Konduru Balakrishna | Molecular Diagnostics | Industry Impact Award

Published on by Popular Scientist

Dr. Konduru Balakrishna | Molecular Diagnostics | Industry Impact Award

Scientist | Defence Institute of Biodefence Technologies | India

Dr. Konduru Balakrishna is a senior scientist with extensive expertise in food microbiology, molecular biotechnology, and biodefence-related diagnostics. His research focuses on rapid detection of foodborne and zoonotic pathogens, mycotoxins, and biological threat agents using molecular, immunological, and recombinant protein–based approaches. He has made significant contributions to multiplex PCR assays, monoclonal antibody development, chimeric proteins, and vaccine candidates for bacterial infections. His work bridges fundamental microbiology and applied biosensing, leading to multiple granted patents and high-impact publications. His research output includes 31 documents, cited 474 times, with an h-index of 13, reflecting his role in advancing indigenous technologies for food safety, public health protection, and biodefence applications through translational research and innovation.

Citation Metrics (Scopus)

600

450
300
150
0

Citations
474

Documents
31

h-index
13

🟦 Citations   🟥 Documents   🟩 h-index


View Scopus Profile

Featured Publications

Kostas Stylianou | Nephrology | Research Excellence Award

Published on by Popular Scientist

Assoc. Prof. Dr. Kostas Stylianou | Nephrology | Research Excellence Award

Nephrology Dept | Greece

Assoc. Prof. Dr. Kostas Stylianou is a clinician scientist in nephrology whose work integrates advanced clinical practice with translational research on complex kidney disorders. His academic and professional experience spans leadership in nephrology units, extensive involvement in multidisciplinary kidney care, and contributions to national and international scientific initiatives. His research focuses on the genetic and molecular mechanisms underlying familial and chronic kidney diseases of unclear origin, with particular emphasis on collagen IV nephropathies, Alport-related conditions, LCAT deficiency syndromes, and other inherited glomerular disorders. He has contributed significantly to the understanding of molecular pathways such as PI3K/AKT/mTOR signaling in autoimmune kidney disease and has advanced the study of cardiorenal interactions through clinical and biomarker-based investigations. His work includes detailed analysis of kidney biopsies using electron microscopy and integration of genomic and proteomic profiling to improve diagnostic precision. Dr. Stylianou participates in major collaborative projects addressing rare genetic nephropathies and contributes to multicentre clinical trials exploring novel therapeutic approaches in nephrology. He is widely recognized for his scientific output, editorial responsibilities, and reviewing activities across high-impact journals. His expertise is further reflected in the organization of national and international nephrology conferences and in his longstanding role in medical education, where he trains undergraduate students, postgraduate learners, and nephrology trainees. Through his combined clinical, research, and academic commitments, he has established a strong reputation in genetic kidney disease research, cardiorenal medicine, and evidence-based nephrology practice.

Profile: Google Scholar

Featured Publications

Singh, A. K., Carroll, K., Perkovic, V., Solomon, S., Jha, V., Johansen, K. L., Lopes, … & MMJJV. (2021). Daprodustat for the treatment of anemia in patients undergoing dialysis. NEJM Group, 385(25), 2325–2335.

Barratt, J., Lafayette, R., Kristensen, J., Stone, A., Cattran, D., Floege, J., Tesar, V., … & others. (2023). Results from part A of the multi-center, double-blind, randomized, placebo-controlled NefIgArd trial, which evaluated targeted-release formulation of budesonide for the treatment of IgA nephropathy. Kidney International, 103(2), 391–402.

Carrero, J. J., Kyriazis, J., Sonmez, A., Tzanakis, I., Qureshi, A. R., Stenvinkel, P., … & others. (2012). Prolactin levels, endothelial dysfunction, and the risk of cardiovascular events and mortality in patients with CKD. Clinical Journal of the American Society of Nephrology, 7(2), 207–215.

Fysaraki, M., Samonis, G., Valachis, A., Daphnis, E., Karageorgopoulos, D. E., … & others. (2013). Incidence, clinical, microbiological features and outcome of bloodstream infections in patients undergoing hemodialysis. International Journal of Medical Sciences, 10(12), 1632–1638.

Andrianaki, A. M., Kyrmizi, I., Thanopoulou, K., Baldin, C., Drakos, E., … & others. (2018). Iron restriction inside macrophages regulates pulmonary host defense against Rhizopus species. Nature Communications, 9(1), 3333.

Andrea Cynthia Santos | Operational research | Research Excellence Distinction Award

Published on by Popular Scientist

Prof. Dr. Andrea Cynthia Santos | Operational research | Research Excellence Distinction Award

Le Havre Normandie University, Engineering Institute of Logistics (ISEL) | France

Prof. Dr. Andréa Cynthia Santos is a leading scholar in Computer Science whose research lies at the intersection of Operations Research, urban systems, and large-scale disaster management. Her work focuses on developing advanced optimization models, algorithms, and decision-support approaches that address complex sociotechnical challenges in industrial, natural, and health-related crisis scenarios. She is widely recognized for contributions to integrated routing, scheduling, robust optimization, network design, drone-based search strategies, and humanitarian logistics in post-disaster environments. Her research is characterized by strong interdisciplinary engagement, combining computational optimization, artificial intelligence, and systems engineering to improve resilience and sustainability in modern cities. She has produced a substantial body of scientific work, including numerous international journal articles, book chapters, and conference contributions, and has played a key role in organizing international scientific events. Beyond her research activity, she has demonstrated significant leadership in academic administration and scientific strategy, including directing major institutional programs, steering research initiatives, and contributing to national and international committees. She has led multiple research projects across national, regional, industrial, and international collaborations, supported by multidisciplinary teams. Her supervision of PhD candidates, postdoctoral researchers, and master’s students reflects her strong commitment to academic mentorship and capacity building. She has also served as an evaluator for global research organizations and participated in expert panels spanning science, technology, and innovation. Her professional experience includes roles in academic governance, digital transformation, international relations, curriculum development, and research program management, positioning her as an influential figure in the fields of operations research, logistics innovation, and sustainable urban systems.

Profiles: Scopus | Orcid

Featured Publications

Barbalho, T. J., Jiménez Laredo, J. L., & Santos, A. C. (2025). The resource-constrained project scheduling problem for risk reduction after industrial disasters involving dangerous substances. OR Spectrum. Advance online publication.

Coco, A. A., Duhamel, C., Santos, A. C., & Haddad, M. N. (2024). Solving the probabilistic drone routing problem: Searching for victims in the aftermath of disasters. Networks, (July 2024).

Duhamel, C., & Santos, A. C. (2024). The strong network orientation problem. International Transactions in Operational Research.

Haddad, M. N., Santos, A. C., Duhamel, C., & Coco, A. A. (2023). Intelligent drone swarms to search for victims in post-disaster areas. Sensors, 23(23), 9540.

De Freitas, C. C., Aloise, D. J., Fontes, F. F. C., Santos, A. C., & Menezes, M. S. (2023). A biased random-key genetic algorithm for the two-level hub location routing problem with directed tours. OR Spectrum, 45, 1–26.

Jinglin Li | Computer Science | Best Researcher Award

Published on by Popular Scientist

Mr. Jinglin Li | Computer Science | Best Researcher Award

Engineer | China National Nuclear Corporation | China

Li Jinglin is a researcher specializing in intelligent systems, reinforcement learning, and energy-efficient technologies for industrial and service applications. He holds advanced degrees in Instrument Science and Technology, Electrical Engineering, and Vehicle Engineering with a focus on new energy systems. His research encompasses the development of intelligent interactive service technologies for elderly care, optimization of energy-harvesting wireless sensor networks, and multi-task scheduling for energy-secured unmanned vehicles. He has led projects on digital twin platform technologies and vertical displacement control of nuclear fusion plasma, applying deep reinforcement learning to enhance system performance and replace traditional control methods. Li has extensive experience in algorithm design, including MATLAB-based reinforcement learning, adaptive dynamic programming, and multi-level exploration deep Q-network scheduling, with applications in optimal microgrid transmission, mobile charging sequence scheduling, and network monitoring. His work has resulted in multiple first-author publications in high-impact journals covering reinforcement learning, wireless sensor networks, and energy management, as well as conference contributions in control and automation. Beyond his technical expertise, he demonstrates strong analytical, problem-solving, and team collaboration skills, with experience in summarizing complex research findings and implementing practical solutions. Li actively engages in academic presentations and has earned recognition for his research achievements. In addition to his research, he maintains leadership roles in university sports teams, reflecting his commitment to teamwork, discipline, and resilience. His professional approach combines a proactive mindset, logical thinking, and a dedication to advancing intelligent and sustainable technological solutions across both industrial and service domains.

Profile: Scopus

Featured Publications

Li, J. (2024). A deep reinforcement learning approach for online mobile charging scheduling with optimal quality of sensing coverage in wireless rechargeable sensor networks. Ad Hoc Networks, 156, 103431.

Li, J. (2024). A reinforcement learning based mobile charging sequence scheduling algorithm for optimal sensing coverage in wireless rechargeable sensor networks. Journal of Ambient Intelligence and Humanized Computing, 15(6), 2869–2881.

Li, J. (2023). Mobile charging sequence scheduling for optimal sensing coverage in wireless rechargeable sensor networks. Applied Sciences, 13(5), 2840.

Li, J. (2024). A reinforcement learning based mobile charging sequence scheduling algorithm for optimal stochastic event detection in wireless rechargeable sensor networks. IEEE Transactions on Network and Service Management.

Li, J. (2024). A swarm deep reinforcement learning based on-demand mobile charging-scheduling and charging-time control joint algorithm for optimal stochastic event detection in wireless rechargeable sensor networks. Expert Systems with Applications.

Yan Zhang | Computer Science | Best Researcher Award

Published on by Popular Scientist

Yan Zhang | Computer Science | Best Researcher Award

Tsinghua University,China

Author Profile

Early Academic Pursuits

Yan Zhang embarked on an academic journey in computer science, which laid a solid foundation for his future endeavors. He pursued his undergraduate studies with a focus on the fundamentals of computer science, which ignited his interest in privacy-preserving technologies and data security. His early academic work was characterized by a keen interest in theoretical aspects of computer science, which later evolved into a practical application in the fields of privacy and data security.

Professional Endeavors

Currently, Yan Zhang is advancing his academic career as a PhD candidate in the Department of Computer Science and Technology at Tsinghua University, one of China's most prestigious institutions. His professional journey is marked by rigorous research and a commitment to addressing complex issues in data privacy and deep learning. Throughout his time at Tsinghua, Yan has been involved in various research projects, collaborating with experts and contributing to significant advancements in his field.

Contributions and Research Focus

Yan Zhang’s research primarily focuses on privacy-preserving techniques, privacy issues in data publishing, and the integration of these areas with deep learning. His work aims to develop methodologies that protect sensitive information while ensuring data utility. Yan has contributed to several high-impact publications and conferences, where he presented innovative solutions for safeguarding privacy in the era of big data. His research addresses critical challenges in maintaining the balance between data accessibility and privacy, a concern increasingly relevant in today's digital world.

Accolades and Recognition

Throughout his academic career, Yan Zhang has received numerous accolades for his contributions to computer science. His research papers have been widely cited, and he has been recognized by his peers for his innovative approaches to privacy-preserving data techniques. Yan’s dedication and excellence in research have earned him various scholarships and awards, highlighting his status as a rising star in his field.

Impact and Influence

Yan Zhang’s work has had a significant impact on the field of computer science, particularly in the areas of privacy and data security. His research has influenced the development of new protocols and systems that enhance privacy-preserving measures in data publishing. By addressing some of the most pressing issues in data security, Yan has not only contributed to academic knowledge but also to practical applications that benefit society at large.

Legacy and Future Contributions

As Yan Zhang continues his research and completes his PhD, his legacy is already taking shape through his contributions to privacy-preserving technologies. His future work is expected to further influence the field, with potential advancements in deep learning applications and data security frameworks. Yan’s ongoing commitment to tackling complex privacy issues will likely lead to groundbreaking innovations that safeguard data privacy in increasingly sophisticated ways.By maintaining a strong focus on the intersection of privacy, data publishing, and deep learning, Yan Zhang is poised to make enduring contributions that will shape the future of computer science and technology. His dedication to research excellence and his innovative mindset ensure that his work will continue to have a profound impact on both academic circles and the broader technological landscape.