Sunawar Khan | Computer Science | Research Excellence Award

Mr. Sunawar Khan | Computer Science | Research Excellence Award

National College of Business Administration | Pakistan

Sunawar Khan is a research-oriented academic and practitioner with strong expertise in artificial intelligence, machine learning, deep learning, cybersecurity, smart grid technologies, Computer Science and intelligent systems. His research interests center on applying advanced computational intelligence techniques to real-world problems, particularly in healthcare analytics, intrusion detection systems, software reliability, and smart city security. He has worked extensively with neural networks, ensemble learning, explainable AI, and hybrid deep learning architectures such as CNN- and BiGRU-based models. His projects include deep learning–based disease detection using benchmark medical datasets, facial expression recognition with neural AdaBoost methods, and software defect prediction using industrial datasets. In cybersecurity, his research focuses on robust intrusion detection for smart environments, emphasizing accuracy, scalability, and interpretability. He also has experience designing and implementing intelligent management systems and applying machine learning to large, structured datasets. His academic background reflects a strong foundation in artificial intelligence, image processing, computer vision, data mining, algorithm analysis, and computational theory, complemented by practical experience in programming and system development. Overall, his research profile demonstrates a commitment to innovative, data-driven solutions that bridge theoretical models and applied intelligent technologies across interdisciplinary domains.

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Featured Publications


Antenna Systems for IoT Applications: A Review


Discover Sustainability, Vol. 5(1), Article 412, 2024

Generative AI, IoT, and Blockchain in Healthcare: Applications, Issues, and Solutions


Discover Internet of Things, Vol. 5(1), Article 5, 2025

Kaili Wang | Machine Learning and Statistics | Best Researcher Award

Dr. Kaili Wang | Machine Learning and Statistics | Best Researcher Award

university of malaya | Malaysia

Dr. Kaili Wang is an accomplished economist and Doctoral Candidate in Financial Economics at the University of Malaya, with a strong academic foundation in quantitative analysis, holding a master’s degree in Quantitative Economics from Zhongnan University of Economics and Law and a bachelor’s degree in Statistics from Luoyang Normal University. She has extensive teaching experience, having served as a full-time faculty member at the Business School of Nantong University of Technology, where she contributed significantly to both academic research and student mentorship. Her research expertise encompasses financial security, green finance, and the operational efficiency of financial institutions, reflected in her monographs, including Analysis of RMB Internationalization Path from the Perspective of Financial Security (sole author) and Research on the Long-term Mechanism of Green Finance Development (second author). She has also led impactful research projects, such as the Jiangsu Provincial University Philosophy and Social Sciences Research Project on the operational efficiency of city commercial banks. Kaili Wang has demonstrated a strong commitment to student development, guiding participants in national and provincial financial competitions to notable achievements, including second and third prizes in the National ETF Elite Challenge and the “East Money Cup” National College Students’ Financial Challenge, and earning recognition as an Excellent Supervisor. Her work reflects a combination of rigorous empirical analysis and practical engagement with financial markets, emphasizing sustainable finance and strategic economic development. With a focus on integrating academic excellence with real-world financial insights, Kaili Wang continues to advance knowledge in financial economics while nurturing the next generation of economists and financial professionals through research, mentorship, and academic leadership. Her career demonstrates a sustained dedication to both scholarly contributions and fostering student success in competitive financial arenas.

Profile: Orcid

Featured Publication

Wang, K. (2024). An analysis of the RMB internationalization path from the perspective of financial security.

Om Sambhaji Shelke | Operations Research and Statistical Optimization | Excellence in Research Award

Dr. Om Sambhaji Shelke | Operations Research and Statistical Optimization | Excellence in Research Award

Sinomune Pharmaceutical Co. Ltd | China

Dr. Om Sambhaji Shelke is a highly accomplished pharmaceutical scientist with extensive expertise in the formulation and development of topical, semisolid, solid, and liquid drug products. Holding a Ph.D. in Pharmacy and an M. Pharmacy from Savitribai Phule Pune University, he has over a decade of experience across global markets including the US, EU, China, Hong Kong, and India. Currently serving as Chief Scientist at Sinomune Pharmaceutical Co. Ltd. in Wuxi, Jiangsu, China, Dr. Shelke leads the development of generic topical products for the NMPA market. He is skilled in Quality by Design (QbD)-based development of creams, ointments, gels, shampoos, and solutions, with specialization in novel formats such as emulgel, organogel, nanogel, solid lipid nanoparticles, suspensions, and toothpaste. He also holds three granted patents and has published multiple scientific and technical articles. Throughout his career, he has received multiple awards recognizing his innovation, knowledge sharing, and leadership, including the StarFire Award. Dr. Shelke has held pivotal roles at leading pharmaceutical and consumer healthcare companies such as Prinbury Biopharm Co. Ltd., Encube Ethicals Pvt Ltd., Bright Future Pharmaceuticals Ltd., Unilever Industries Pvt Ltd., Abbott Healthcare Pvt Ltd., Dr. Reddy’s Laboratories, and Glenmark Pharmaceuticals Ltd., contributing to both regulatory-compliant NDA, ANDA, and 505(b)(2) products as well as OTC, cosmetic, and personal care formulations. His professional journey reflects a consistent commitment to scientific excellence, innovative product development, and leadership in cross-functional teams, positioning him as a prominent figure in global pharmaceutical research and development.

Profiles: Google Scholar Orcid

Featured Publications

F. Jie, O. Shelke, Z. Yijie, C. Yulan, & L. Yongbo. (2025). Q1 and Q2 selection, Q3, IVRT, IVPT, pharmacokinetic and pharmacodynamic evaluation of topical generic product. Drug Development and Industrial Pharmacy, 51(6), 555–565.

J. Feng, O. S. Shelke, Y. Chen, Z. Zhang, X. Tang, & Y. Zhu. (2025). IVRT and IVPT of desonide lotion and cream: Correlation with human bioequivalence study. Journal of Pharmaceutical Innovation, 20(5), 196.

S. Krishna Phani Chandra, S. Om Sambhaji, & N. Shorgar. (2025). Quantification of leniolisib in rat plasma using LC-MS/MS: Method development, validation, and pharmacokinetic study. African Journal of Biological Sciences, 7(7), 121–142.

S. Om. (2025). Editorial article: The transformative impact of AI in pharmaceutical drug product development. Insights of Pharmatech, 1(2), 1.

S. Gadge, O. S. Shelke, R. Pingale, P. Palande, S. Tandale, P. Sonawane, … (2025). Development and evaluation of a polyherbal neem-based emulgel enriched with herbal oils for enhanced topical delivery and antibacterial efficacy. Journal of Chemical Health Risks, 15(3), 2189–2209.

Fatih UCUN | Regression and Correlation Analysis | Best Researcher Award

Prof. Dr. Fatih UCUN | Regression and Correlation Analysis | Best Researcher Award

Suleyman Demirel University | Turkey

Prof. Dr. Fatih Ucun is a distinguished physicist specializing in atomic and molecular physics, with expertise in electron paramagnetic resonance (EPR), nuclear magnetic resonance (NMR), and infrared (IR) spectroscopy. He completed his B.Sc. and M.Sc. in Physics at Atatürk University and earned his Ph.D. from Ondokuz Mayıs University. He is a full professor in the Department of Physics at Suleyman Demirel University in Isparta, Turkey. Prof. Ucun has made significant contributions to computational chemistry, molecular modeling, and quantum mechanics, bridging theoretical insights with practical applications in material science and nanotechnology through pioneering studies on molecular electronic structures and quantum chemical simulations. He has authored 91 publications, cited 883 times, and holds an h-index of 16, reflecting his substantial impact in the field. In addition to his research, he has published four books and serves on editorial boards of scientific journals, demonstrating his leadership and influence in the academic community. His work has advanced the understanding of atomic-level interactions and energy transfer mechanisms, while mentoring future scientists and enriching scientific progress in physical chemistry and computational modeling.

Profiles: Scopus Google Scholar 

Featured Publications

Ucun, F., Isik, Y. E., & Tiryaki, O. (2025). An approach to description of isotropic hyperfine interaction constants in the fluorinated nitrobenzene and nitrophenol radical anions: DFT calculations vs. experiment. Russian Journal of Physical Chemistry A, 99, 2498–2505.

Yolburun, H., & Ucun, F. (2023). EPR analysis of dinitrobenzoic acid anion radicals. International Journal of Computational and Experimental Science and Technology.

Ucun, F. (2023). EPR analysis of dinitrobenzoic acid anion radicals. International Journal of Computational and Experimental Science and Technology.

Ucun, F., & Alakuş, N. (2022). Enthalpies and activation energies of several gas reactions by intrinsic reaction coordinate (IRC) calculations. El-Cezeri, 9(2), 576–583.

Ucun, F., & Küçük, S. (2022). Triafulvalen, pentafulvalen ve heptafulvalenin katyon ve anyon radikallerinin EPR aşırı ince-yapı yapıları: Bir teorik çalışma. Süleyman Demirel University Faculty of Arts and Science Journal of Science.

Tushar Bhoite | Bayesian Networks and Decision Theory | Best Researcher Award

Dr. Tushar Bhoite | Bayesian Networks and Decision Theory | Best Researcher Award

Dr. Tushar Bhoite | MES’s Wadia College of Engineering | India

Dr. Tushar Devidas Bhoite, Ph.D. in Mechanical Technology, M.E. in Machine Design, with over sixteen years of professional experience (including twelve in the automobile industry and four in academics), is a leading researcher and practitioner in integrating advanced IT technologies in auto-component manufacturing. His research interests encompass Industry 4.0, Industrial Internet of Things (IIoT), Digital Twin systems, Generative AI, predictive maintenance, neural and Bayesian networks, real-time monitoring, optimization and efficiency improvements in production environments. To date, he has authored 6 international journal papers and 3 international conference papers, co-authored 2 textbooks, and filed 2 patents, contributing to both theoretical and applied advancements. His master’s project, awarded from RGSTC Mumbai, stands as a landmark in his research portfolio, he has an h-index of 1 and over 1 citations as per his Scopus profile, reflecting strong scholarly impact. In his industrial roles, Dr. Bhoite has successfully led IOT implementations in assembly and press shops, improved Overall Equipment Effectiveness, standardized work systems, deployed TPM and Kaizen methodologies, and developed innovative solutions such as a wet-waste treatment machine. He currently serves as Assistant Professor in Automation & Robotics Engineering at MES’s Wadia College of Engineering, Pune, and continues consulting in production efficiency, resource optimization, and technology integration in manufacturing enterprises.

Profiles: Scopus Google Scholar Orcid

Featured Publications

Bhoite, T. D., Pawar, P. M., & Gaikwad, B. D. FEA based study of effect of radial variation of outer link in a typical roller chain link assembly. International Journal of Mechanical and Industrial Engineering, 1, 65–70.

Bhoite, T. D., & Buktar, R. B. (2025). Productivity enhancement in Indian auto component manufacturing supply chain with IoT using neural networks. Production, 35, e20240047.

Bhoite, T. D., Buktar, R. B., Mahalle, P. N., Khond, M. P., Pise, G. S., & More, Y. Y. (2025). Productivity enhancement in the Indian auto component manufacturing supply chain through IoT, digital twins with generative AI, and stacked encoder-enhanced neural networks. Operations Research Forum, 6(4), 143.

Bhoite, D. T., & Buktar, R. (2025). An investigation into revolutionizing auto component manufacturing: An IoT-based approach for improved productivity and waste elimination. Journal of Information Systems Engineering and Management, 10(9s), 409–429.

Bhoite, D. T., Buktar, R., & Kannukkadan, G. (2024). Leveraging IoT in auto component manufacturing to monitor surface roughness and tool temperature. Journal of Electrical Systems, 20(2s), 563–574.*

Ching Chih Tsai | Fuzzy Statistics and Uncertainty Modelling | Best Researcher Award

Prof. Ching Chih Tsai | Fuzzy Statistics and Uncertainty Modelling | Best Researcher Award

Prof. Ching Chih Tsai |  National Chung Hsing University | Taiwan

Prof. Ching Chih Tsai is a distinguished academic in electrical engineering and control systems, currently serving as a Life Distinguished Professor at the Department of Electrical Engineering, National Chung Hsing University (NCHU), Taiwan. He earned his Ph.D. from Northwestern University in 1991. Dr. Tsai has held significant leadership roles, including serving as the President of the Chinese Automatic Control Society (CACS), the Robotics Society of Taiwan (RST), and the International Fuzzy Systems Association (IFSA). He has also been a Board of Governors member of IEEE Systems, Man, and Cybernetics Society (SMCS) and is currently the Dean of the College of Electrical Engineering and Computer Science at NCHU. An IEEE Fellow, his research focuses on intelligent control systems, mobile robotics, and automation intelligence. Dr. Tsai has published over 700 technical articles, with more than 20 in the International Journal of Fuzzy Systems since 2005. His recent work includes a 2025 paper on intelligent adaptive formation control for multi-quadrotors, introducing a hybrid controller combining Output Recurrent Fuzzy Broad Learning Systems (ORFBLS), reinforcement learning, and adaptive backstepping sliding mode control. According to Scopus, he has an h-index of 29, with 3,902 citations from 272 documents.

Profiles: Scopus Google Scholar Orcid

Featured Publications

Rospawan, A., Tsai, C.-C., & Hung, C.-C. (2025). Two-layer intelligent learning control using output recurrent fuzzy neural long short-term memory broad learning system with RMSprop. IEEE Access.

Tsai, C.-C., Hung, C.-C., Mao, C.-F., Wu, H.-S., & Chen, C.-H. (2025). Fuzzy neural LSTM-RBLS for fractional-order PID sliding-mode motion control of autonomous mobile robots with four ISID wheels. International Journal of Fuzzy Systems.

Tsai, C.-C., Mao, C.-F., & Hussain, K. (2025). Intelligent adaptive formation control using ORFBLS and reinforcement learning for uncertain tilting multi-quadrotors. International Journal of Fuzzy Systems. =

Rospawan, A., Tsai, C.-C., & Hung, C.-C. (2025). Intelligent MIMO ORFBLS-based setpoint tracking control with its application to temperature control of an industrial extrusion barrel. International Journal of Fuzzy Systems.

Tsai, C.-C., Huang, H.-C., Chen, H.-Y., Hung, C.-C., & Chen, S.-T. (2024). Intelligent collision-free formation control of ball-riding robots using output recurrent broad learning in industrial cyber-physical systems. IEEE Transactions on Industrial Cyber-Physical Systems.

Dmitry Ponomarev | Causal Inference and Experimental Design | Best Researcher Award

Dr. Dmitry Ponomarev | Causal Inference and Experimental Design | Best Researcher Award

Kurchatov Institute | Russia

Dr. Dmitry Ponomarev, Ph.D. in Electrical Engineering, is an accomplished scientist and academic leader who serves as Deputy Research Director and Head of the Optoelectronics Group at the National Research Centre “Kurchatov Institute,” Moscow, Russia, while also holding the role of Principal Investigator at Tohoku University, Japan. His career has been dedicated to advancing millimeter-wave electronics, terahertz photonics, and quantum optoelectronic devices, where he has consistently demonstrated the ability to bridge fundamental research with technological applications. With more than 118 peer-reviewed journal publications, contributions to 2 academic books, and 12 patents granted alongside 2 under evaluation, he has established himself as a prolific and innovative researcher whose output has been widely disseminated across international platforms. His scientific influence is evident in an H-index of 30 and more than 3,000 citations, which highlight not only the originality of his ideas but also their relevance and adoption by the broader global scientific community. Over the course of his career, he has successfully led 18 completed research projects and continues to direct 3 active investigations, in addition to playing a central role in 6 consultancy and industry collaborations that link academic knowledge to real-world applications. His research contributions include the realization of polarization-sensitive sub-THz detectors, ultralow-noise strain-induced terahertz devices, the pioneering development of a 64-pixel optoelectronic THz detector array, novel performance-enhancement strategies for emitters using plasmonic electrode designs, and the creation of sapphire-fiber microlens arrays with high refractive precision. Beyond his technical achievements, Dr. Ponomarev has made significant service contributions to the academic community, holding 10 editorial appointments, mentoring doctoral students, and serving as a member of scientific councils at leading institutions, including the Russian Academy of Sciences and the Moscow Institute of Physics and Technology. He has built strong collaborations with world-class institutions such as Tohoku University in Japan, École Polytechnique de Montréal in Canada, and Rensselaer Polytechnic Institute in the United States, reinforcing his role as a global connector of expertise. His impact has also been recognized through prestigious prizes and honors awarded for his advances in optoelectronics and quantum photonics, affirming the quality, novelty, and societal relevance of his research. Combining leadership, innovation, and dedication, Dr. Ponomarev continues to shape the future of terahertz science and optoelectronics, while his academic profile, certificates, and supporting documents remain accessible through trusted repositories and official research links, ensuring transparency and verification of his professional achievements.

Profiles: Scopus Google Scholar Orcid

Featured Publications

Gavdush, A. A., Zhelnov, V. A., Dolganov, K. B., Bogutskii, A. A., Garnov, S. V., Burdanova, M. G., Ponomarev, D. S., Shi, Q., Zaytsev, K. I., & Komandin, G. A. (2025). Insulator–metal transition in VO₂ film on sapphire studied by broadband dielectric spectroscopy. Scientific Reports, 15, Article 3500.

Zhelnov, V. A., Rybnikov, D. D., Ulitko, V. E., Goncharov, Yu. G., Lavrukhin, D. V., Perov, A. N., Garnov, S. V., Ponomarev, D. S., Skorobogatiy, M., Zaytsev, K. I., & Chernomyrdin, N. V. (2025). Superresolution THz pulsed solid immersion microscopy. Applied Physics Letters.

Galiev, R. A., Ushakov, D. V., Afonenko, A. A., Pavlov, A. Yu., Ponomarev, D. (2024). Continuous‐wave two‐photon terahertz quantum cascade laser. Journal of Applied Physics, 136(19), Article 194504.

Zenchenko, N. V., Lavrukhin, D. V., Galiev, R., Yachmenev, A., Khabibullin, R., Goncharov, Y., Dolganova, I., Kurlov, V., Otsuji, T., Zaytsev, K., & Ponomarev, D. (2024). Enhanced terahertz emission in a large‐area photoconductive antenna through an array of tightly packed sapphire fibers. Applied Physics Letters, 124, 121107.

Kovaleva, P., Kuznetsov, K. A., Kuznetzov, P. I., Kitaeva, G., Safronenkov, D., & Ponomarev, D. (2024, July). Plasmonic photoconductive antennas based on Bi₂₋ₓSbₓSeᵧTe₃₋ᵧ topological insulators. In Proceedings of the International Conference Laser Optics (ICLO).

Haifa Jammeli | Operations Research and Statistical Optimization | Best Researcher Award

Dr. Haifa Jammeli | Operations Research and Statistical Optimization | Best Researcher Award

Normasys | France

Dr. Haifa Jammeli is a research fellow at the Institut Supérieur de Gestion de Tunis, specializing in business computing and operations research. She holds a PhD from the Higher Institute of Management in Tunisia and a Master’s degree in Logistics and Transportation Sciences from the Higher Institute of Logistics and Transportation, Sousse University. Her academic and professional journey spans over a decade, with significant contributions to supply chain optimization, AI in logistics, and sustainable urban planning. She is a part-time instructor at Paris Nanterre University and NEOMA Business School, teaching courses in supply chain management, operations research, data analysis, and IT project management. Her research focuses on optimizing transportation routes for COVID-19 patients and cash logistics using tools like CPLEX, QGIS, and Python, and she has developed AI models to forecast urban solid waste generation and propose green logistics solutions for household waste collection. With over 70 citations across nine publications, her work has been presented at international conferences and published in journals such as IEEE Transactions on Engineering Management and Annals of Operations Research. Her h-index is 10, reflecting both productivity and impact in her field. She has received awards including the Perficio Award for Best Woman Entrepreneur of the Year and was a finalist for the IFROS Prize for Operational Research in Development. Fluent in English, French, and Arabic, she combines strong technical skills (CPLEX, MATLAB, Python, R, SQL, QGIS) with experience in teaching, project leadership, and applying AI-based decision models to real‐world sustainability challenges.

Profiles: Scopus | Orcid

Featured Publications

Alaya, H., Jammeli, H., Ben Abdelaziz, F., Masmoudi, M., & Verny, J. (2024). Sustainable logistics for transfer of COVID-19 patients: Lesson learned from France. International Transactions in Operational Research.

Jammeli, H., & Verny, J. (2024). A multi-objective model for two-level distribution system in the city of Paris. Annals of Operations Research. (Accepted for publication)

Jammeli, H., Khefacha, A., Sellei, B., & Verny, J. (2023, October 18–21). The impact of AI tools in education environment. In 2023 IEEE ASEE Frontiers in Education Conference, College Station, Texas.

Jammeli, H., Alaya, H., & Verny, J. (2023, October 23–25). An analysis of the role of the Internet of Things and sensor technologies in optimizing waste management in the city of Sousse, Tunisia . World Recycling Convention, Madrid, Spain.

Jammeli, H., & Verny, J. (2022). A literature review for green smart home delivery problem in urban environments. In 2022 International Conference on Decision Aid Sciences and Applications (DASA) (pp. 756–760). IEEE.

Ahmed A. Ahmed | Regression and Correlation Analysis | Best Researcher Award

Assoc Prof. Dr. Ahmed A. Ahmed | Regression and Correlation Analysis | Best Researcher Award

Mustansiriyah University | Iraq

Dr. Ahmed A. Ahmed, Ph.D, is a distinguished faculty member in the Civil Engineering Department at Mustansiriyah University, Baghdad, Iraq, with a robust research profile emphasizing new and advanced infrastructure materials, durability of engineering materials, infrastructure sustainability, green building materials, material characterization, corrosion and carbonation assessment, microstructure analysis, and evaluation of concrete deterioration processes and mechanisms. With an h-index of 5, 70 citations, and a ResearchGate score of 83.5, Dr. Ahmed has contributed extensively to the field through numerous high-impact publications, including studies on corrosion resistance of calcium sulfoaluminate cementitious systems, reliability of chloride testing in cementitious systems, and experimental investigations on reinforcing steel behavior under corrosive conditions. Since 2012, he has served as a faculty member at Mustansiriyah University and held leadership roles such as Head of the Training and Development Unit in the Continuing Education Branch and active membership in professional societies including the American Concrete Institute, American Society of Civil Engineers, Iraqi Academic Syndicate, Iraqi Engineers Union, and Iraqi Teachers Union. Dr. Ahmed earned his Ph.D. in Infrastructure Materials with a minor in Statistics from Oregon State University and holds multiple advanced teaching certificates and engineering degrees. He has also presented at international conventions and workshops across the United States and Malaysia, highlighting his commitment to research excellence, pedagogy, and professional development in civil engineering.

Profiles:  Orcid | Scopus

Featured Publications

“Assessing the Impact of Graphene Nanoplatelets Aggregates on the Performance Characteristics of Cement-Based Materials”

“Performance Evaluation of Concrete Masonry Unit Mixtures Incorporating Citric Acid-Treated Corn Stover Ash and Alkalinized Corn Stover Fibers”

“Evaluating the Characteristics of Fibrous Pure Gypsum Containing Chopped Carbon Fiber (CCF)”

“Evaluating the performance of thermomechanically beneficiated fly ash blended mortar”

“Reliability of chloride testing results in cementitious systems containing admixed chlorides”

Saikat Biswas | Operations Research and Statistical Optimization | Best Researcher Award

Dr. Saikat Biswas | Operations Research and Statistical Optimization | Best Researcher Award

IIT Roorkee | India

Dr. Saikat Biswas is an Indian chemical engineer and academic whose research primarily focuses on computational fluid dynamics (CFD), multiphase flow, and microfluidics, with a special emphasis on droplet dynamics including breakup, splitting, and the transition from dripping to jetting in complex microchannel geometries. He earned his PhD in Chemical Engineering from the Indian Institute of Technology Guwahati (2016–2023), where his doctoral work investigated droplet breakup dynamics in confined microscale flows, and previously completed both his M.Tech and B.Tech in Chemical Engineering at the National Institute of Technology Agartala. Throughout his academic journey, he has published 14 documents, accumulating 41 citations and achieving an h-index of 3, reflecting his growing impact in the field. His contributions include both numerical and computational studies, such as two-dimensional and three-dimensional simulations of droplet splitting at T-junctions and multifurcating channels, investigations of flow-focusing geometries, and analyses of the role of viscosity ratio, surface tension, and channel design in influencing microfluidic droplet behaviour. Skilled in advanced tools such as ANSYS Fluent, COMSOL Multiphysics, OpenFOAM, and MATLAB, he integrates computational methods with engineering applications to address fundamental and applied challenges. Recognized as hard-working, adaptable, and collaborative, Biswas continues to contribute to the advancement of microfluidics and multiphase flow research.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

“Digital electronic based portable device for colorimetric quantification of ketones and glucose level in human urine”

“Droplet splitting in multifurcating microchannel: A three-dimensional numerical simulation study”

“3D simulation of dripping and jetting phenomena in a flow-focusing geometry”

“A computational study on transition mechanism of dripping to jetting flow in a flow focusing geometry”

“Influence of microchannel geometry on droplet breakup dynamics: A computational study”