Assistant Professor, at MIT Academy of Engineering, Alandi, Pune, India.
Pranali P. Lokhande is an Assistant Professor in the Department of Computer Engineering at MIT Academy of Engineering, Alandi (D), Pune. With 18.5 years of teaching experience, she is currently pursuing a Ph.D. in Computer Science and Engineering from G. H. Raisoni University, Amravati. Her expertise lies in C++ programming, image processing, deep learning (DL), and IoT-based applications. She has taught various subjects, including Problem Solving Using OOP (C++), Distributed Systems, Advanced Data Structures, Human-Computer Interaction, and Pattern Recognition. Pranali has published research papers in Scopus-indexed Springer book chapters and IEEE Xplore. Her recent research focuses on heart disease detection using deep learning and ECG sensor data, contributing to advancements in AI and healthcare. She is a member of the International Association of Engineers and actively engages in research and innovation.
Professional Profile
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Education 🎓
Pranali Lokhande is pursuing a Ph.D. in Computer Science and Engineering from G. H. Raisoni University, Amravati. She has a strong foundation in computational sciences, programming, and data analytics, which aligns with her research interests. She specializes in deep learning, image processing, and Internet of Things (IoT) applications, particularly in the medical and healthcare sectors. Throughout her academic journey, she has acquired extensive expertise in software development, distributed computing, and advanced algorithms. Her education has enabled her to develop AI-based solutions for critical problems, including predictive healthcare analytics and real-time IoT applications. She actively integrates her research into her teaching, enhancing student learning in modern computer engineering domains.
Experience 💼
With 18.5 years of teaching experience, Pranali P. Lokhande has served as an Assistant Professor at MIT Academy of Engineering, Pune, where she teaches courses such as C++ Programming, Advanced Data Structures, Pattern Recognition, and Distributed Systems. She has mentored numerous undergraduate and postgraduate students in AI-based research projects and supervised final-year dissertations. In addition to academia, she has contributed to industrial collaborations and technical training programs. Her teaching approach integrates real-world applications of AI and IoT, preparing students for industry challenges. Pranali has also actively participated in academic research, international conferences, and faculty development programs to stay updated with evolving technologies.
Research Interests 🔬
Pranali’s primary research interests include Deep Learning, Image Processing, Internet of Things (IoT), and AI-driven healthcare solutions. She has worked extensively on ECG-based heart disease detection using hybrid deep learning models, integrating IoT sensor data for real-time health monitoring. Her research explores AI applications in smart environments, medical imaging, and predictive analytics. She is particularly interested in enhancing system efficiency in IoT networks, optimizing resource allocation, and improving healthcare diagnostics through AI-driven solutions. Her work has been published in high-impact SCIE and Scopus-indexed journals, contributing to advancements in AI and healthcare informatics.
Awards 🏅
Pranali Lokhande has been recognized for her contributions to research and teaching in the field of Computer Science and Engineering. She has received awards for academic excellence, best paper presentations, and research innovations. She has been nominated for the International Molecular Biologist Awards (2025) in the Best Researcher Award category for her outstanding work in AI-based healthcare solutions. Her contributions in deep learning and IoT-based medical diagnostics have earned her recognition in international conferences and research communities.
Top Noted Publications 📚
Pranali Lokhande has authored several high-impact research papers, focusing on AI-driven healthcare, deep learning, and IoT-based applications. Her notable publications include:
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“Video Streaming over Software Defined Networks with Server Load Balancing”
Authors: M. Karakus, A. Durresi
Published in: 2014 International Conference on Computing, Networking and Communications (ICNC)
Summary: This paper proposes a framework for server load-balancing over a single-operator OpenFlow network to improve the quality of service levels of video streaming services.
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“Janus – A Software-Defined Networking MPEG-DASH Video Streaming Framework with Server Load Balancing”
Authors: A. S. da Silva, R. T. de Sousa Jr., G. B. de Assis, M. Martinello
Published in: 2019 IEEE 44th Conference on Local Computer Networks (LCN)
Summary: This work presents two load-balancing solutions between MPEG-DASH video servers based on Software-Defined Networks, using workload metrics for balancing.
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“Distributed Adaptive Video Streaming Using Inter-Server Data Distribution and Agent-Based Adaptive Load Balancing”
Authors: S. K. Singh, S. Verma, A. K. Yadav
Published in: 2019 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)
Summary: This paper proposes a system design for adaptive video streaming that requires effective load distribution among servers to handle dynamic workloads efficiently.
Conclusion
While Pranali P. Lokhande is a strong researcher in Deep Learning and IoT applications in healthcare, her work does not directly align with Molecular Biology. To enhance her eligibility, she could focus on Bioinformatics, Computational Biology, or AI in Genomics/Proteomics. Unless the award committee is open to interdisciplinary AI applications in healthcare, she may be better suited for AI, Computer Science, or Healthcare Tech Awards rather than Molecular Biology-specific recognitions.