Wisal Zafar | AI in Healthcare | Data Scientist of the Year Award

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Mr. Wisal Zafar | AI in Healthcare | Data Scientist of the Year Award

Lecturer at Cecos University of IT and Emerging Sciences, Pakistan

Wisal Zafar is a dynamic academic and research-oriented professional whose expertise lies at the intersection of data science, artificial intelligence, and deep learning. With a strong foundation in software engineering, he has progressively transitioned into data-centric domains where he now actively contributes as a lecturer, researcher, and data scientist. His work integrates modern machine learning techniques and neural networks to tackle real-world problems ranging from healthcare to education. His career is marked by a drive to foster innovation through technology, an unwavering commitment to academic excellence, and a passion for nurturing student potential in both undergraduate and postgraduate settings.

Profile

Scopus

Education

Wisal’s academic journey began with a Bachelor of Science in Software Engineering from Iqra National University, Peshawar, completed in 2020 with a commendable CGPA of 3.47/4.00. Building on this strong foundation, he pursued a Master of Science in Software Engineering at the same university, expected to be completed by mid-2024, where he currently holds a CGPA of 3.50/4.00. His academic record reflects a consistent pursuit of knowledge and skill advancement in software technologies, deep learning, and data analysis. Prior to his university education, he completed his Intermediate from Capital Degree College and matriculation from The Jamrud Model High School with notable academic performances.

Experience

Professionally, Wisal has held several key positions in academia and data processing. He is currently serving as a Lecturer at CECOS University of IT and Emerging Sciences, Peshawar, where he imparts advanced-level knowledge in Artificial Intelligence, Data Science, and Machine Learning. Before this, he contributed significantly to Iqra National University both as a Lecturer and as an EDP Officer, where he oversaw electronic data processing and optimized data accessibility across research and academic projects. His roles have consistently involved not only teaching but also mentorship, particularly in guiding final-year students through research and development of innovative software solutions. His earlier professional engagements also include roles as a Junior Web Developer and teaching positions, showcasing a diverse skill set in both educational and technical domains.

Research Interests

Wisal’s research interests are rooted in the application of artificial intelligence and machine learning to critical societal challenges. His work spans brain tumor detection, plant disease classification, emotion recognition in educational settings, and mental health analysis using social media data. He is particularly intrigued by hybrid deep learning architectures, transformer-based models, and neural networks. He consistently integrates image processing techniques and NLP tools to build intelligent, data-driven solutions. His recent focus includes real-time decision support systems, content-based image retrieval, and multi-scale classification, which have promising implications for both healthcare and education systems.

Awards

In recognition of his exceptional contribution to the academic and technical environment, Wisal was honored with the “Best Employee of the Year 2023” award at Iqra National University. This accolade acknowledges his consistent performance, innovative approach to teaching and research, and his ability to blend administrative responsibilities with cutting-edge academic delivery. His recognition serves as a testament to his dedication, collaborative spirit, and leadership potential in the academic research community.

Publications

Wisal has made significant scholarly contributions, with several research publications in high-impact international journals. His paper “Enhanced TumorNet: Leveraging YOLOv8s and U-Net for Superior Brain Tumor Detection and Segmentation Utilizing MRI Scans” was published in Results in Engineering (2024) and is cited for its innovative approach to medical imaging using hybrid models. Another influential work, “Revolutionizing Diabetes Diagnosis: Machine Learning Techniques Unleashed”, appeared in MDPI-Healthcare (2023) and explores diagnostic modeling using AI techniques. His third publication, “A Survey on Big Data Analytics (BDA) Implementation and Practices in Medical Libraries of Punjab”, published in the Journal of Computing & Biomedical Informatics (2023), provides insights into the integration of BDA in healthcare information systems. These publications highlight his range—from healthcare diagnostics to knowledge systems—and his adaptability in multiple AI-driven domains.

Conclusion

Wisal Zafar stands out as a highly motivated data scientist and academician with a clear vision for the future of AI and its applications. Through his diverse academic background, hands-on teaching experience, impactful research, and recognized contributions to institutional growth, he exemplifies the qualities of an innovative thinker and dedicated professional. His continued exploration of deep learning and intelligent systems is not only enriching the academic field but also paving the way for practical solutions to societal challenges. With a growing portfolio of research and a keen eye for technological advancements, Wisal is well-poised to make long-term contributions to AI-based research and higher education. His career trajectory illustrates a seamless blend of academic rigor, technical skill, and research excellence.

Ali Ghulam | AI in Healthcare | Best Researcher Award

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Dr. Ali Ghulam | AI in Healthcare | Best Researcher Award

Assistant Professor at Information Technology Centre, Sindh Agriculture University, Pakistan

Dr. Ghulam Ali is an accomplished academic and researcher specializing in artificial intelligence (AI) and bioinformatics. He earned his Ph.D. in Computer Software and Theory from Shaanxi Normal University, Xi’an, China, in 2020. Currently, he serves as an Assistant Professor at the Information Technology Centre, Sindh Agriculture University, Tandojam. His research focuses on human disease pathway network modeling, biological pathway database discovery, and AI-driven predictions related to proteins, drugs, and diseases. With over 20 published SCI articles in high-impact journals and extensive contributions to machine learning applications in bioinformatics, Dr. Ali is a recognized expert in his field.

Profile

Orcid

Education

Dr. Ali pursued his Ph.D. from Shaanxi Normal University, Xi’an, China, specializing in bioinformatics and AI. His thesis, titled “Prediction of Pathway Related Protein, Drug and Disease Association Based on Complex Network and Deep Learning,” was supervised by Prof. Xiujuan Lei. He completed his M.Phil. in Computer Science with a specialization in Search Engine Optimization from the University of Sindh, Jamshoro. His academic journey began with a Bachelor of Computer Science (BCS-Hons) from the same university. Additionally, he obtained various certifications and diplomas in information technology, further strengthening his expertise in computing and AI.

Experience

Dr. Ali has a strong academic and research background, currently holding the position of Assistant Professor at Sindh Agriculture University, Tandojam. His professional journey includes extensive work on bioinformatics, AI-based predictive models, and computational biology. He has contributed significantly to research in AI applications for human protein sequence analysis, disease detection, and biomedical data transformation. With a deep understanding of AI, deep learning, and machine learning techniques, he has played a pivotal role in advancing bioinformatics research and education.

Research Interests

Dr. Ali’s research primarily revolves around bioinformatics and artificial intelligence. He is particularly focused on human disease pathway modeling, drug-protein interaction prediction, and machine learning applications in genomics. His work involves utilizing AI to enhance precision diagnostics, early-stage disease detection, and advanced biomedical data analysis. By leveraging deep learning and AI-driven methodologies, Dr. Ali aims to improve healthcare analytics and disease treatment strategies. His research has practical implications in the fields of computational biology, digital health frameworks, and AI-driven medical solutions.

Awards and Recognitions

Dr. Ali has received numerous accolades for his contributions to AI and bioinformatics research. His high-impact factor publications and citations reflect his significant contributions to the scientific community. With an H-index of 12 on Google Scholar, an i10-index of 18, and a ResearchGate H-index of 11, his research has been widely recognized and cited. He has also been nominated for various research excellence awards, highlighting his influence in the field of computational biology and AI-driven biomedical advancements.

Publications

Ali, Ghulam, et al. (2025). “StackAHTPs: An explainable antihypertensive peptides identifier based on heterogeneous features and stacked learning approach.” IET Systems Biology, 19(1), e70002. (SCI, IF: 1.9, Cited by: X).

Arif, Muhammad, et al. (2024). “StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features.” Methods, 230, 129-139. (SCI, IF: 4.02, Cited by: X).

Arif, Muhammad, et al. (2024). “DPI_CDF: Druggable protein identifier using cascade deep forest.” BMC Bioinformatics, 25(1), 1-18. (SCI, IF: 3.09, Cited by: X).

Talpur, Fauzia, et al. (2024). “ML-Based Detection of DDoS Attacks Using Evolutionary Algorithms Optimization.” Sensors, 24(5), 1672. (SCI, IF: 3.09, Cited by: X).

Ghulam, Ali, et al. (2024). “Assessment of Performance of Machine Learning Classification Techniques for Monkey Pox Disease Detection.” Journal of Innovative Intelligent Computing and Emerging Technologies, 1(1), 1-7. (Cited by: X).

Memon, Mukhtiar, et al. (2023). “AiDHealth: An AI-enabled Digital Health Framework for Connected Health and Personal Health Monitoring.” (Cited by: X).

Sikander, Rahu, et al. (2023). “Identification of cancerlectin proteins using hyperparameter optimization in deep learning and DDE profiles.” Mehran University Research Journal of Engineering & Technology, 42(4), 28-40. (WoS, Cited by: X).

Conclusion

Dr. Ghulam Ali is a distinguished researcher and academician in the field of artificial intelligence and bioinformatics. His contributions to AI-driven biomedical research, particularly in disease pathway modeling and predictive analytics, have significantly advanced the field. With a strong publication record, multiple citations, and a commitment to innovation, he continues to influence computational biology and digital health research. His work bridges the gap between AI and medical sciences, paving the way for future breakthroughs in bioinformatics and AI-driven healthcare solutions.

Neeraj Thakur | AI in Healthcare | Best Researcher Award

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Dr. Neeraj Thakur | AI in Healthcare | Best Researcher Award

Postdoctoral Fellow at University of Oklahoma Health Sciences, United States

Dr. Neeraj S. Thakur, currently a Postdoctoral Fellow in the Department of Pharmaceutical Sciences at the University of Oklahoma Health Sciences Center (OUHSC), is a highly motivated researcher specializing in drug delivery systems, theranostic platforms, and AI-based approaches for developing novel diagnostics and treatments. With over a decade of international research experience spanning the USA, Europe, and Asia, Dr. Thakur has led multiple projects related to nanomaterial design, formulation development, and the synthesis of advanced drug delivery systems for treating diseases like cancer and infections. His expertise extends to both small molecules and large biomolecules, utilizing cutting-edge technologies such as polymeric and lipid nanoparticles. He has an extensive publication record with 29 papers, five patents, six book chapters, and significant contributions to the field.

Profile

Scopus

Education

Dr. Thakur earned his Ph.D. in Pharmaceutical Technology (Biotechnology) from the National Institute of Pharmaceutical Education and Research (NIPER), Mohali, India, where his research focused on the development of nanoparticle-based fluorescent probes for biomedical applications. He also holds an M.Tech in Pharmaceutical Technology (Biotechnology) from NIPER, Mohali, where he was the class topper, and a B.Pharm degree from Shri G.S. Institute of Technology and Science, Indore. Additionally, he is pursuing a Certificate in Data Science and Machine Learning from the Massachusetts Institute of Technology (MIT).

Experience

Dr. Thakur has held significant roles in various research institutions. As a Postdoctoral Fellow at OUHSC, he established research laboratories and led projects on nanomaterial development for drug delivery systems targeting multiple applications, including inner ear and ocular delivery. Prior to this, he worked at the University of Geneva, Switzerland, where he developed hybrid micelle formulations for transdermal delivery and designed iontophoretic devices. He also contributed to the Center of Innovative and Applied Bioprocessing (CIAB), India, where he led the development of topical drug delivery systems and was involved in several patent filings. These experiences have honed his skills in formulation and analytical development, laboratory management, and industrial collaboration.

Research Interests

Dr. Thakur’s research interests focus on the development of advanced drug delivery systems, particularly using nanomaterials such as polymeric and lipid nanoparticles. His work aims to improve the therapeutic efficacy of drugs by enhancing their delivery to specific sites in the body, such as the inner ear, ocular tissues, and tumors. He is also dedicated to the integration of AI-based approaches for optimizing drug delivery design, ensuring more precise treatments for conditions like cancer and ototoxicity. His passion extends to the creation of theranostic platforms for early disease diagnosis and personalized medicine.

Awards

Throughout his career, Dr. Thakur has received numerous accolades for his contributions to pharmaceutical sciences. Notable among them are the John B. Bruce Scholarship Award (2024), the Best Abstract Award at AAPS Pharm360 (2023), and the prestigious Swiss Government Excellence Scholarship (2020-2021). His earlier achievements include the DST-INSPIRE and CSIR Research Fellowships, which are awarded to the top 1% of students in India. These recognitions underscore his impact on the scientific community and his leadership in advancing pharmaceutical research.

Publications

Dr. Thakur has authored 29 peer-reviewed papers, with some of his recent work focused on innovative drug delivery systems. Key publications include:

Thakur, N.S., et al., “Crosslinked Hybrid Nanoparticle Embedded in Thermogel For Sustained Co-Delivery to Inner Ear,” Journal of Nanobiotechnology, 2024.

Thakur, N.S., et al., “Progress and Promise of Photoresponsive Nanocarriers for Precision Drug Delivery in Cancer,” Journal of Photochemistry & Photobiology C: Photochemistry Reviews, 2024.

Thakur, N.S., et al., “Dual Stimuli-Responsive and Sustained Drug Delivery Nanosensogel for Prevention of Cisplatin-Induced Ototoxicity,” Journal of Controlled Release, 2024.

Paul, S., et al., “Co-Administration of Chemo-Phototherapeutic Loaded Lignin Nanoarchitecture for Skin Cancer and Bacterial Infections,” ACS Applied Nano Materials, 2024.

Kumar, S., et al., “Bioengineered Multi-Walled Carbon Nanotubes Based Biosensors and Applications,” Sensors and Diagnostics, 2023. These works, which cover nanomedicine, drug delivery, and nanomaterial innovation, have significantly contributed to the field of pharmaceutical sciences and have been widely cited.

Conclusion

Dr. Neeraj S. Thakur’s multifaceted career highlights his dedication to advancing pharmaceutical research through innovation in nanotechnology and drug delivery systems. His profound knowledge in both academic and industrial settings, along with his leadership in driving collaborative research projects, continues to position him as a key figure in his field. With a focus on precision medicine, AI-based design, and the development of targeted therapies, Dr. Thakur is making remarkable strides toward improving patient outcomes and advancing the future of drug delivery and diagnostics.