Preeti Sharma | Deep Learning | Women Researcher Award

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.

Fatemeh Golpayegani | Artificial Intelligence | Best Researcher Award

Dr. Fatemeh Golpayegani | Artificial Intelligence | Best Researcher Award 

Assistant Professor | University College Dublin | Ireland

📜 Short Bio:

Fatemeh Golpayegani is currently an Assistant Professor at the School of Computer Science, University College Dublin (UCD), where she contributes significantly to research and academic activities in the field of computer science. Her expertise lies in multi-agent systems, edge computing, and intelligent transport systems.

Profile:

SCOPUS

🎓 Education:

Fatemeh pursued her academic journey with a strong foundation in computer science:

  • Ph.D. in Computer Science (2013-2018)
    Trinity College Dublin, Dublin, Ireland
    Thesis Title: “Collaboration community formation in open systems for agents with multiple goals.”
    Supervised by Prof. Siobhan Clarke.
  • M.Sc. in Computer (Software) Engineering (2010-2012)
    Sharif University of Technology, Tehran, Iran
    Thesis Title: “Development of a process line engineering approach based on product line engineering methods for engineering agent-oriented methodologies.”
  • B.Sc. Hons in Computer (Software) Engineering (2006-2010)
    Alzahra University, Tehran, Iran

👩‍🏫 Experience:

Fatemeh has held various academic and professional roles:

  • Assistant Professor (Dec 2020 – Present)
    School of Computer Science, UCD, Dublin, Ireland
  • Postdoctoral Researcher (June 2018 – Jan 2019)
    CONNECT, School of Computer Science and Statistics, Trinity College Dublin, Ireland
  • Software Engineer (Sept 2010 – Aug 2013)
    ITOrbit, Tehran, Iran

🔍 Research Interest:

Her research interests encompass:

Multi-agent Systems, Edge Computing, Intelligent Transport Systems, Agent-based Modeling

🏆 Award:

Fatemeh Golpayegani is recognized as a member of the Young Academy of Ireland (2023-2027), highlighting her contribution to advancing research and cultural life in Ireland.

📚 Publications:

Fatemeh has contributed significantly to her field with numerous peer-reviewed publications. A selection of her notable works include:

Adaptation in Edge Computing: A review on design principles and research challenges
Published in ACM Transactions on Autonomous and Adaptive Systems, 2024. Cited by: 15

Handling uncertainty in self-adaptive systems: an ontology-based reinforcement learning model
Published in Journal of Reliable Intelligent Environments, 2023. Cited by: 20

Towards the Use of Hypermedia MAS and Microservices for Web Scale Agent-Based Simulation
Published in SN Computer Science, 2022.

Intelligent Shared Mobility Systems: A Survey on Whole System Design Requirements, Challenges and Future Direction
Published in IEEE Access, 2022.

Using Social Dependence to Enable Neighbourly Behaviour in Open Multi-agent Systems
Published in ACM Transactions on Intelligent Systems and Technology (TIST), 2019.

These publications underscore her research breadth and impact in areas such as adaptive systems, shared mobility, and multi-agent collaboration.

 

Ayesheh Enayati | neurosciences | Excellence in Research

Dr. Ayesheh Enayati | neurosciences | Excellence in Research

assistant professor, Golestan University of Medical Sciences, Iran

Ayesheh Enayati holds a Ph.D. in Pharmacognosy from Tehran University of Medical Sciences and specializes in cardiovascular research, phytochemistry, and biotechnology. Currently based at Golestan University of Medical Sciences, she conducts research on natural products and their applications in cardiovascular health and tissue engineering.

Profile

Google Scholar

 

🎓 Education:

Ayesheh Enayati completed her Doctor of Pharmacognosy at Tehran University of Medical Sciences, Tehran, Iran. She also holds a Master of Science in Phytochemistry and a Bachelor of Science in Chemistry.

🔬 Experience:

With extensive research experience, Ayesheh conducted her doctoral thesis research at both Tehran University of Medical Sciences and Golestan University of Medical Sciences, focusing on pharmacognosy and pharmacological experiments using the Langendorff perfusion system. She serves as Director and Secretary of the STE-MI Registry Committee at the Ischemic Disorders Research Center.

🔍 Research Interests:

Her research interests span phytochemistry, natural products, cardiovascular research, biotechnology, and heart tissue engineering.

 

📚 Publications:

Roselle (Hibiscus sabdariffa L.) extract as an adjunct to valsartan in patients with mild chronic kidney disease: A double-blind randomized controlled clinical trial (2024, Avicenna Journal of Phytomedicine)

Potential antiplatelet agents with grape seed–backbone polyphenols: computational studies (2024, Natural Product Research)

Effect of Pistacia genus on gastrointestinal tract disorders: A systematic and comprehensive review (2024, Fitoterapia)

LC–MS/MS phytochemical profiling, antioxidant activity, and enzyme inhibitory of Potentilla reptans L. root: Computational studies and experimental validation (2024, Process Biochemistry)

A comprehensive review of scientific evidence of Daucus carota L. plant from the viewpoints of Persian Medicine and Current Medicine: A review study (2023, Journal of Islamic and Iranian Traditional Medicine)

Neuroprotective effect of Potentilla reptans L. root in the rat brain global ischemia/reperfusion model (Year not specified, Journal not specified)