strong contender for the award.

Natasha Christabelle Santosa | Artificial Intelligence | Best Researcher Award

Posted on by Academic achievements

Mrs Natasha Christabelle Santosa | Artificial Intelligence | Best Researcher Award

Mrs Natasha Christabelle Santosa , Tokyo Institute of Technology , Japan

Natasha Christabelle Santosa is a dedicated artificial intelligence researcher with a passion for advancing machine learning technologies. Fluent in four languages, she has honed her expertise over two years of part-time work and PhD studies. Natasha is currently a research assistant at Tokyo Institute of Technology, where she investigates dynamic ontology applications in scientific paper recommendations. Her experience spans diverse areas including natural language processing, information retrieval, and computer vision. She is actively seeking opportunities in Tokyo, preferably in remote or hybrid roles, to leverage her skills in a global or English-Japanese environment.

Publication Profile

Google Scholar

Strengths for the Award

  1. Diverse Expertise: Natasha has a strong background in AI, machine learning, and data analysis, covering the full machine learning cycle from data construction to model deployment. Her experience spans various domains, including information retrieval, natural language processing, and computer vision.
  2. Advanced Research: Her PhD research at Tokyo Institute of Technology on dynamic ontology for scientific paper recommendations shows a commitment to advancing AI methodologies and practical applications. Her work on graph neural networks for paper recommendations, published in reputable journals, highlights her ability to tackle complex problems in cutting-edge research.
  3. Multilingual Capabilities: Being quadrilingual (Indonesian, Javanese, English, and intermediate Japanese) enhances her ability to collaborate in diverse environments, particularly beneficial in global research settings.
  4. Recognition and Funding: Receiving the prestigious Japanese government MEXT scholarship for both master’s and PhD studies underscores her exceptional academic capabilities and potential.

Areas for Improvement

  1. Broader Impact: While her research is advanced, expanding her work to include more interdisciplinary applications or collaborations could broaden its impact and applicability.
  2. Professional Experience: Gaining more industry experience or leading larger-scale projects could further enhance her practical skills and visibility in the field.
  3. Networking and Outreach: Increasing her presence in international conferences and workshops could provide additional opportunities for collaboration and recognition.

Education

Natasha is pursuing a PhD in Artificial Intelligence at Tokyo Institute of Technology, with an expected completion in September 2024. Her research focuses on scientific paper recommendation using dynamic ontology and neural networks. She holds a Master’s in Artificial Intelligence from the same institution, with a thesis on ontology-based personalized recommendation systems. Her academic journey began with a Bachelor’s in Computer Science from Gadjah Mada University, where she graduated with honors, focusing on adaptive neuro-fuzzy inference systems for cancer diagnosis.

Experience

Natasha’s professional experience includes part-time research roles at Tokyo Institute of Technology and the Advanced Institute of Science and Technology. At Tokyo Tech, she explores dynamic ontology for scientific paper recommendations. Previously, at AIST, she worked on using graph neural networks for end-to-end paper recommendations, contributing to a preprint publication. Her roles involved extensive research and practical applications in machine learning, enhancing her expertise across various domains including NLP and computer vision.

Research Focus

Natasha’s research concentrates on enhancing scientific paper recommendation systems through dynamic ontology and neural network approaches. Her PhD work involves developing advanced methods to assist in paper writing, while her earlier research explored ontology-based personalized recommendations. She has applied her skills in machine learning, data analysis, and graph neural networks to improve information retrieval and recommendation systems, aiming to advance the field of AI with innovative solutions.

Publications Top Notes

📄 N. C. Santosa, X. Liu, H. Han, J. Miyazaki. 2023. S3PaR: Section-Based Sequential Scientific Paper Recommendation for Paper Writing Assistance. In Knowledge Based Systems [in press]

📄 N. C. Santosa, J. Miyazaki, H. Han. 2021. Automating Computer Science Ontology Extension with Classification Techniques. In IEEE Access, Vol. 9, pp.161815-161833.

📄 N. C. Santosa, J. Miyazaki, H. Han. 2021. Flat vs. Hierarchical: Classification Approach for Automatic Ontology Extension. In Proceedings of Data Engineering and Information Management (DEIM).

Conclusion

Natasha Christabelle Santosa is a highly qualified candidate for the Best Researcher Award due to her extensive expertise in AI, strong research contributions, and multilingual capabilities. Her innovative work on scientific paper recommendations and advanced machine learning techniques demonstrates her potential to make significant contributions to the field. By addressing areas for improvement, such as expanding her interdisciplinary impact and gaining further industry experience, she can enhance her profile and increase her chances of receiving the award.

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.