Hussain Ahmad | Software Engineering | Best Researcher Award

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Mr. Hussain Ahmad | Software Engineering | Best Researcher Award

PhD Student at The University of Adelaide, Australia

πŸ›‘οΈ Hussain Ahmad is a cybersecurity and software engineering expert with a strong background in cloud computing, machine learning, robotics, and autonomous systems. Currently pursuing a PhD at the University of Adelaide (2021-2025), his research focuses on self-adaptive cybersecurity and software scalability. He has led 15+ R&DI projects, published 10 high-impact papers with 500+ citations, and secured AUD 200k+ in funding from Google, Amazon, and Cyber Security CRC. A Professional Electronics Engineer (Engineers Australia), he has supervised 12+ students and received the Outstanding International Student Award. His industry roles include Cyber Security Engineer, Chief Project Officer (Migrova), and Software Engineer (Kindship). πŸŒπŸ”πŸ€–

 

Publication Profile

Scopus

 

πŸŽ“ Education

Hussain Ahmad is currently pursuing a Doctor of Philosophy (PhD) in Cybersecurity and Software Engineering at The University of Adelaide, Australia (2021-2025). His research focuses on self-adaptive cybersecurity and software scalability, under the supervision of Claudia Szabo, Christoph Treude, and Markus Wagner. Prior to this, he earned a Bachelor of Science in Electronic Engineering (2013-2017) from Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Pakistan, achieving a High Distinction. His bachelor’s degree is accredited by Engineers Australia, reflecting his strong foundation in electronic engineering and advanced computing systems. πŸ“‘πŸ”πŸ“Š

 

πŸ’Ό Work Experience

Hussain Ahmad is an R&D Scholar in Software Security & Scalability at The University of Adelaide (2021-2025), leading 15+ R&DI projects at the intersection of Cybersecurity, Software Engineering, and Machine Learning, with high-impact findings published in leading journals. As a Research Supervisor (2022-2025), he mentors students on industry-focused R&DI projects in collaboration with CSIRO’s Data61, Migrova, and Schlumberger. He also serves as Chief Project Officer at Migrova (2023-2024), securing AUD 100k for AI-driven cybersecurity solutions. Additionally, he developed an ML-enabled therapist recommendation engine as a Software Engineer at Kindship (2022-2023). πŸ”πŸ’»πŸš€

 

πŸ† Awards & Achievements

Hussain Ahmad has received numerous prestigious accolades for his contributions to R&DI, cybersecurity, and academic excellence. He was featured in a leading newspaper and honored with the Outstanding International Student Award at The University of Adelaide. He won the Exceptional HDR Representative Award and secured People’s Choice & Second Place in the 2024 Visualise Your Thesis Competition. His achievements include a Google Cloud Grant, AUD 100k Seed-Start grant, and three RTP Scholarships. Additionally, he is an accredited Professional Electronics Engineer, a recipient of six Dean’s Excellence Awards, and was awarded a GIKI Fully Funded Financial Assistance Award. πŸ…πŸ”¬πŸš€

 

πŸ” Research Focus

 

Hussain Ahmad’s research primarily focuses on cybersecurity, software engineering, and microservice architectures. His work on Microservice Vulnerability Analysis in IEEE Access (2024) highlights security risks, threat modeling, and empirical insights into software vulnerabilities. His expertise extends to self-adaptive cybersecurity, cloud computing, machine learning, and autonomous systems. With multiple high-impact publications and industry collaborations, he contributes to secure software scalability, cyber defense mechanisms, and AI-driven security solutions. His interdisciplinary approach bridges software security, electronic engineering, and automation, making him a key researcher in next-generation secure computing systems. πŸ”πŸ’»πŸ“‘

 

Publication Top Notes

1️⃣ A Review on C3I Systems’ Security: Vulnerabilities, Attacks, and Countermeasures – ACM Computing Surveys, 2023 πŸ†Β 
2️⃣ Smart HPA: A Resource-Efficient Horizontal Pod Auto-scaler for Microservice Architectures – ICSA, 2024 πŸ†Β 
3️⃣ Towards Resource-Efficient Reactive and Proactive Auto-scaling for Microservice Architectures – Journal of Systems and Software, 2024 πŸ†Β 
4️⃣ Microservice Vulnerability Analysis: A Literature Review with Empirical Insights – IEEE Access, 2024 πŸ†Β 
5️⃣ Towards Deep Learning Enabled Cybersecurity Risk Assessment for Microservice Architectures – Cluster Computing, 2024 πŸ†
6️⃣ A Survey on Immersive Cyber Situational Awareness Systems – Submitted to IEEE Access, 2024 πŸ† πŸ›‘οΈ
7️⃣ ChatNVD: Advancing Cybersecurity Vulnerability Assessment with Large Language Models – 2024 πŸ†
8️⃣ Machine Learning Driven Smishing Detection Framework for Mobile Security – Submitted to Cluster Computing, 2024 πŸ†Β 
9️⃣ What Skills Do Cyber Security Professionals Need? – Submitted to Neurocomputing, 2025 πŸ†Β 
πŸ”Ÿ Exploring Sentiments of ChatGPT Early Adopters using Twitter Data – 2023 πŸ†

 

 

 

Erika LoučanovÑ | Digital Transformation | Best Researcher Award

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Assoc. Prof. Dr. Erika LoučanovÑ | Digital Transformation | Best Researcher Award

Assoc. Prof., Technical Unversity in Zvolen, Slovakia

Assoc. Prof. Dr. Erika LoučanovΓ‘ is a researcher and educator specializing in innovation management and eco-innovation 🌱. She serves as an Associate Professor at the Technical University of Zvolen and has over two decades of experience in academia πŸ“š. Holding a PhD in Sectoral and Cross-Sectional Economics, her work focuses on sustainable business strategies and industrial innovation. She has authored 320+ publications πŸ“ and contributed to major scientific projects.

Publication Profile

Orcid

πŸŽ“ Education & Academic Qualifications

Assoc. Prof. Dr. Erika LoučanovΓ‘ has a strong academic background in economics and business management πŸ“š. In 2021, she attained the title of Associate Professor at the University of Ε½ilina, specializing in Sectoral and Cross-Sectional Economics πŸ“Š. She earned her PhD (2007) from the Technical University of Zvolen, focusing on innovation in the woodworking industry πŸ—οΈ. Earlier, she completed her Engineering degree (2004) in Wood Engineering – Business Management 🏒. Her academic journey began at the Business Academy Ε½iar nad Hronom (1999), where she graduated with a strong foundation in business studies πŸ’Ό.

 

πŸ† Skills & Certifications

Assoc. Prof. Dr. Erika LoučanovΓ‘ possesses strong organizational, analytical, and communication skills πŸ—‚οΈ, honed through scientific projects, research management, and conference organization 🎀. She is proficient in digital tools πŸ’», including Microsoft Office, STATISTICA, and Adobe Acrobat Reader. Her work ethic is defined by reliability, flexibility, and leadership 🀝. She holds multiple certifications πŸ“œ, including Managing Innovation (2024, UNIDO, Austria), Business and Law (2022, PalackΓ½ University), and Tax Law (2023, PalackΓ½ University). Additionally, she has expertise in public health protection πŸ₯ and has undergone training in cluster management and bookkeeping πŸ“Š. Fluent in English, she actively engages in scientific collaboration 🌍.

Research Focus

Erika LoučanovΓ‘’s research primarily focuses on eco-innovation, sustainable development, and business models for digital transformation and smart services. πŸŒ±πŸ’‘ Her work explores strategic environmental consumer segmentation, AI in innovation processes, and financial sustainability in pension systems. πŸ“ŠπŸ‘ She has contributed significantly to ecological innovation in Slovakia, including perceptions of wood-based structures and eco-services innovations in the furniture industry. πŸ—οΈπŸŒ³ Additionally, she examines innovation in banking, management education, and public smart services for sustainability. πŸ¦πŸŽ“ Her research integrates economic, environmental, and technological perspectives, making substantial contributions to green business strategies and digital innovation. πŸŒπŸ“ˆ

Publication Top Notes

  • “Digital Transformation in Higher Education Institutions as a Driver of Social Oriented Innovations” (2022) – Cited by 3

  • “Innovation as a Tool for Sustainable Development in Small and Medium Size Enterprises in Slovakia” (2023) – Cited by 6

  • “The Perception of Respondents of Intelligent Packaging in Slovakia as Ecological Innovations” (2019) – Cited by 5

  • “Supporting Ecological Innovation as a Factor for Economic Development” (2019)

  • “Perception of packaging functions and the interest in intelligent and active packaging in terms of age” (2018)

  • Hodnotenie stavu udrΕΎateΔΎnosti krajΓ­n EÚ (2022) Β πŸŒβ™»οΈ

  • ObchodnΓ© praktiky aplikovanΓ© voči spotrebiteΔΎom a ich prΓ‘vam na slovenskom trhu z pohΔΎadu etiky (2022) Β βš–οΈπŸ›’

  • Perception of Supplied Furniture and Its Innovation by Slovak Customers (2022)  🏠✨

  • The Relationship of Innovation and the Performance of Business Logistics in the EU (2022) Β πŸššπŸ“ˆ

  • Crowdfunding as a Way of the Monetary and Financial Ecologies (2021) Β πŸ’°πŸŒ±

  • Ecological Innovations in Services – Servitization of Furniture (2021)Β πŸŒ³πŸ›‹οΈ

  • Perception of Zero Waste in the Context of Environmental Innovation in Slovakia (2021) 🌿🚯

  • Positive Effects of the Forest on the Human Organism in the Context of Ecological Innovations and Modern Medicine (2021) 🌲❀️

  • Practices of Innovative Marketing Communication Tools in Furniture Sector (2021) Β πŸ“’πŸͺ‘

Sheng Ye | Computer Science | Best Researcher Award

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Sheng Ye | Computer Science | Best Researcher Award

Mr Sheng Ye, Tsinghua University, China

Mr. Sheng Ye πŸŽ“ is a talented researcher in advanced computer science, specializing in deep learning and computer vision. Graduating in the top 15% from Tsinghua University with a GPA of 3.89/4.0, under the guidance of Prof. Liu Yongjin, he quickly established himself as a promising talent. His award-winning project on real-time video stylization πŸ… received the β€œBest Practice Award” from Kuaishou and Tsinghua University, and he has been honored with multiple scholarships, including the prestigious β€œJiukun Scholarship.” Known for his impactful publications πŸ“‘ and contributions to academic conferences, Mr. Sheng Ye is well-positioned to excel in research.

Publication Profile

Scopus

Education Background πŸŽ“

The candidate holds a strong academic record in advanced computer science, focusing on deep learning and computer vision. Graduating among the top 15% from Tsinghua University with a GPA of 3.89/4.0, they were supervised by Prof. Liu Yongjin. Recognized as an exemplary graduate, their academic achievements reflect a dedication to excellence. Early accolades include ranking within the top 10 of their grade and excelling in the national entrance exam with a score of 703. This foundation underlines their exceptional knowledge base and capability in scientific research.

Research Focus and Achievements πŸ”¬

The candidate’s research spans innovative deep learning techniques and computer vision applications. A notable project on real-time video stylization was awarded the “Best Practice Award” by Kuaishou and Tsinghua University. Additional distinctions include winning first prize at the 16th Image and Graphics Technology and Applications Conference (IGTA). Their publication record is further strengthened by multiple scholarship awards and recognitions, including the prestigious β€œTsinghua Friends – Jiukun Scholarship” in 2022–2023. This research-oriented focus positions the candidate as a strong contender for the Best Researcher Award.

Professional Experience and Contributions πŸ’Ό

Through internships and student roles, the candidate has significantly impacted Tsinghua’s computing community. Leading publicity efforts in the computer science department, they manage the β€œJiXiaoYan” public account, curating content across various academic themes. Their professional involvement also extends to reviewing for prominent conferences and journals like CVPR, AAAI, NeurIPS, and ECCV. This experience illustrates their commitment to academic development and a thriving research community.

Key Publications πŸ“‘

  • 2024: DiffPoseTalk: Speech-Driven Stylistic 3D Facial Animation – ACM Transactions on Graphics, 43(4) πŸ“Š
  • 2024: O2-Recon: 3D Reconstruction of Occluded Objects – AAAI Conference on AI, 38(3) πŸ–ΌοΈ
  • 2024: Online Exhibition Halls with Virtual Agents – Journal of Software, 35(3) 🌐
  • 2024: Fine-Grained Indoor Scene Reconstruction – IEEE Transactions on Visualization πŸ“
  • 2023: Virtual Digital Human for Customer Service – Computers and Graphics, 115 🎭
  • 2022: Audio-Driven Gesture Generation – Lecture Notes in Computer Science, 13665 🎢

Publication Top Notes

DiffPoseTalk: Speech-Driven Stylistic 3D Facial Animation and Head Pose Generation via Diffusion Models

O2-Recon: Completing 3D Reconstruction of Occluded Objects in the Scene with a Pre-trained 2D Diffusion Model

Indoor Scene Reconstruction with Fine-Grained Details Using Hybrid Representation and Normal Prior Enhancement

Generation of virtual digital human for customer service industry

Audio-Driven Stylized Gesture Generation with Flow-Based Model

Conclusion πŸ†

The candidate’s robust educational background, innovative research, and active participation in academic communities distinguish them as a prime candidate for the Best Researcher Award. With numerous accolades, impactful publications, and a track record of community engagement, they are set to make meaningful contributions to the fields of deep learning and computer vision.

K ASHWINI | Computer Science | Best Researcher Award

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K ASHWINI | Computer Science | Best Researcher Award

K ASHWINI, National Institute of Technology Rourkela, India

K. Ashwini is a dedicated Ph.D. candidate in Computer Science and Engineering at NIT Rourkela, specializing in deep learning applications for grading diabetic retinopathy. She holds an M.Tech. from VSSUT Burla and a B.Tech. from Synergy Institute of Engineering & Technology, Dhenkanal. Her research includes notable publications, such as her work on CNN-based diabetic retinopathy grading in Biomedical Signal Processing and Control. Skilled in Python, MATLAB, and LaTeX, she has actively participated in workshops on machine learning and signal processing. Ashwini is fluent in Hindi, Telugu, and English.

Publication profile

google scholar

Academic Background

Ms. K. Ashwini is a Research Scholar in Computer Science and Engineering (CSE) at NIT Rourkela, currently pursuing her Ph.D., with her research focused on diabetic retinopathy grading using deep learning techniques. Her advanced studies in deep learning, combined with an M.Tech. in CSE from VSSUT Burla, highlight her dedication to exploring complex topics within biomedical and computational research. She has maintained a strong academic record throughout her studies, underscoring her commitment and expertise in her field.

Research Focus and Publications

Ashwini’s primary research area is in biomedical signal processing, specifically targeting diabetic retinopathy grading using CNNs and soft attention mechanisms. She has contributed a journal article to Biomedical Signal Processing and Control and presented multiple conference papers at reputable IEEE and Springer conferences, indicating her active participation in disseminating her research findings. Notably, her publications demonstrate her capacity to employ and innovate with advanced computational methods for impactful health-related applications, a relevant focus for this award.

Technical Skills and Training

Her technical skill set, including Python, MATLAB, and LaTeX, complements her research competencies. Ashwini’s training in SQL and experience with clustering and fraud detection in mobile networks contribute to a robust and versatile research portfolio. Her academic research skills and fluency in programming languages further solidify her qualifications as a proficient researcher in her domain.

Workshops and Professional Development

Ms. Ashwini has participated in several workshops and short-term training programs across India, including those focused on biomedical signal processing, machine learning, and image processing applications. Her engagement in diverse professional development initiatives, such as faculty development programs and national seminars, showcases her continuous effort to enhance her knowledge base and technical skills.

Publication top notes

Grading diabetic retinopathy using multiresolution based CNN

Soft attention with convolutional neural network for grading diabetic retinopathy

Application of Generalized Possibilistic Fuzzy C-Means Clustering for User Profiling in Mobile Networks

Improving Diabetic Retinopathy grading using Feature Fusion for limited data samples

An intelligent ransomware attack detection and classification using dual vision transformer with Mantis Search Split Attention Network

Check for updates Modified Inception V3 Using Soft Attention for the Grading of Diabetic Retinopathy

Modified InceptionV3 Using Soft Attention for the Grading of Diabetic Retinopathy

Grading of Diabetic Retinopathy using iterative Attentional Feature Fusion (iAFF)

Conclusion

Ms. K. Ashwini exemplifies a suitable candidate for the Research for Best Researcher Award. Her specialized research in diabetic retinopathy grading, supported by a solid academic and technical background, positions her as a promising researcher. Her publications and active participation in workshops further validate her dedication and contributions to biomedical signal processing and computer vision applications, aligning well with the award’s criteria for excellence in research and innovation.

Dinesh Sharma | Computer Science | Best Researcher Award

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Dr. Dinesh Sharma | Computer Science | Best Researcher Award

Dr. Dinesh Sharma, Manipal University Jaipur, India

Dr. Dinesh Sharma holds a Ph.D. in Computer Science and Engineering from Uttarakhand and an M.E. from C-DAC, Pune. With over 14 years of experience in technical and engineering education, he currently serves as an Associate Professor at Manipal University Jaipur. He has published multiple patents, including innovations in animal wellbeing and waste management. Dr. Sharma is a technical committee member for various international conferences and has acted as a guest editor for respected journals. He is also an AICTE High-Performance Computing Master Trainer, dedicated to advancing technology in education. 🌍✨

 

Publication profile

Scopus

Qualification

Dr. Dinesh Sharma is an accomplished academic in the field of Computer Science and Engineering, holding a Ph.D. from Uttarakhand Technical University. He also earned a Master’s degree in CSE from C-DAC, Pune, and a Bachelor’s degree from R.G.P.V., Bhopal. With over 14 years of experience in technical education, he currently serves as an Associate Professor at Manipal University Jaipur. Dr. Sharma has a strong research background, with multiple patents and publications focusing on innovative technologies. His contributions to academia include serving as a reviewer for numerous journals and as a technical committee member for various international conferences. 🌍✨

 

Professional Achievements πŸ†

Dr. Dinesh Sharma has made significant contributions to academia and industry, serving as a Guest Editor for a special issue on “Industrial System Pioneering in Industry 4.0” in the Journal of New Materials and Electrochemical Systems. He is an AICTE High-Performance Computing Master Trainer and has been invited as a session chair at numerous international conferences, including IEEE CSNT and CICN. Dr. Sharma coordinated a five-day Faculty Development Program on IoT at Amity University and served as an Associate Editor for Pragyan Journal of Information Technology. Additionally, he reviews for various SCI, IEEE, and Scopus-indexed journals. 🌐✨

 

Awards & Guided Projects πŸ…

Dr. Dinesh Sharma has successfully mentored CSE students who achieved remarkable milestones, including securing international funding of $1,000 and $250 from Latrobe University Technology Grand Challenge, where one project also won the 1st runner-up prize. Under his guidance, Mr. Ashish Kumar Mishra developed a β€œSmart Attendance System,” earning 1st position in a national challenge organized by Amazon and receiving β‚Ή35,000. Additionally, Ms. Priyanshi Gupta won β‚Ή30,000 and the runner-up prize at the “Gwalior Smart City Tech Challenge 2020.” Dr. Sharma also led the development of the web conferencing platform “Bharat Live” for online activities. πŸŒπŸŽ‰

 

Professional Experience πŸ“š

Dr. Dinesh Sharma brings over 14 years of expertise in technical and engineering education, specializing in software development with 8 years of freelance experience in C#, ASP.Net, PHP, Java, and Android app development. Currently, he serves as an Associate Professor in Data Science and Engineering at Manipal University Jaipur since August 2023, where he is also a software developer, KPI coordinator, and E-cell coordinator. Previously, he worked as an Assistant Professor at Amity University Madhya Pradesh and IMS Unison University, contributing significantly as a software developer and coordinator for various academic initiatives. His journey began as the Head of the Computer Science & Engineering Department at Amardeep College of Engineering and Management. πŸŽ“πŸ’»

 

Conclusion

Dr. Dinesh Sharma’s qualifications, innovative research contributions, professional achievements, and mentorship make him an exemplary candidate for the Best Researcher Award. His commitment to advancing technology and educating future generations in the field of computer science is commendable, and he is well-deserving of this recognition.

 

Publication Top Notes

  • Neural network-based soil parameters predictive coordination algorithm for energy efficient wireless sensor network – Cited by: 0 (2024) 🐾
  • Automatic detection and classification of plant leaf diseases using image processing: A survey – Cited by: 1 (2023) 🌱
  • Enhancing Feature Extraction in Plant Image Analysis through a Multilayer Hybrid DCNN – Cited by: 0 (2023) πŸ–ΌοΈ
  • Comparative Analysis of Skin Cancer Detection Using Classification Algorithms – Cited by: 1 (2023) πŸŽ—οΈ
  • Face Mask Detection Analysis for Covid19 Using CNN and Deep Learning – Cited by: 3 (2022) 😷
  • Energy Efficient Multitier Random DEC Routing Protocols for WSN: In Agricultural – Cited by: 18 (2021) 🌾
  • A new energy efficient multitier deterministic energy-efficient clustering routing protocol for wireless sensor networks – Cited by: 34 (2020) πŸ’‘
  • Comparative energy evaluation of lEACH protocol for monitoring soil parameter in wireless sensors network – Cited by: 7 (2018) 🌍
  • Enhance PeGASIS algorithm for increasing the life time of wireless sensor network – Cited by: 6 (2018) ⚑