Sajjad Saleem is a computer science researcher based in New Jersey with a Master’s in Information Technology from Washington University of Science and Technology. His expertise spans artificial intelligence, deep learning, and image processing, with impactful applications in agriculture and healthcare. He has developed innovative solutions for multi-crop disease detection and early diagnosis of Alzheimer’s and lung diseases. Sajjad thrives in interdisciplinary teams, turning complex datasets into actionable insights. With strong skills in data analytics and statistical tools, he also contributes as a peer reviewer for reputed journals like IEEE Access and Springer. Passionate about sustainable agriculture and precision medicine, he continuously explores ways to improve diagnostics and crop yield prediction through AI. His work integrates technical depth with real-world relevance, making him a valuable contributor to both academic and applied research landscapes.
Profile
Scholar
🎓 Education
Sajjad Saleem holds an MS in Information Technology (Data Analytics and Management) from Washington University of Science and Technology, completed in 2024. During his graduate studies, he specialized in artificial intelligence and data analytics, developing projects and research around deep learning applications in medical diagnostics and agriculture. Prior to this, he earned a Bachelor of Business Administration from COMSATS University Islamabad, Lahore Campus (2016–2020), where he cultivated foundational knowledge in management sciences and research methodologies. His unique combination of business and technology education empowers him to address real-world problems using AI solutions. Sajjad’s education is enriched by hands-on experience with tools like SPSS, SQL, Tableau, and Cloudera, along with advanced training in machine learning, research analytics, and data management. His academic journey reflects a continuous commitment to leveraging data-driven technologies for solving contemporary challenges in both business intelligence and scientific research.
💼 Experience
Sajjad’s professional experience is a blend of academic research, data analytics, and peer reviewing. He currently works as a Data Analyst at Technova Systems Inc. in Virginia, utilizing advanced analytics and visualization techniques to support decision-making. From 2016 to 2020, he served as a Research Assistant at COMSATS University Lahore, engaging in research design, literature reviews, and data interpretation. Sajjad is also an active journal peer reviewer, having reviewed over 32 manuscripts for prestigious journals like IEEE Access, Springer Scientific Reports, Wiley’s Developmental Neurobiology, and Frontiers in Plant Science. His reviews span AI, plant science, and developmental neuroscience. This exposure to cutting-edge research across disciplines has deepened his understanding and critical evaluation skills. His experience reflects a strong analytical mindset, collaboration in multidisciplinary environments, and a dedication to advancing both academic and applied research frontiers in AI, agriculture, and healthcare.
🏅 Awards and Honors
Sajjad Saleem has gained recognition primarily through his academic contributions and peer-review roles. He has reviewed over 32 research manuscripts, reflecting his credibility and expertise in fields such as artificial intelligence, plant science, and developmental neurobiology. His trusted status as a reviewer for top-tier journals like IEEE Access and Springer’s Scientific Reports highlights his ability to assess cutting-edge research critically. He has contributed significantly to maintaining publication standards across diverse domains, including medical diagnostics and agricultural AI. While specific awards are not listed, his selection as a reviewer and consistent participation in scholarly publication processes stand as professional honors. These roles not only acknowledge his subject matter expertise but also illustrate his commitment to academic integrity and knowledge dissemination. His research publications and contributions in deep learning applications have further strengthened his academic profile, positioning him as an emerging expert in AI-driven precision solutions.
🔬 Research Focus
Sajjad Saleem’s research is centered on the intersection of artificial intelligence and real-world problem-solving in agriculture and healthcare. His work in deep learning addresses critical issues such as crop disease detection, early Alzheimer’s diagnosis, and lung disease classification. His recent projects involve hybrid neural architectures combining NASNet, Vision Transformers, and wrapper-feature selection techniques to optimize accuracy in medical imaging. In agriculture, he has developed enhanced models for multi-crop leaf disease detection and wheat disease classification using feature fusion strategies. Sajjad’s overarching goal is to harness AI to support precision farming, sustainable agriculture, and efficient diagnostics. He also explores the socio-technical impacts of cybercrime, HR analytics, and AI integration in business management. His interdisciplinary research not only contributes to academic literature but also has real-world applications, improving yield prediction, disease diagnosis, and organizational performance through intelligent systems and data analytics.
📝 Conclusion
Sajjad Saleem is a promising researcher whose interdisciplinary expertise in AI, deep learning, and image processing offers substantial contributions to both the agricultural and medical sectors. His publications, peer review experience, and technical skills place him in an excellent position for the Young Scientist Award. By expanding his focus on societal impacts and engaging with industry leaders, Sajjad can further solidify his standing as a thought leader in the fields of AI-driven agriculture and healthcare solutions.
Publication
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Title: Comparison of Deep Learning Models for Multi-Crop Leaf Disease Detection with Enhanced Vegetative Feature Isolation and Definition of a New Hybrid Architecture
Year: 2024
Authors: S Saleem, MI Sharif, MI Sharif, MZ Sajid, F Marinello
Citations: 10
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Title: Untapped potential and country-of-origin: do employee attitudes and HR analytics boost career growth with a COM-B model application
Year: 2024
Authors: S Sattar, M Bukhari, S Saleem, S Ijaz, S Ejaz, K Al Sulaiti, J Abbas
Citations: 5
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Title: A Multi-Scale Feature Extraction and Fusion Deep Learning Method for Classification of Wheat Diseases
Year: 2025
Authors: S Saleem, A Hussain, N Majeed, Z Akhtar, K Siddique
Citations: 2
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Title: Deep Learning-Based Approach for Identification of Potato Leaf Diseases Using Wrapper Feature Selection and Feature Concatenation
Year: 2025
Authors: M Ahtsam Naeem, M Asim Saleem, MI Sharif, S Akber, S Saleem, …
Citations: 1*
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Title: The Impact of Cybercrime Incidents and Artificial Intelligence Adoption on Organizational Performance: A Mediated Moderation Model
Year: 2024
Authors: M Bukhari, S Sattar, S Saleem, KZ Khan, A KHAN
Citations: 1
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Title: Deep Learning in Early Alzheimer’s Diseases Detection: A Comprehensive Survey of Classification, Segmentation, and Feature Extraction Methods
Year: 2025
Authors: R Hafeez, S Waheed, SA Naqvi, F Maqbool, A Sarwar, S Saleem, …
Citations: 0 (arXiv:2501.15293)