Noreen Kamal | Translational Neuroscience | Best Researcher Award

Assoc. Prof. Dr. Noreen Kamal | Translational Neuroscience | Best Researcher Award

Assoc. Prof. Dr. Noreen Kamal | Dalhousie University | Canada

Dr. Noreen Kamal, Ph.D., P.Eng., is an Associate Professor of Industrial Engineering at Dalhousie University, Canada, with cross-appointments in the Departments of Community Health and Epidemiology and Medicine (Neurology). Her research lies at the intersection of health systems engineering and clinical neuroscience, focusing on the optimization of stroke care systems, development of data-driven quality improvement frameworks, and evaluation of biomedical devices for stroke rehabilitation. Dr. Kamal has played a pivotal role in advancing integrated approaches to enhance the efficiency, safety, and accessibility of acute stroke services across Canada. Prior to joining Dalhousie University, she held academic and leadership positions at the University of Calgary and the University of British Columbia, contributing extensively to clinical research and health technology innovation. Her work bridges engineering, medicine, and health policy, emphasizing interdisciplinary collaboration and patient-centered outcomes. With 107 scientific publications, 8,033 citations, and an h-index of 22, Dr. Kamal has established herself as a recognized scholar in healthcare systems improvement and translational neuroscience. Her scholarly and professional contributions continue to drive evidence-based innovation in stroke systems of care, supporting better clinical outcomes and sustainable health service delivery.

Profiles: Scopus | Google Scholar | Research Gate | Linked In

Featured Publications

Author(s). (2025). Exploring differences in stroke treatment between urban and rural hospitals: A thematic analysis of practices in Canada. Canadian Journal of Neurological Sciences.

Author(s). (2025). Designing a patient outcome clinical assessment tool for modified Rankin Scale: “You feel the same way too”. Informatics.

Author(s). (2025). Predicting ischemic stroke patients to transfer for endovascular thrombectomy using machine learning: A case study. Healthcare (Switzerland).

Author(s). (2025). Incident prescriptions for common cardiovascular medications: Comparison of recent versus pre-2020 medication adherence and discontinuation in three universal health care systems. BMC Cardiovascular Disorders.

Author(s). (2025). Rising out-of-hospital mortality in Canada during 2020–2022: A striking impact observed among young adults. Canadian Journal of Public Health.

Author(s). (2025). Discrete event simulation model of an acute stroke treatment process at a comprehensive stroke center: Determining the ideal improvement strategies for reducing treatment times. Journal of the Neurological Sciences.

Author(s). (2025). Validation of the Passive Surveillance Stroke Severity Score in three Canadian provinces. Canadian Journal of Neurological Sciences.

Author(s). (2025). A stochastic optimization model for designing disaster relief networks with congestion, disruption and distributional ambiguity. Infor.

Author(s). (2025). Improving access and efficiency of acute ischemic stroke treatment across four Canadian provinces: A stepped-wedge trial. Frontiers in Neurology.

Author(s). (2025). The acute stroke system of treatment across Canada: Findings from a national stroke centre survey. Canadian Journal of Neurological Sciences.

Mansoor Showkat | Computational Neuroscience | Best Researcher Award

Mr. Mansoor Showkat | Computational Neuroscience | Best Researcher Award

Mr. Mansoor Showkat | SKUAT-Kashmir | India

Mansoor Showkat is a researcher in Plant Biotechnology with an M.Sc. from the University of Agricultural Sciences, Bangalore, and a B.Sc. (Hons.) in Horticulture from Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir. His research expertise spans molecular biology, computational biology, bioinformatics, and tissue culture, with particular emphasis on antifungal compound analysis, gene transformation, and plant-pathogen interactions. Mansoor has contributed to several peer-reviewed publications and book chapters, focusing on the in-silico and in-vitro evaluation of bioactive compounds such as cordycepin, molecular mechanisms of stress responses, and secondary metabolite profiling in plants. His research projects include genetic transformation studies, metabolomics-based investigations, and the use of omics tools for crop improvement. He has actively participated in numerous international workshops, conferences, and webinars related to biotechnology, bioinformatics, and genomics. Mansoor has achieved significant academic recognition, including national rankings in competitive examinations by the Indian Council of Agricultural Research. His scientific impact is reflected by a citation count of 15, an h-index of 2, and an i10-index of 0, highlighting his growing contribution to molecular and agricultural biotechnology research.

Featured Publications

  1. Showkat, M., Narayanappa, N., Umashankar, N., & Saraswathy, B. P., et al. (2024). Optimization of fermentation conditions of Cordyceps militaris and in silico analysis of antifungal property of cordycepin against plant pathogens. Journal of Basic Microbiology, 64(10), e2400409.

  2. Fatimah, N., Ashraf, S., R. U., K. N., Anju, P. B., Showkat, M., Perveen, K., Bukhari, N. A., et al. (2024). Evaluation of suitability and biodegradability of the organophosphate insecticides to mitigate insecticide pollution in onion farming. Heliyon, 10(12).

  3. Margay, K. A. A. A. R., Ashraf, S., Fatimah, N., Jabeen, S. G., & Showkat, M., et al. (2024). Plant circadian clocks: Unravelling the molecular rhythms of nature. International Journal of Plant and Soil Science, 36(8), 596–617.

  4. Margay, A. R., Ashraf, S., Fatimah, N., Jabeen, S. G., Showkat, M., R. U., K. N., Gani, A., et al. (2024). Harnessing brassinosteroids for heat resilience in wheat: A comprehensive study.

  5. Showkat, M., Nagesha, N., Ashraf, S., Nayana, K., Bashir, S., Nair, A. S., et al. (2024). Cordycepin: A molecular Trojan horse against Fusarium oxysporum f. sp. cubense—A computational perspective.

Priyadharshini Veeralakshmanan | Clinical Neuroscience | Best Researcher Award

Ms. Priyadharshini Veeralakshmanan | Clinical Neuroscience | Best Researcher Award

Ms. Priyadharshini Veeralakshmanan | Amrita Vishwa Vidyapeetham | India

Ms. Priyadharshini Veeralakshmanan is a dedicated PhD scholar at Amrita Vishwa Vidyapeetham, specializing in Medical Oncology with a focus on Breast Cancer Immunology and the immunosuppressive tumour microenvironment (TME), particularly in Triple-Negative Breast Cancer (TNBC). Her doctoral research involves a Phase 2/3 open-label pilot clinical trial to evaluate neoadjuvant metronomic chemotherapy for modulating the TME and enhancing chemo- and immunotherapy responses, quantifying immunosuppressive cells and tumour-infiltrating lymphocytes from blood and tumour tissue. She holds an M.Sc. in Physician Assistant (Medical Oncology) and a B.Sc. in Physician Assistant (General Medicine), with extensive clinical training in oncology, hematology, surgical oncology, radiation oncology, and palliative care. Priyadharshini has strong expertise in flow cytometry, cell culture, in vitro drug testing, cytotoxicity assays, systematic reviews, meta-analysis, and clinical trial design, using advanced analytical tools such as FlowJo, SPSS, and GraphPad Prism. She has authored several publications, with an h-index of 3, over 7 documents, and more than 50 citations. A member of ESMO, ASCO, and I-OSI, she is committed to advancing cancer research, translating innovative findings into clinical practice to improve patient outcomes globally.

Profiles: Orcid | Linked In

Featured publications

Veeralakshmanan, P., Jose, W. M., Udayakumaran, S., Bindhu, M. R., Dutta, D., Rajesh, K., Kavalagunta, S., Bhaskaran, R., Haridas, N. K., Rakesh, M. P., et al. (2025). Multimodal management and outcome of pediatric and adolescent malignant central nervous system tumors: A single‐center retrospective study. Malignancy Spectrum.

Surendran, H. P., Sah, S. K., Veeralakshmanan, P., Nair, P., Ashok, H. P., Unnikrishnan, M. K., Kalavagunta, S., Sasidharan, A., Chandran, D., Poornachary, N. M., et al. (2025). Efficacy of hippocampal avoidance whole brain radiotherapy to preserve the cognitive functions among brain metastasis patients: Systematic review and meta-analysis. Neurology India, 73(5), 715–725.

Masoud Kargar | Computational Neuroscience | Best Researcher Award

Assist. Prof. Dr. Masoud Kargar | Computational Neuroscience | Best Researcher Award

Assist. Prof. Dr. Masoud Kargar | Islamic Azad University | Iran

Dr. Masoud Kargar is an Assistant Professor in the Department of Computer Engineering at Islamic Azad University, Tabriz Branch, specializing in artificial intelligence, machine learning, reinforcement learning, and software system engineering. He earned his bachelor’s degree in applied mathematics, master’s degree in software engineering, and Ph.D. in software engineering with a focus on modularization of multi-programming software systems. Dr. Kargar has extensive academic experience, having taught a wide range of undergraduate, master’s, and doctoral courses in advanced programming, algorithms, software engineering, data mining, big data, project management, and natural language processing across multiple universities. He also serves as the Director of Information and Communication Technology and leads the development of various software systems. Dr. Kargar is a member of the editorial board of the Iranian Journal of Computer Science (Springer) and has published 19 documents, which have been cited 89 times, giving him an h-index of 6. His research contributions have significantly advanced the fields of machine learning and software engineering, and his academic leadership continues to inspire both students and colleagues. Dr. Kargar remains committed to fostering innovation and excellence in computer engineering education and research.

Profiles: Scopus | Google Scholar | Orcid | Research Gate

Featured Publications

Karegar, M., Isazadeh, A., Fartash, F., Saderi, T., & Navin, A. H. (2008). Data-mining by probability-based patterns. Proceedings of the 30th International Conference on Information Technology Interfaces, 28.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2019). Multi-programming language software systems modularization. Computers & Electrical Engineering, 80, 106500.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2017). Semantic-based software clustering using hill climbing. 2017 International Symposium on Computer Science and Software Engineering.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2020). Improving the modularization quality of heterogeneous multi-programming software systems by unifying structural and semantic concepts. Journal of Supercomputing, 76(1), 17.

Navin, A. H., Fesharaki, M. N., Mirnia, M., & Kargar, M. (2007). Modeling of random variable with digital probability hyper digraph: Data-oriented approach. Proceedings of World Academy of Science, Engineering and Technology, 25, 25.

Bayani, A., & Kargar, M. (2024). LDCNN: A new arrhythmia detection technique with ECG signals using a linear deep convolutional neural network. Physiological Reports, 12(17), e16182.

Karegar, M., Saderi, T., Isazadeh, A., & Fartash, F. (2008). Electronic consulting in marketing. 2008 3rd International Conference on Information and Communication Technology, 5.

VIKRAM SINGH KARDAM | Neuroinformatics | Best Researcher Award

Mr. VIKRAM SINGH KARDAM | Neuroinformatics | Best Researcher Award

Mr. VIKRAM SINGH KARDAM, DTU DELHI, India.

Vikram Singh Kardam is a dedicated researcher and academician specializing in signal processing, currently pursuing his Ph.D. at Delhi Technological University (DTU). With a strong educational foundation, including an M.Tech in Signal Processing and Digital Design, and a B.Tech in Electronics and Communication Engineering, he has consistently demonstrated academic excellence. Vikram has diverse professional experience, having worked both in industry and academia, including roles as a Project Engineer and Assistant Professor. His innovative M.Tech thesis on real-time iris recognition highlights his ability to apply advanced concepts to practical challenges in biometric security. Proficient in multiple programming languages and known for his problem-solving attitude, he blends technical skill with teaching acumen, influencing students and peers alike. His GATE rank and contributions to student development further underscore his commitment to excellence in engineering and education.

Profile

Scopus

 

🎓 Early Academic Pursuits

Vikram Singh Kardam’s academic journey began with a solid foundation in science and technology. He completed his 10th and 12th education from Government Inter College, Agra, achieving commendable marks that laid the groundwork for his future in engineering. His higher education commenced at the University Institute of Engineering and Technology, CSJM University, Kanpur, where he earned his Bachelor of Technology in Electronics and Communication Engineering in 2007 with a respectable score of 73.2%. Driven by a passion for advanced studies, he pursued a Master of Technology in Signal Processing and Digital Design from Delhi Technological University (DTU), securing a CGPA of 8.06 in 2017. His academic path reflects not only consistent effort but also a dedication to the field of signal processing.

🧑‍🏫 Professional Endeavors

Vikram embarked on his professional career with diverse roles that bridged academia and industry. He served as a Project Engineer at ITI Limited, Delhi, and as a Lab Engineer at Dayalbagh Engineering College, Agra, gaining hands-on experience in real-world engineering environments. His passion for teaching led him to academia, where he worked as an Assistant Professor in reputed institutions such as Galgotias College of Engineering and Technology, Greater Noida, and HMR Institute of Technology and Management, Delhi. With around three years of cumulative teaching experience, he has imparted theoretical knowledge and practical insights in Electronics and Communication Engineering, contributing to the academic development of numerous students.

🔬 Contributions and Research Focus

Currently pursuing his Ph.D. in Signal Processing at Delhi Technological University, Vikram Singh Kardam’s research delves into the intricacies of digital signal processing with real-world applications. His M.Tech thesis, titled “Real Time Iris Recognition”, showcases his innovation in biometric security systems. By integrating iris recognition with eye-blinking detection using a basic webcam, he proposed a novel, low-cost, and more secure method for identity verification. The system’s robustness and its resistance to hacking highlight his ability to merge theoretical concepts with practical utility. His fluency in programming languages such as MATLAB, C, C++, and Python3 supports his technical versatility in algorithm development and simulation.

🏅 Accolades and Recognition

A noteworthy milestone in Vikram’s academic journey is securing an All India Rank of 5334 in the GATE 2021 examination in Electronics and Communication Engineering. This national-level achievement is a testament to his strong grasp of core concepts and problem-solving acumen. Additionally, his academic performances during B.Tech and M.Tech reflect sustained excellence. His thesis project, recognized for its practical application and innovative approach, further enhances his academic reputation.

📚 Impact and Influence

In his role as an Assistant Professor, Vikram Singh Kardam has significantly influenced his students’ academic and professional growth. His commitment to regularly conducting lectures, his focus on ensuring student understanding, and his hands-on approach to lab sessions highlight his dedication to holistic teaching. Beyond knowledge delivery, his empathetic and analytical mindset enables him to mentor students, offer academic guidance, and solve problems effectively. His ability to integrate teaching with research creates an inspiring learning environment.

🌐 Legacy and Future Contributions

Looking forward, Vikram aspires to contribute to both academia and industry through innovative research in signal processing, embedded systems, and biometric technology. His current Ph.D. pursuits are expected to yield impactful contributions to the scientific community, particularly in the areas of real-time data analysis and secure identification systems. With a forward-thinking vision, he aims to blend educational excellence with technological advancement, fostering a new generation of engineers equipped with both critical thinking and creative problem-solving skills.

🧠 Vision and Intellect

At the core of Vikram Singh Kardam’s career is a mindset defined by curiosity, dedication, and the pursuit of knowledge. A quick learner and an effective communicator, he embodies the spirit of modern engineering – adaptive, analytical, and collaborative. His ability to learn and implement complex systems, along with his respect for students and colleagues, reflects not just technical competence but also emotional intelligence. As a lifelong learner and educator, he is poised to make enduring contributions in signal processing and beyond.

Publication

  • Title: BSPKTM-SIFE-WST: Bispectrum based channel selection using set-based-integer-coded fuzzy granular evolutionary algorithm and wavelet scattering transform for motor imagery EEG classification

  • Authors: V.S. Kardam, S. Taran, A. Pandey

  • Year: 2025

 

 

Conclusion

Vikram Singh Kardam stands out as a promising scholar and educator in the field of signal processing. His journey reflects a balance of theoretical rigor, practical implementation, and a passion for continuous learning. With a future-oriented mindset, he is poised to make meaningful contributions to biometric systems, digital design, and the broader engineering community. As he advances through his doctoral research and professional engagements, Vikram’s legacy is one of innovation, dedication, and impactful mentorship in the evolving landscape of technology and education.

Koagne Longpa Tamo Silas | Neuroinformatics | Pioneer Researcher Award

Mr. Koagne Longpa Tamo Silas | Neuroinformatics | Pioneer Researcher Award

Mr.  Koagne Longpa Tamo Silas, University of Dschang, Cameroon.

Koagne Longpa Tamo Silas is a dedicated researcher in the field of medical physics, specializing in automation, artificial intelligence, and electronic system design. His academic journey from Bamenda State University to Dschang State University reflects his continuous pursuit of knowledge and innovation. His contributions to circuit simulation, embedded systems, and artificial neural networks have established him as a promising figure in medical physics.

Profile

Google Scholar

🎓 Early Academic Pursuits

Born on July 12, 1998, in Mbouda, Cameroon, Koagne Longpa Tamo Silas displayed a keen interest in science and technology from a young age. His passion for physics and engineering led him to pursue higher education at Bamenda State University, where he embarked on an academic journey in Electrical and Power Engineering. His undergraduate studies, from November 2015 to August 2018, laid the foundation for his expertise in electrical systems, automation, and circuit design. Eager to expand his knowledge, he continued his postgraduate studies in the same field at Bamenda State University from September 2018 to July 2020, honing his skills in power engineering and applied electronics.

🚀 Professional Endeavors

Determined to deepen his expertise, Koagne Longpa Tamo Silas transitioned into the field of physics, enrolling as a Ph.D. student at Dschang State University in December 2022. His academic pursuits in the Department of Physics align with his interests in medical physics, where he integrates automation, applied computer science, and electronics to innovate in the field. As a dedicated researcher, he continues to engage with the Faculty of Science at Dschang State University, contributing to the academic and scientific community with his research in medical physics and embedded systems.

🤖 Contributions and Research Focus

Koagne Longpa Tamo Silas has dedicated his research efforts to the intersection of medical physics, automation, and artificial intelligence. His work encompasses Analog Artificial Neural Networks, Embedded Systems, Circuit Simulation, Digital and Analog Electronics, and Microcontroller Programming. His proficiency in tools like Spice Simulation, Cadence Virtuoso, and Electronic Design Automation allows him to design and optimize medical devices and automated systems. His research aims to enhance diagnostic and therapeutic tools in medical physics by leveraging artificial intelligence and embedded systems.

🏆 Accolades and Recognition

Throughout his academic and research career, Koagne Longpa Tamo Silas has garnered recognition for his contributions to medical physics and electronics. His innovative approach to circuit simulation and signal processing has positioned him as a promising researcher in his field. His dedication to advancing medical technologies has earned him the respect of his peers and mentors, as he continues to contribute valuable insights to the scientific community.

🌐 Impact and Influence

Through his academic journey and research, Koagne Longpa Tamo Silas has influenced the way automation and artificial intelligence are integrated into medical physics. His work in digital electronics and microcontroller programming is paving the way for innovative solutions in the medical field. His contributions extend beyond research, as he actively engages with students and researchers, fostering a culture of knowledge-sharing and scientific exploration.

 

Publication

  • A High-Resolution Non-Volatile Floating Gate Transistor Memory Cell for On-Chip Learning in Analog Artificial Neural Networks
    Authors: KLT Silas, DTA Bernard, FT Bernard, L Jean-Pierre, GW Ejuh
    Year: 2025

 

  • Breast Cancer Diagnosis with Machine Learning Using Feed-Forward Multilayer Perceptron Analog Artificial Neural Network
    Authors: B Djimeli-Tsajio Alain, KLT Silas, LT Jean-Pierre, N Thierry, GW Ejuh
    Year: 2024

 

  • Design and Implementation of a Digital Breath Alcohol Detection System with SMS Alert and Vehicle Tracking on Google Map
    Author: KLT Silas
    Year: 2020

 

  • Design and Realization of an Electronic Attendance System Based on RFID with an Automatic Door Unit
    Author: MK Jules
    Year: 2018

 

🎯 Conclusion

With a vision to transform medical physics through automation and AI-driven technologies, Koagne Longpa Tamo Silas is on a path to making significant contributions to healthcare innovation. His passion, dedication, and expertise ensure that his research will continue to shape the future of medical technology, leaving a lasting impact on both academia and practical applications in the field.