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.

Subhrangshu Adhikary | Machine Learning | Young Scientist Award

Posted on by Academic achievements

Mr Subhrangshu Adhikary | Machine Learning | Young Scientist Award

Mr Subhrangshu Adhikary, Spiraldevs Automation Industries Pvt. Ltd. India

Subhrangshu Adhikary is the Director of Spiraldevs Automation Industries Pvt. Ltd. and a PhD scholar at the National Institute of Technology, Durgapur. With a passion for leveraging scientific advancements to solve real-world problems, he aims to make a positive impact on society and the environment. Adhikary has a diverse skill set encompassing big data, AI, and IoT, and he is recognized for his leadership in both academia and industry. His work spans across research, innovation, and technology development, reflecting his commitment to advancing knowledge and practical solutions in computer science and engineering.

Publication Profile

Scopus

Strengths for the Award

  1. Significant Contributions to Research:
    • Subhrangshu Adhikary has made notable contributions in various fields including machine learning, big data, and biomedical signal processing. His research work covers a range of topics such as secure classification frameworks, document classification with vision transformers, and advanced cryptographic algorithms.
    • His papers, such as those published in Biomedical Signal Processing and Control and Machine Learning and Knowledge Extraction, demonstrate his expertise and innovative approach to complex problems.
  2. Innovative Intellectual Properties:
    • Adhikary holds multiple patents and copyrights, which showcase his ability to develop practical and innovative solutions. For instance, his patents related to fault-tolerant storage systems and decentralized sensor networks are indicative of his technical prowess and creativity.
  3. Awards and Recognition:
    • His achievements, including the Best Research Award at SMTST-2020 and several accolades from NPTEL, highlight his recognition within the scientific community. These awards underline his commitment to excellence and his impact on the field of computer science and engineering.
  4. Diverse Skill Set:
    • His broad technical skill set in areas such as big data, AI/ML, and IoT, combined with his experience in full-stack development and various programming languages, reflects a well-rounded expertise essential for cutting-edge research.
  5. Leadership and Experience:
    • As the Director of Spiraldevs Automation Industries Pvt. Ltd. and IT Head of Drevas Vision Pvt. Ltd., Adhikary has demonstrated strong leadership skills and practical experience in managing and executing technology projects. His roles in these positions complement his research activities, providing a solid foundation for innovative and impactful work.

Areas for Improvement

  1. Publication Impact:
    • While Adhikary has numerous publications, increasing the citation impact and visibility of his work in high-impact journals could further enhance his reputation in the research community. Expanding his research into more widely recognized venues could contribute to a greater influence in his field.
  2. Interdisciplinary Collaboration:
    • Further collaboration with researchers from different disciplines could broaden the scope and application of his work. Engaging in interdisciplinary projects may lead to more diverse and impactful research outcomes.
  3. Research Visibility:
    • Increasing engagement with broader research communities through conferences and workshops could raise awareness of his contributions. Presenting at international forums and participating in collaborative research initiatives may help elevate his profile.

Education

Subhrangshu Adhikary is pursuing a Doctorate in Computer Science and Engineering at the National Institute of Technology, Durgapur, since August 2022. He earned his Bachelor of Technology in Computer Science and Engineering from Dr. B.C. Roy Engineering College, achieving a CGPA of 9.20. His academic journey began at Bethany Mission School, where he completed his Class XII with an aggregate of 74% and Class X with a perfect CGPA of 10.0. His educational background underscores his strong foundation and continued pursuit of excellence in technology and research.

Experience

Subhrangshu Adhikary has been the Director of Spiraldevs Automation Industries Pvt. Ltd. since July 2020, driving innovation and technology solutions in West Bengal. He also serves as the IT Head of Drevas Vision Pvt. Ltd., a software outsourcing company, since September 2020. His roles involve overseeing technology development and management, showcasing his leadership and expertise in the tech industry. His experience encompasses both strategic direction and technical execution, highlighting his multifaceted capabilities in technology and business management.

Awards and Honors

Subhrangshu Adhikary has been honored with the Best Research Award at the SMTST-2020 Conference, recognizing his outstanding research contributions. He has also received multiple accolades from NPTEL, including NPTEL Star, NPTEL Believer, and NPTEL Enthusiast. These awards reflect his excellence in the field of computer science and engineering. Additionally, Adhikary has achieved significant recognition through various local, school, and college-level competition wins, and ranked AIR 108 in the PNTSE Olympiad in 2015.

Research Focus

Subhrangshu Adhikary’s research focuses on integrating big data, AI, and IoT to address complex problems. His work includes developing distributed fault-tolerant storage systems, decentralized sensor networks, and advanced cryptographic algorithms. He explores machine learning applications for environmental monitoring and biomedical diagnostics. His research aims to create sustainable and impactful solutions, enhancing both theoretical knowledge and practical applications in technology and data science.

Publication Top Notes

  • “DitDViiPt PrivLet: A differential privacy and inverse wavelet decomposition framework for secure and optimized hemiplegic gait classification” 📝
  • “VisFormers—Combining Vision and Transformers for Enhanced Complex Document Classification” 📄
  • “Global marine phytoplankton dynamics analysis with machine learning and reanalyzed remote sensing” 🌊
  • “Secret learning for lung cancer diagnosis—a study with homomorphic encryption, texture analysis and deep learning” 🩺
  • “Optimized EEG based mood detection with signal processing and deep neural networks for brain-computer interface” 🧠
  • “DeCrypt: a 3DES inspired optimised cryptographic algorithm” 🔐
  • “Improved Large-Scale Ocean Wave Dynamics Remote Monitoring Based on Big Data Analytics and Reanalyzed Remote Sensing” 🌍
  • “If Human Can Learn from Few Samples, Why Can’t AI? An Attempt On Similar Object Recognition With Few Training Data Using Meta-Learning” 🤖
  • “Evolutionary Swarming Particles To Speedup Neural Network Parametric Weights Updates” ⚙️
  • “Price Prediction of Digital Currencies using Machine Learning” 💹

Conclusion

Subhrangshu Adhikary is a highly deserving candidate for the Best Researcher Award due to his significant contributions to research, innovative intellectual properties, and demonstrated leadership in the technology sector. His impressive track record of awards, patents, and publications underscores his expertise and dedication to advancing knowledge in his field. Addressing areas for improvement, such as increasing the impact of his publications and enhancing interdisciplinary collaborations, could further solidify his standing as a leading researcher. Overall, Adhikary’s achievements and potential make him a strong contender for this prestigious award.

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).

 

 

ANUJA BHARGAVA | Artificial Intelligence | Most Cited Paper Award

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Assist Prof Dr. ANUJA BHARGAVA | Artificial Intelligence | Most Cited Paper Award

Assistant Professor GLA University India

Dr. Anuja Bhargava is an accomplished academic and researcher, currently serving as an Assistant Professor at GLA University, Mathura. With a Ph.D. in Electronics and Communication Engineering, she specializes in Digital Signal Processing, VLSI, and Artificial Intelligence. Dr. Bhargava has a wealth of teaching experience and has published extensively in renowned journals and conferences. Her dedication to education and research has earned her a prominent place in her field.

Profile

Scopus

Education 🎓

Dr. Anuja Bhargava earned her Ph.D. in Electronics and Communication Engineering from GLA University, Mathura, where she conducted groundbreaking research on “Quality Evaluation of Fruits using Image Processing.” She holds a Master of Technology in Digital Communication from Uttrakhand Technical University and a Bachelor of Engineering in Electronics and Communication Engineering from Modi Institute of Technology, Kota, both with first-class honors.

Experience 🏫

Dr. Bhargava’s academic journey includes roles as Assistant Professor at GLA University since October 2021, and previously at Gurukul Institute of Engineering & Technology and Maharishi Arvind International Institute of Technology. Her extensive teaching experience spans over a decade, focusing on various aspects of electronics and communication engineering.

Research Interests 🔍

Dr. Bhargava’s research interests are diverse and include Digital Signal Processing, Very Large Scale Integration (VLSI), Control Systems, Signal and Systems, Electromagnetic Field Theory, Microprocessors, and Basic Electrical and Electronics. She is particularly interested in the application of Artificial Intelligence in these domains.

Awards 🏆

Dr. Anuja Bhargava has been recognized for her contributions to academia and research with various awards and nominations. She has served as a keynote speaker at international conferences and received accolades for her innovative research and teaching methodologies.

Publications Top Notes 📚

Gupta D, Bhargava A, et al. “Deep Learning-Based Truthful and Deceptive Hotel Reviews.” Sustainability, 2024, link, cited by articles.

Bhargava A, et al. “Plant Leaf Disease Detection, Classification and Diagnosis using Computer Vision and AI: A Review.” IEEE Access, 2024, link, cited by articles.

Sachdeva A, Bhargava A, et al. “A CNTFET based stable, single ended 7T SRAM cell with improved write operation.” Physica Scripta, 2024, link, cited by articles.

Bhargava A, et al. “Machine learning & computer vision-based optimum black tea fermentation detection.” Multimed Tools Appl, 2023, link, cited by articles.

Sharma A, Bhargava A, et al. “Multi-level Segmentation of Fruits Using Modified Firefly Algorithm.” Food Anal. Methods, 2022, link, cited by articles.

Paulo Vinicius Moreira Dutra | Artificial Intelligence and Machine Learning | Best Researcher Award

Posted on by Academic achievements

Mr.Paulo Vinicius Moreira Dutra | Artificial Intelligence and Machine Learning | Best Researcher Award

Master Federal University of Juiz de Fora Brazil

Paulo Vinícius Moreira Dutra is a dedicated computer science professor specializing in system development, software engineering, and digital games. With over a decade of teaching experience, Paulo has made significant contributions to various educational institutions, including the Instituto Federal de Educação Ciência e Tecnologia Sudeste de Minas Gerais.

Profile

ORCiD

Education

🎓 Paulo holds a Master’s degree in Computer Science from the Universidade Federal de Juiz de Fora (2023), with a focus on artificial intelligence. He also has a specialization in Computer Programming (2008), Higher Education Teaching (2017), and Digital Game Development (2018), as well as a bachelor’s degree in System Development Technology (2006).

Experience

💼 Paulo has extensive experience in both academia and industry. He has taught at the Faculdade de Filosofia, Ciências e Letras Santa Marcelina and currently serves as a professor at the Instituto Federal do Sudeste de Minas Gerais. His professional journey also includes a role as a systems analyst at Dvallone Tecidos Ltda, where he developed applications using Delphi, Advpl, and C#.

Research Interest

🔍 Paulo’s research interests lie in system development, software engineering, digital games, databases, machine learning, and reinforcement learning. His work often explores the intersection of artificial intelligence and game development, focusing on procedural content generation and educational applications.

Awards

🏆 Paulo has been recognized for his contributions to computer science education and research. His innovative approach to teaching and his impactful research projects have earned him accolades and nominations in various academic circles.

Publications

📝 Paulo has published several research articles and papers in esteemed journals and conferences. Notable publications include:

  1. “ARTOOLKIT: UMA BIBLIOTECA PARA CONSTRUÇÃO DE APLICAÇÕES EM REALIDADE AUMENTADA” (2016). Published in DUC IN ALTUM (Muriaé). Link.
  2. “Desenvolvimento de um framework para construção de aplicações desktop em java utilizando swing” (2011). Published in Duc in Altum (Muriaé).
  3. “A mixed-initiative design framework for procedural content generation using reinforcement learning” (2024). Accepted for publication in ENTERTAINMENT COMPUTING.
  4. “Procedural Content Generation using Reinforcement Learning and Entropy Measure as Feedback” (2022). Presented at the 21st Brazilian Symposium on Computer Games and Digital Entertainment (SBGames). Link.