Mohamed Ali Hajjaji | Applications of Computer Vision | Top Researcher Award

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Prof. Mohamed Ali Hajjaji | Applications of Computer Vision | Top Researcher Award

ISSAT De Sousse | University of Sousse | Tunisia

Prof. Mohamed Ali Hajjaji is a distinguished researcher at the Institut Supérieur des Sciences Appliquées et de Technologie de Sousse, Tunisia, specializing in FPGA-based systems, artificial intelligence, cryptography, and intelligent infrastructure monitoring. He is a key member of the PEJC 2025 project “Intelligent RoadGuard”, funded by the Tunisian Ministry of Higher Education and Scientific Research. With 71 publications cited over 608 times and an h-index of 16, his work spans hardware acceleration of neural networks, chaos-based cryptosystems, and real-time image processing. Collaborating with over 49 co-authors internationally, his research delivers practical solutions for autonomous systems, secure communications, and smart transportation, impacting both technology and societal safety.

 

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Featured Publications

Zhao Zhao | Computer Vision for Robotics and Autonomous Systems | Research Excellence Award

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Mr. Zhao Zhao | Computer Vision for Robotics and Autonomous Systems | Research Excellence Award

Tianjin University | Canada

Mr. Zhao Zhao is a researcher at Tianjin University specializing in intelligent transportation systems, autonomous mobile robot (AMR) scheduling, and sustainable urban logistics. His work focuses on optimization models integrating energy consumption, time-dependent electricity pricing, and real-world operational constraints. He has published in leading journals including Transportation Research Part C and International Journal of Production Research. Zhao has collaborated with international institutions such as Tsinghua University, Sichuan University, Tilburg University, and KEDGE Business School, and with industry partners including Toyota Tianjin and Hikvision, contributing to large-scale AMR deployment and innovative last-mile delivery solutions with significant societal and sustainability impact.

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Featured Publications


In-plant autonomous mobile robot scheduling and routing problem considering battery consumption model.

– Transportation Research Part C: Emerging Technologies  (2025). Cited By : 1

Steven Sheng-Uei Guan | Machine Learning for Computer Vision | Research Excellence Award

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Prof. Dr. Steven Sheng-Uei Guan | Machine Learning for Computer Vision | Research Excellence Award

Professor | Xi’an Jiaotong-Liverpool University | Australia

Prof. Dr. Steven Sheng Uei Guan is an accomplished researcher at Xi’an Jiaotong-Liverpool University, China, with a Scopus h-index of 25, over 244 publications, and more than 2,362 citations. His research expertise spans human–object interaction detection, graph neural networks, continual learning, human–robot interaction, blockchain-enabled data trading, and intelligent healthcare systems. Dr. Guan has collaborated with over 200 international co-authors, reflecting his strong global research network. His work contributes significantly to advancing artificial intelligence for real-world perception, secure data sharing, and socially beneficial intelligent systems, impacting domains such as robotics, medical informatics, and computational social systems.

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Featured Publications


Encyclopedia of information science and technology.

– IGI Global. (2018). Cited By : 454

Parameter estimation of photovoltaic models via cuckoo search.

-Parameter estimation of photovoltaic models via cuckoo search. (2013). Cited By: 303

An incremental approach to genetic-algorithms-based classification.

-Multimedia Tools and Applications. (2005). Cited By: 124

Investigation of neural networks for function approximation.

– Procedia Computer Science. (2013). Cited By: 111

Riadh Harizi | Deep Learning For Computer Vision | Research Excellence Award

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Dr. Riadh Harizi | Deep Learning For Computer Vision | Research Excellence Award

Teacher | Ecole Nationale d’Ingénieurs de Sfax | Tunisia

Dr. Riadh Harizi is a researcher at the École Nationale d’Ingénieurs de Sfax, Tunisia, with expertise in Machine Learning, Artificial Intelligence, Computer Vision, Deep Learning, and Data Science. He has authored 5 research outputs, receiving 33 citations across 25 citing documents and achieving an h-index of 3. His work spans scene text understanding, reinforcement learning, and AI-driven educational analytics, with publications in Applied Soft Computing, Multimedia Tools and Applications, and leading international conferences. He has collaborated with interdisciplinary teams and contributed an open Latin and Arabic scene character dataset to IEEE Dataport, supporting reproducible research and societal impact in education and intelligent visual systems.

 

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           View ORCID Profile
      View Google Scholar Profile

Featured Publications


Deep-learning based end-to-end system for text reading in the wild.

-Multimedia Tools and Applications. (2022) Cited By: 10

SIFT-ResNet synergy for accurate scene word detection in complex scenarios.

– In Proceedings of the 16th International Conference on Agents and Artificial Intelligence (ICAART) . (2024). Cited By: 3

Divya Nimma | Applications of Computer Vision | Women Researcher Award

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Assist. Prof. Dr. Divya Nimma | Applications of Computer Vision | Women Researcher Award

Assistant Professor | Arkansas Tech University | United States

Dr. Divya Nimma is an accomplished researcher and Assistant Professor at Arkansas Tech University, specializing in Computer Vision, Artificial Intelligence, Image Processing, and Machine Learning. With a strong interdisciplinary footprint, she has contributed extensively to domains spanning environmental monitoring, healthcare analytics, intelligent transportation cybersecurity and immersive technologies. She has published 46 scholarly works and accumulated over 326 citations, with an h-index of 10 and i10-index of 10, underscoring her growing global research influence.Dr. Nimma’s research portfolio reflects a commitment to developing intelligent systems for real-world impact. Her notable contributions include climate-responsive modeling of freshwater ecosystems remote sensing–based marine life assessment for food security transformer-driven object detection , and advanced deep learning frameworks for image forensics and semantic segmentation. She has led and co-authored high-impact studies published in Scientific Reports IEEE Transactions Alexandria Engineering Journal Desalination and Water Treatment Remote Sensing in Earth Systems Sciences and other reputed journals.Her collaborative research spans international teams across the United States  Europe the Middle East  and Asia. Significant works include attention-based models for real-time surveillance explainable AI pipelines for fingerprint recognition IoT-enabled energy management for EV charging predictive maintenance in Industry 4.0 and multisource wearable data analytics for human activity recognition.Dr. Nimma has also made influential contributions to biomedical informatics including cancer detection using optimized deep learning osteoporosis classification and non-invasive brain stimulation–based sleep stage modeling. Additionally her research extends to precision agriculture integrating drone imagery AI and consumer electronics to enhance crop optimization and sustainability.Committed to societal and technological advancement Dr. Nimma’s work demonstrates a unique synthesis of deep learning innovation domain-driven applications and cross-disciplinary collaboration positioning her as a rising scholar and impactful global contributor in modern AI-driven intelligent systems.

Profiles:  Scopus | ORCID | Googlescholar

Featured Publications

1. Nimma, D., Devi, O. R., Laishram, B., Ramesh, J. V. N., Boddupalli, S., Ayyasamy, R., et al. (2025). Implications of climate change on freshwater ecosystems and their biodiversity. Desalination and Water Treatment, 321, 100889. Cited By : 42

2. Srikanth, G., Nimma, D., Lalitha, R. V. S., Jangir, P., Kumari, N. V. S., & Arpita. (2025). Food security-based marine life ecosystem for polar region conditioning: Remote sensing analysis with machine learning model. Remote Sensing in Earth Systems Sciences, 8(1), 65–73. Cited By : 36

3. Nimma, D., Nimma, R., Rajendar, & Uddagiri. (2024). Image processing in augmented reality (AR) and virtual reality (VR). International Journal on Recent and Innovation Trends in Computing and Communication. Cited By : 27

4. Nimma, D., & Zhou, Z. (2024). IntelPVT: Intelligent patch-based pyramid vision transformers for object detection and classification. International Journal of Machine Learning and Cybernetics, 15(5), 1767–1778. Cited By : 25

5. Nimma, D., Nimma, R., & Uddagiri, A. (2024). Advanced image forensics: Detecting and reconstructing manipulated images with deep learning. International Journal of Intelligent Systems and Applications in Engineering.
Cited By : 24

Dr. Divya Nimma’s research advances intelligent vision systems that enhance environmental sustainability, healthcare diagnostics, and smart transportation. Her work integrates AI with real-world applications, driving scientific innovation that strengthens societal resilience and global technological progress.

Nagaraj | Deep Learning for Computer Vision | Excellence in Research

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Dr. P. Nagaraj | Deep Learning for Computer Vision | Excellence in Research

Associate Professor | SRM Institute of Science and Technology  | India 

Dr. P. Nagaraj is an esteemed Associate Professor at the SRM Institute of Science and Technology, Tiruchirappalli, Tamil Nadu, India. With research expertise spanning Artificial Intelligence, Data Science, Data Analytics, Machine Learning, and Recommender Systems, he has made substantial contributions to intelligent computing and healthcare analytics. His innovative work focuses on applying deep learning, fuzzy inference, and explainable AI (XAI) techniques to real-world challenges in medical diagnosis, cybersecurity, and sustainable automation.Dr. Nagaraj has an impressive research portfolio, with over 208 indexed publications, 2,736 citations, and an h-index of 32, reflecting the global relevance and scholarly influence of his work. His notable publications include advancements in diabetes prediction, brain tumor classification, Alzheimer’s disease analysis, and cyberattack detection using AI-driven frameworks. His studies on distributed denial-of-service (DDoS) detection, IoT-based healthcare systems, and intelligent recommendation models have been widely cited and applied across multiple interdisciplinary domains.In recognition of his outstanding research, Dr. Nagaraj has been consecutively listed among the World’s Top 2% Scientists (2023–2025), highlighting his sustained impact in computer science and data-driven innovation. He is also a two-time recipient of the prestigious India AI Fellowship (Ministry of Electronics and Information Technology, MeitY), each worth ₹1 Lakh, for his pioneering projects titled AgriTech of Next-Gen Automation for Sustainable Crop Production and A Deep Learning Approach to Improve Pulmonary Cancer Diagnosis Using CNN.Through collaborations with national and international scholars, Dr. Nagaraj continues to advance the frontier of intelligent data analytics for societal benefit. His research contributes significantly to sustainable digital transformation, healthcare improvement, and agricultural innovation, positioning him as a leading figure in India’s AI research landscape and a global advocate for technology-driven social progress.

Profiles: Google Scholar | ORCID  | Scopus

Featured Publications

1.Sudar, K. M., Beulah, M., Deepalakshmi, P., Nagaraj, P., & Chinnasamy, P. (2021). Detection of distributed denial of service attacks in SDN using machine learning techniques. In Proceedings of the 2021 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1–6). IEEE. Cited By : 158

2.Nagaraj, P., & Deepalakshmi, P. (2022). An intelligent fuzzy inference rule‐based expert recommendation system for predictive diabetes diagnosis. International Journal of Imaging Systems and Technology, 32(4), 1373–1396. Cited By : 100

3.Nagaraj, P., Muneeswaran, V., Reddy, L. V., Upendra, P., & Reddy, M. V. V. (2020). Programmed multi-classification of brain tumor images using deep neural network. In Proceedings of the 2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS) (pp. 1–6). IEEE. Cited By : 85

4.Nagaraj, P., Deepalakshmi, P., & Romany, F. M. (2021). Artificial flora algorithm-based feature selection with gradient boosted tree model for diabetes classification. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy, 14, 2789–2802. Cited By : 79

.5.Nagaraj, P., & Deepalakshmi, P. (2020). A framework for e-healthcare management service using recommender system. Electronic Government, an International Journal, 16(1–2), 84–100. Cited By : 70

Dr. P. Nagaraj’s research advances global innovation by integrating artificial intelligence and data analytics to address critical challenges in healthcare, agriculture, and cybersecurity. His vision is to harness intelligent automation and explainable AI to create sustainable, data-driven solutions that enhance human well-being, industrial efficiency, and societal resilience.

Vasuki | Deep Learning for Computer Vision | Women Researcher Award

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Dr. R. Vasuki | Deep Learning for Computer Vision | Women Researcher Award

Assistant Professor | Mannar Thirumalai Naicker College | India

Dr. R. Vasuki is an Assistant Professor in the Department of Artificial Intelligence at Mannar Thirumalai Naicker College, Madurai. She holds a Ph.D. in Computer Science from Karpagam Academy of Education, along with M.Phil, MCA, and BCA degrees from Bharathidasan University and Cauvery College for Women. She has over fourteen years of academic experience and previously served as an Assistant Professor at Annai Fathima College and as a Website Developer at LM Technologies, Chennai. Her research interests include biometrics, cryptography, database management systems, web development, and artificial intelligence. She has published several papers in reputed international journals and conferences such as IEEE, Springer, and Scopus-indexed publications, with notable work in biometric template protection, image encryption, and machine learning applications. Dr. Vasuki has organized and participated in numerous faculty development programs, workshops, and seminars, and has contributed as a reviewer for reputed journals. She received the first prize for a paper presentation from the Madurai Productivity Council and has authored a book titled Internet of Things along with a book chapter on conversational AI applications. Her research skills include data analysis, model optimization, and AI-driven system development, supported by certifications in deep learning, cybersecurity, and cloud computing. She actively mentors students in technical skill development and promotes innovation in higher education. Her research has received 1 citation by 3 documents with an h-index of 1.

Profile: Scopus

Featured Publications

1. Vasuki, R. (2024). Iris biometric template identification and recognition scheme using a novel parallel fused encoder.

 

Xinrong Hu | Object Detection and Recognition | Women Researcher Award

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Prof. Xinrong Hu | Object Detection and Recognition | Women Researcher Award

Dean of Computer Science and Artificial Intelligence | Wuhan Textile University | China

Prof. Xinrong Hu is a distinguished researcher and academic leader in computer vision, natural language processing, virtual reality, and machine learning. She serves as Dean of the School of Computer and Artificial Intelligence at Wuhan Textile University and is a doctoral supervisor, leading an innovative research team at the Hubei Provincial Engineering Technology Research Center for Garment Informatization. She holds a Ph.D. and has extensive experience in guiding research projects, including over 30 funded initiatives, some with national and international significance. Her research interests focus on advancing artificial intelligence applications in real-world scenarios, combining theoretical innovation with practical solutions. She has authored more than 100 academic papers, edited six textbooks, translated a book, and holds 26 invention patents, demonstrating her strong research skills and contribution to knowledge dissemination. Prof. Hu has been recognized with multiple awards and honors, including provincial and ministerial-level scientific research awards, teaching achievement awards, and prestigious titles such as Hubei Provincial Distinguished Teacher and recipient of the Special Government Allowance from the State Council. Her professional engagement includes leadership in academic communities, mentorship of young researchers, and active participation in advancing the field of AI through both education and research initiatives. Her comprehensive expertise, innovative contributions, and dedication to fostering academic excellence make her a leading figure in her field. Her research impact is reflected in 1,044 citations, 209 documents, and an h-index of 16.

Profiles: Scopus | ResearchGate 

Featured Publications

  1. Hu, X., et al. (2025). CDPMF-DDA: Contrastive deep probabilistic matrix factorization for drug-disease association prediction. BMC Bioinformatics.

  2. Hu, X., et al. (2025). Source-free cross-modality medical image synthesis with diffusion priors. Journal of King Saud University – Computer and Information Sciences.

  3. Hu, X., et al. (2025). TADUFMA: Transformer-based adaptive denoising and unified feature modeling for multi-condition anomaly detection in computerized flat knitting machines. Measurement Science and Technology.

  4. Hu, X., et al. (2025). ViT-BF: Vision transformer with border-aware features for visual tracking. Visual Computer.

  5. Hu, X., et al. (2025). Adaptive debiasing learning for drug repositioning. Journal of Biomedical Informatics.

Osman Yildirim | Deep Learning | Best Researcher Award

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Prof. Osman Yildirim | Deep Learning | Best Researcher Award

Head of the Department | Istanbul Aydın University | Turkey 

Prof. Osman Yildirim is a distinguished academic and researcher recognized for his contributions at the intersection of engineering, business, sustainability, and biomedical applications. He holds dual doctoral degrees in Engineering and Business Administration, a unique combination that has enabled him to approach research challenges with a strong interdisciplinary perspective. Over the course of his career, he has taken on significant academic leadership roles, including serving as Head of Department at Istanbul Aydin University, while also guiding doctoral students and fostering collaborative research projects. His professional experience spans teaching across engineering and business disciplines, coordinating research initiatives, and contributing to institutional development through mentorship and administrative leadership. His primary research interests focus on green transformation, sustainable supply chains, carbon policy impacts, energy management systems in universities, and AI-based medical imaging applications for improved diagnostics. These areas reflect his commitment to aligning research with both technological advancements and societal needs, particularly in the context of sustainable development and healthcare innovation. He has published widely in reputed Q1 and Q2 indexed journals such as Scopus and SCI, showcasing the impact of his work in both technical and applied fields. His achievements have been recognized through awards and honors that acknowledge his contributions to advancing interdisciplinary research and education. In addition, he has built valuable collaborations with international teams, integrating expertise from engineering, business, and medicine to deliver impactful solutions with global relevance. His research skills include expertise in machine learning, AI-driven image analysis, sustainable system design, and computational modeling for optimization under carbon constraints. These technical strengths, combined with his leadership and mentorship, position him as a leading scholar dedicated to advancing academic excellence and addressing global challenges through innovative and socially relevant research.

Profile: Google Scholar | Scopus Profile | ORCID Profile

Featured Publications

Ozturk, A. I., Yıldırım, O., İdman, E., & İdman, E. (2025). A comparative study of hybrid decision tree–deep learning models in the detection of intracranial arachnoid cysts. Neuroscience Informatics, 100234.

Ozturk, A. I., Yildirim, O., Kaygusuz, K., Idman, E., & Idman, E. (2025). Brain cyst detection using deep learning models. International Journal of Innovative Research and Scientific Studies, 8(5), 8974.

Borhan Elmi, M. M., & Yıldırım, O. (2025). Improve MPPT in organic photovoltaics with chaos-based nonlinear MPC. Balkan Journal of Electrical and Computer Engineering, 13(1), 1418574.

Ozturk, A. I., Yıldırım, O., & Deryahanoglu, O. (2025). A comprehensive strategy for the identification of arachnoid cysts in the brain utilizing image processing segmentation methods. International Journal of Innovative Technology and Exploring Engineering, 14(2), 1031.

Borhan Elmi, M. M., & Yıldırım, O. (2024). Improve LVRT capability of organic solar arrays by using chaos-based NMPC. International Journal of Energy Studies, 4(3), 1449558.

Yildirim, O., Khaustova, V. Y., & Ilyash, O. I. (2023). Reliability and validity adaptation of the hospital safety climate scale. The Problems of Economy, 4(1), 207–216.

Yildirim, O. (2023). Multidimensional and strategic outlook in digital business transformation: Human resource and management recommendations for performance improvement. In Book chapter.

Yildirim, O. (2023). Health professionals’ perspective in the context of social media, paranoia, and working autonomy during the COVID-19 pandemic period. Archives of Health Science Research, 10(1), 30–37.

Yildirim, O. (2023). The personified model for supply chain management. In Multidimensional and strategic outlook in digital business transformation: Human resource and management recommendations for performance improvement.

Yildirim, O., Ilyash, O. I., Khaustova, V. Y., & Celiksular, A. (2022). The effect of emotional intelligence and work-related strain on the employee’s organizational behavior factors. The Problems of Economy, 2(1), 124–131.

Yildirim, O. (2022). Investigation of the electrical conductivity of pernigranilin with carbon monoxide and nitrogen monoxide doping. Mathematical Statistician and Engineering Applications, 9(4).

Yildirim, O. (2022). Cyst segmentation using filtering technique in computed tomography abdominal kidney images. Mathematical Statistician and Engineering Applications, 9(4).

Yildirim, O. (2022). Design of flyback converter by obtaining the characteristics of polymer based R2R organic PV panels. International Journal of Renewable Energy Research, 12(4).

Avdullahi, A., & Yildirim, O. (2021). The mediating role of emotional stability between regulation of emotion and overwork. In Book chapter.

Tunç, P., Yıldırım, O., Göktepe, E. A., & Çapuk, S. (2021). Investigation of the relationship between personality, organizational identification and turnover in competitive flight model. TroyAcademy, 6(1), 894141.

Tunç, P., Yıldırım, O., Göktepe, E. A., & Çapuk, S. (2021). Investigation of the relationship between personality, organizational identification and turnover in competitive flight model. Çanakkale Onsekiz Mart Üniversitesi Uluslararası Sosyal Bilimler Dergisi, 4(1), 804959.

Puja Gupta | Computer Vision | Excellence in Research

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Dr. Puja Gupta | Computer Vision | Excellence in Research

Asst Professor at Shri G.S. Institute of Technology & Science | India

Dr. Puja Gupta is a dedicated researcher and academic with expertise in artificial intelligence, machine learning, IoT, and smart computing technologies. She has contributed significantly to the field through her high-quality publications in reputed journals, patents, and innovative product development. Her work has addressed real-world challenges in healthcare, security, and sustainable technologies, bridging the gap between research and practical applications. With a strong academic foundation, she has successfully guided students in research and projects, fostering innovation and academic growth. She has been actively involved in international collaborations, research projects, and academic leadership roles, contributing to the advancement of her field. She is also a committed member of professional organizations, demonstrating her engagement in the broader research community. Her impactful contributions, leadership potential, and dedication to continuous professional development make her a valuable asset to both academia and society.

Professional Profile 

Google Scholar | Scopus Profile | ORCID Profile 

Education

Dr. Puja Gupta holds a strong academic background in computer science and engineering, culminating in a doctoral degree specializing in artificial intelligence and smart systems. Her Ph.D. research focused on the integration of machine learning techniques and IoT frameworks to design intelligent solutions that address complex societal problems. Prior to her doctoral studies, she earned her master’s and bachelor’s degrees in computer science, gaining a solid foundation in algorithms, data structures, and system design. Throughout her academic journey, she demonstrated exceptional commitment to learning, consistently achieving top ranks and recognition for her research contributions. Her advanced education has equipped her with in-depth knowledge of computational intelligence, optimization techniques, and applied research methodologies, enabling her to contribute effectively to both theoretical advancements and practical applications in the field. Her academic background continues to support her innovative research and teaching excellence in the areas of AI, IoT, and emerging technologies.

Professional Experience

Dr. Puja Gupta has extensive professional experience in both academic and research domains, with a focus on artificial intelligence, IoT, and smart computing solutions. She has worked as a faculty member at prestigious institutions, where she has taught and mentored students at undergraduate and postgraduate levels, guiding them in research projects and fostering innovation. Alongside teaching, she has been actively involved in funded research projects, many of which involved international collaborations and multidisciplinary teams. She has successfully published her findings in reputed journals and conferences indexed in IEEE and Scopus, and her work has also resulted in patents and prototypes with practical applications. Beyond academia, she has contributed to the research community by serving as a reviewer, participating in editorial activities, and organizing academic events. Her leadership roles in academic programs and community-driven initiatives further highlight her commitment to advancing knowledge and supporting the development of future researchers.

Research Interest

Dr. Puja Gupta’s research interests revolve around artificial intelligence, machine learning, IoT, big data analytics, and smart system design. She is particularly focused on developing intelligent solutions that address pressing societal challenges in areas such as healthcare, security, and sustainability. Her work often integrates computational intelligence with real-world applications, such as predictive healthcare models, smart monitoring systems, and secure communication frameworks for IoT devices. She is also keen on advancing research in explainable AI and optimization algorithms to ensure reliability and transparency in machine learning systems. Another area of interest is the development of resource-efficient AI models for deployment in edge and cloud environments. Her multidisciplinary approach allows her to collaborate across domains, leveraging data-driven techniques to innovate practical solutions. By combining theoretical knowledge with applied research, she aims to contribute to technological advancements that enhance the quality of life and create sustainable, impactful outcomes for society.

Award and Honor

Dr. Puja Gupta has been recognized with numerous awards and honors that highlight her academic excellence, research contributions, and leadership in the field of computer science and engineering. Her achievements include recognition for publishing impactful research in reputed journals, presenting at leading international conferences, and securing patents that demonstrate the practical value of her work. She has also been honored for her contributions to student mentoring and academic program development, reflecting her dedication to nurturing young talent. Several of her awards acknowledge her innovative approaches in AI and IoT research, particularly for developing solutions with direct societal impact. In addition, she has received appreciation for her involvement in community-driven initiatives and leadership in professional organizations. These honors not only recognize her past accomplishments but also serve as a testament to her commitment, perseverance, and ability to inspire others in the academic and research communities.

Research Skill

Dr. Puja Gupta possesses advanced research skills in artificial intelligence, machine learning, IoT systems, and computational modeling, enabling her to conduct impactful and interdisciplinary research. She is proficient in applying data analysis techniques, optimization algorithms, and predictive modeling to design intelligent solutions for real-world applications. Her expertise includes working with various programming languages, simulation tools, and research frameworks that support scalable and innovative problem-solving. She has developed strong skills in experimental design, result validation, and research dissemination through high-quality publications and conference presentations. Beyond technical expertise, she excels in collaborative research, often working with international teams and multidisciplinary groups to drive innovation. She is also skilled in project management, proposal writing, and securing research funding, which have been instrumental in the successful execution of her projects. Her research skills, combined with her commitment to continuous learning, position her as a versatile and resourceful academic and researcher in her field.

Publications Top Notes

Title: Impact of knowledge management practices on innovative capacity: A study of telecommunication sector
Authors: J Jyoti, P Gupta, S Kotwal
Year: 2011
Citation: 56

Title: A Novel Algorithm for Mask Detection and Recognizing Actions of Human
Authors: P Gupta, V Sharma, S Varma
Year: 2022
Citation: 48

Title: Transcriptional mechanisms underlying sensitization of peripheral sensory neurons by granulocyte-/granulocyte-macrophage colony stimulating factors
Authors: KK Bali, V Venkataramani, VP Satagopam, P Gupta, R Schneider, …
Year: 2013
Citation: 42

Title: Minimally invasive plate osteosynthesis (MIPO) for proximal and distal fractures of the tibia: a biological approach
Authors: P Gupta, A Tiwari, A Thora, JK Gandhi, VP Jog
Year: 2016
Citation: 41

Title: SUMOylation of enzymes and ion channels in sensory neurons protects against metabolic dysfunction, neuropathy, and sensory loss in diabetes
Authors: N Agarwal, FJ Taberner, DR Rojas, M Moroni, D Omberbasic, C Njoo, …
Year: 2020
Citation: 39

Title: An introduction of soft computing approach over hard computing
Authors: P Gupta, N Kulkarni
Year: 2013
Citation: 31

Title: People detection and counting using YOLOv3 and SSD models
Authors: P Gupta, V Sharma, S Varma
Year: 2021
Citation: 30

Title: Challenges in the adaptation of IoT technology
Authors: Neha, P Gupta, MA Alam
Year: 2021
Citation: 20

Title: Role of fine needle aspiration cytology in preoperative diagnosis of ameloblastoma
Authors: S Bisht, SA Kotwal, P Gupta, R Dawar
Year: 2009
Citation: 13

Title: Let the Blind See: An AIIoT based device for real-time object recognition with the voice conversion
Authors: P Gupta, M Shukla, N Arya, U Singh, K Mishra
Year: 2022
Citation: 9

Title: The impact of artificial intelligence on renewable energy systems
Authors: P Gupta, S Kumar, YB Singh, P Singh, SK Sharma, NK Rathore
Year: 2022
Citation: 8

Title: Simultaneous feature selection and clustering of micro-array and RNA-sequence gene expression data using multiobjective optimization
Authors: AK Alok, P Gupta, S Saha, V Sharma
Year: 2020
Citation: 8

Title: Activity detection and counting people using mask-RCNN with bidirectional ConvLSTM
Authors: P Gupta, U Singh, M Shukla
Year: 2022
Citation: 7

Title: Study of cloud providers (azure, amazon, and oracle) according to service availability and price
Authors: A Rajput, P Gupta, P Ghodeshwar, S Varma, KK Sharma, U Singh
Year: 2023
Citation: 6

Title: Machine learning approaches for IoT-data classification
Authors: O Farooq, P Gupta
Year: 2020
Citation: 5

Title: Evaluation of AI system’s voice recognition performance in social conversation
Authors: SK Barnwal, P Gupta
Year: 2022
Citation: 4

Title: Analysis of CNN Model with Traditional Approach and Cloud AI based Approach
Authors: U Kushwaha, P Gupta, S Airen, M Kuliha
Year: 2022
Citation: 4

Title: Analysis of crowd features based on deep learning
Authors: P Gupta, V Sharma, S Varma
Year: 2022
Citation: 4

Title: Acknowledgment of patient in sense behaviors using bidirectional ConvLSTM
Authors: U Singh, P Gupta, M Shukla, V Sharma, S Varma, SK Sharma
Year: 2023
Citation: 3

Title: Study on the NB-IoT based smart medical system
Authors: P Gupta, AK Pandey
Year: 2023
Citation: 3

Conclusion

Dr. Puja Gupta is highly deserving of the Best Researcher Award for her significant contributions to advancing research in artificial intelligence, IoT, and smart technologies, as well as her role in mentoring students and fostering innovation. Her impactful work, including patents, high-quality publications, and practical product development, has addressed societal challenges in healthcare, security, and sustainability. With her strong academic background, leadership in academic and community initiatives, and commitment to continuous growth, she holds great potential to further excel in future research, expand global collaborations, and take on greater leadership roles in the academic and research community.