Gabriella Punziano | Biological Data Science | Best Researcher Award

Published on by Computational Biologists

Prof. Gabriella Punziano | Biological Data Science | Best Researcher Award

Associate Professor at Department of Social Sciences University of Naples Federico II | Italy

Gabriella Punziano is a leading Italian sociologist and Associate Professor of General Sociology at the University of Naples Federico II. With a dynamic academic and research profile, she contributes significantly to the methodological and epistemological advancement of the social sciences. Her work focuses on the integration of qualitative, quantitative, and mixed-methods approaches, the sociology of communication, and the impact of digital transformation on research paradigms. She plays pivotal roles in numerous international projects, doctoral programs, and scientific networks, demonstrating a sustained commitment to both theoretical inquiry and applied social research.

Profile

ORCID

Education

Gabriella earned her Ph.D. in Sociology and Social Research from the University of Naples Federico II, where her dissertation explored the comparative analysis of European welfare regimes through mixed-methods approaches. Prior to her doctorate, she obtained a Master’s degree in Public, Social, and Political Communication (110 cum laude) and a Bachelor’s degree in Sociology (110/110). Throughout her academic formation, she supplemented her education with numerous specialized training sessions at prominent institutions like the University of Essex and the Summer School on Method and Social Research, gaining expertise in R, STATA, NVivo, and multilevel data analysis.

Experience

Her academic career spans over 15 years and includes roles as a postdoctoral fellow, fixed-term researcher, and ultimately Associate Professor at the Department of Social Sciences, University of Naples Federico II. She has served as a visiting researcher at Northumbria University in the UK and Stockholm University in Sweden. Her expertise is frequently sought for PhD programs, inter-university Master’s courses, and national evaluation boards. Gabriella has organized and lectured at major summer schools, contributed to international conferences, and coordinated educational and methodological training initiatives. She holds editorial roles with prominent journals including SN Social Sciences and ARSS, and is an accredited evaluator for the Italian Ministry of Research.

Research Interest

Her research interests encompass the transformation of social welfare systems, digital research methods, mixed methods integration, public communication, and the role of algorithms in shaping digital consumption behaviors. She is particularly engaged in projects studying digital inequality, algorithmic feedback loops, and the evolution of communication in platform societies. Her theoretical orientation is deeply rooted in critical and reflexive approaches to methodology, with a consistent focus on interdisciplinarity and innovation.

Award

Gabriella Punziano received a special mention from the Italian Sociology Association (AIS) during its Youth Forum for the scientific maturity and international scope of her comparative research on European welfare systems. This recognition highlights her capacity to employ integrated research techniques with notable results and societal relevance. Her awarded publication explored Europeanization processes through typological analysis, reinforcing her standing in the academic community.

Publications

Gabriella Punziano has authored numerous academic publications, among which the following are particularly notable:

Title: Digital capital and social inequality: Revisiting divides in the Italian context
Year: 2023
Cited by: 18 articles

Title: Mixed methods research strategies in the digital age
Year: 2022
Cited by: 27 articles

Title: Algorithmic culture and feedback systems in platform societies
Year: 2021
Cited by: 21 articles

Title: Covid-19 and Third Sector innovation: New organizational responses in Campania
Year: 2020
Cited by: 12 articles

Title: Urban transformations and governance: A comparative analysis of Naples and L’Aquila
Year: 2019
Cited by: 16 articles

Conclusion

Gabriella Punziano stands out as a multifaceted scholar whose contributions to research, teaching, international collaboration, and academic leadership make her an outstanding candidate for the Best Researcher Award. Her work transcends disciplinary and national boundaries, offering novel insights into digital society, social policy, and methodological innovation.

Mukhtar Sofi | Artificial Intelligence and Computational Biology | Proteomics Research Award

Published on by Computational Biologists

Dr. Mukhtar Sofi | Artificial Intelligence and Computational Biology | Proteomics Research Award

Assistant Professor at VIT Vellore, India

Dr. Mukhtar Ahmad Sofi is an accomplished academician and researcher specializing in the intersection of artificial intelligence and bioinformatics. He currently serves as an Assistant Professor at BVRIT Hyderabad, India. With a robust foundation in computer science, Dr. Sofi’s career reflects a dedication to scientific rigor, educational excellence, and interdisciplinary innovation. His key research efforts explore machine learning, deep learning, and computational biology, particularly in protein structure prediction and biomedical data analysis. Dr. Sofi’s scholarly contributions include impactful publications in high-ranking journals, patents, and participation in global conferences. His professional journey exemplifies a commitment to scientific advancement and collaborative research leadership.

Profile

Google scholar

Education

Dr. Sofi earned his Ph.D. in Computer Science & Engineering from the University of Kashmir. He holds an M.Tech in Computer Science & Engineering and an MCA in Computer Science from Pondicherry Central University. His academic journey began with a BCA from the University of Kashmir, laying a solid foundation in computing principles. Supplementing his formal education, he pursued a Certificate in Foreign Languages (French) and completed specialized training in machine learning through the NPTEL platform from IIT Kharagpur. His academic profile demonstrates a continuous commitment to advanced learning and interdisciplinary competence.

Experience

Dr. Sofi has been working as an Assistant Professor at BVRIT Hyderabad since February 2023. His experience bridges both teaching and research, providing students with advanced training in machine learning and deep learning while leading impactful research initiatives. Before his academic appointment, he gained experience as a research fellow during his doctoral studies under the University Grants Commission’s Senior and Junior Research Fellowship schemes. Additionally, Dr. Sofi has contributed to multiple workshops, training sessions, and has mentored students to win prestigious R&D showcases. His practical experience also includes leading projects in Docker environments and leveraging deep learning libraries on NVIDIA’s DGX A100 server infrastructure.

Research Interest

Dr. Sofi’s research interests lie at the intersection of machine learning, deep learning, computational biology, and bioinformatics. His primary focus is on protein secondary structure prediction using deep learning models. He explores data partitioning strategies, convolutional and recurrent architectures, and attention mechanisms to enhance prediction accuracy. His work also expands into broader applications such as reservoir water prediction, sentiment analysis in human-robot interactions, and medical diagnostics using digital twins. Through his research, Dr. Sofi aims to bridge the gap between computational modeling and real-world biological systems, contributing to personalized medicine and AI-driven biomedical innovations.

Awards

Among Dr. Sofi’s many recognitions are the UGC-NET and JK-SET qualifications in Computer Science, both achieved in 2018. He was awarded Senior and Junior Research Fellowships by UGC for his Ph.D. studies. He received a grant of ₹3.5 lakh from AICTE to conduct an ATAL Faculty Development Program on “Generative AI: Transforming Education and Research” in 2023. He was recently selected for a prestigious Post-Doctoral Fellowship at the National University of Singapore and Chinese Academy of Medical Sciences (2024). Additionally, he received the Best Paper Presentation Award at the IEEE ICDSNS-2024 and served as a supporting trainer for NVIDIA’s advanced deep learning workshop.

Publications

Dr. Sofi’s impactful scholarly work includes the following publications:

IRNN-SS: Deep learning for optimised protein secondary structure prediction – Int. J. Bioinformatics Research and Applications, 2024. Cited by: 2.

RiRPSSP: A Unified Deep Learning method for Protein Secondary Structures – Journal of Bioinformatics and Computational Biology, 2023. Cited by: 8.

Protein secondary structure prediction using CNNs and GRUs – International Journal of Information Technology (Springer), 2022. Cited by: 14.

Smart Toll Tax Collection using BLE – International Journal of Advanced Research in Computer Science, 2017. Cited by: 5.

Bluetooth Protocol in IoT: Security Review – International Journal of Engineering Research & Technology (IJERT), 2016. Cited by: 11.

Cheating Detection in Proctored Exams using Deep Neural Networks – IEEE Access (Accepted, minor revision).

Reservoir Water Prediction using LSTM and GRU – Water Resource Management Journal (Springer) (Under review).

These publications highlight Dr. Sofi’s pioneering work in applying AI to bioinformatics and smart system solutions.

Conclusion

Dr. Mukhtar Ahmad Sofi exemplifies the future of proteomics research by merging computational intelligence with biological structure prediction. His innovative approaches, validated by high-impact publications and international recognition, significantly advance the field. Given his contributions to protein structure prediction and his visionary application of AI in bioinformatics, Dr. Sofi is an ideal recipient for the Proteomics Research Award, embodying the excellence, innovation, and interdisciplinary rigor the award stands for.

David Abel | Molecular Evolution | Best Researcher Award

Published on by Computational Biologists

Dr. David  Abel |  Molecular Evolution | Best Researcher Award 

Director at The Origin of Life Science Foundation, Inc, United States

Dr. David Lynn Abel is a pioneering researcher in the fields of origin-of-life science, proto-biocibernetics, and protocellular metabolomics. As the driving force behind The Gene Emergence Project and The Origin of Life Science Foundation, Dr. Abel explores the foundational principles of biological programming, the emergence of genetic information, and the algorithmic nature of life.

Profile:

🧠 Research Focus:

Dr. David Lynn Abel is a pioneering thinker in the realms of proto-biocentric systems, origin-of-life studies, and genetic emergence. Through his innovative concept of ProtoBioCybernetics, he explores life as a form of programmed computation, challenging conventional narratives around abiogenesis and molecular evolution.

📚 Recent Peer-Reviewed Publications (2024–2025):

Dr. Abel has published prolifically in the past six months, with six peer-reviewed, well-indexed articles:

  1. Selection in Molecular Evolution – Studies in History and Philosophy of Science (2024)

  2. What is Life? – Archives of Microbiology and Immunology (2024)

  3. Why is Abiogenesis Such a Tough Nut to Crack? – Archives of Microbiology and Immunology (2024)

  4. The Common Denominator of All Known Lifeforms – Journal of Bioinformatics and Systems Biology (2025)

  5. Life is Programmed Computation – Journal of Bioinformatics and Systems Biology (2025)

  6. “Assembly Theory” in Life-Origin Models: A Critical Review – Biosystems (2025)

🔍 Current Research:

“Reconceptualizing ‘Mutation’”
Challenging standard definitions of mutation, Dr. Abel is developing a new framework that merges information theory, semiotics, and systems biology.

Publication:

      1.  “Assembly Theory” in life-origin models: A critical review