Sushama Deshmukh | Computer Science | Best Researcher Award

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Mrs. Sushama Deshmukh | Computer Science | Best Researcher Award

Assistant Professor at JNEC MGMU Aurangabad, India

Summary:

Mrs. Sushama Deshmukh is an experienced academic and researcher with over 17 years in the field of computer engineering. She is currently pursuing her Ph.D. in Computer Engineering from Dr. Babasaheb Ambedkar Marathwada University (Dr. B.A.M.U.), Aurangabad. She holds a Master of Engineering in Computer Science and Engineering from Government Engineering College, Aurangabad, and a Bachelor of Engineering in Information Technology from Jawaharlal Nehru Engineering College, Aurangabad. Mrs. Deshmukh has served as an Assistant Professor at JNEC MGMU and Maharashtra Institute of Technology, Chhatrapati Sambhajinagar, where she has taught various courses including Artificial Intelligence, Machine Learning, Software Engineering, and Cybersecurity. Her research interests span across Artificial Neural Networks, Machine Learning, Security, and Software Engineering. In addition to her academic roles, Mrs. Deshmukh has been involved in developing software applications like the “Software Engineering Virtual Lab Simulator” and the “Vaccination Management System (VACC-IT).” She is also active in professional development, holding certifications in AI, deep learning, natural language processing, and database systems, reflecting her dedication to continuous learning and innovation in the field.

Profile:

Education:

Mrs. Sushama Deshmukh is currently pursuing her Ph.D. in Computer Engineering from Dr. Babasaheb Ambedkar Marathwada University (Dr. B.A.M.U.), Aurangabad, demonstrating her ongoing commitment to advancing her expertise in the field. She holds a Master of Engineering (M.E.) in Computer Science and Engineering from Government Engineering College, Aurangabad, under Dr. B.A.M.U., where she graduated in 2018 with First Division, securing 68.54%. Additionally, she earned a Bachelor of Engineering (B.E.) in Information Technology from Jawaharlal Nehru Engineering College, Aurangabad, in 2006, graduating with Distinction at 66.04%. Mrs. Deshmukh also holds a Diploma in Medical Electronics from Government W.R.P. Latur, completing the program in 2001 with First Division at 60%. Her diverse educational background spans multiple fields, showcasing her deep and versatile understanding of engineering, technology, and interdisciplinary subjects.

Professional Experience:

Mrs. Sushama Deshmukh has accumulated over 17 years of professional experience in academia, primarily in the field of computer engineering. She is currently serving as an Assistant Professor at JNEC MGMU, Chhatrapati Sambhajinagar, since February 2024. Prior to this, she spent 14.2 years at the Maharashtra Institute of Technology, Chhatrapati Sambhajinagar, where she held positions as both an Assistant Professor and Lecturer. During her tenure, she has taught a diverse range of undergraduate courses, including Software Engineering, Artificial Intelligence and Applications, Database Management Systems, and Cybersecurity, among others. In addition to her teaching responsibilities, Mrs. Deshmukh has taken on various leadership roles, such as Training & Placement Coordinator and MoU Coordinator for the Centre of Excellence in Cyber Security and Cyber Forensics. She has also contributed significantly to curriculum development and practical examinations as the Department Practical Exam Coordinator and Lab In Charge. Her involvement in developing software projects, such as the “Vaccination Management System” and “Online Job Assessment and Tracking System,” further underscores her commitment to integrating practical applications with academic instruction.

Research Interests:

Mrs. Sushama Deshmukh’s research interests are diverse and reflect her expertise in several key areas within computer engineering. She is particularly focused on security, where she explores the latest trends and challenges in protecting digital information. Additionally, her work in Artificial Neural Networks (ANN), artificial intelligence (AI), and machine learning encompasses the development of innovative algorithms and applications that enhance data processing and decision-making. Mrs. Deshmukh is also passionate about software engineering, with an emphasis on virtual labs and experiential learning environments that facilitate hands-on education for students. Her M.Tech project on frequent item set mining in large uncertain datasets demonstrates her commitment to advancing knowledge in data mining and analytics. Through her research, Mrs. Deshmukh aims to contribute to the advancement of technology while addressing real-world problems in cybersecurity and software development.

Skills:

Mrs. Sushama Deshmukh possesses a robust skill set that is well-aligned with her professional and academic pursuits. She is proficient in a variety of programming languages and technologies, including Microsoft SQL Server, WAMP, XAMP, and Turbo C, which enable her to develop and manage complex software applications. Her expertise in artificial intelligence (AI) and machine learning is complemented by certifications in deep learning, natural language processing, and SQL for data science, acquired through reputable platforms like Infosys and Coursera. Additionally, Mrs. Deshmukh has demonstrated her ability to create practical solutions, exemplified by her projects such as the Vaccination Management System and the Online Food Delivery System. Her organizational skills are evident through her roles in coordinating departmental activities and workshops, as well as her involvement in establishing partnerships for the Centre of Excellence in Cyber Security and Cyber Forensics. Overall, her diverse skill set equips her to contribute significantly to both academic and practical applications in her field.

Conclution:

Mrs. Sushama Deshmukh’s combination of academic qualifications, extensive experience, cutting-edge research areas, impactful projects, professional certifications, and social engagement make her a suitable candidate for the Research for Best Researcher Award. Her dedication to interdisciplinary research, practical applications of technology, and community involvement align well with the award’s criteria, emphasizing innovation and societal impact..

Publication Top Noted:

Medi-Block Record: Secure Data Sharing Using Blockchain Technology

  • Authors: C. Singh, D. Chauhan, S.A. Deshmukh, S.S. Vishnu, R. Walia
  • Journal: Informatics in Medicine Unlocked
  • Volume: 24
  • Article Number: 100624
  • ISSN: 2352-9148
  • Year: 2021
  • DOI: 10.1016/j.imu.2021.100624
  • Cited by: 37

Designing User Interfaces with a Data Science Approach

  • Authors: A.N. Banubakode, G.D. Bhutkar, Y. Kurniawan, C.S. Gosavi
  • Publisher: IGI Global
  • Chapter in Book: Designing User Interfaces with a Data Science Approach
  • Year: 2022
  • Cited by: 3

Medi-Block Record: Secure Data Sharing Using Blockchain Technology (Duplicate Entry)

  • Authors: C. Singh, D. Chauhan, S.A. Deshmukh, S.S. Vishnu, R. Walia
  • Journal: Informatics in Medicine Unlocked
  • Volume: 24
  • Article Number: 100624
  • ISSN: 2352-9148
  • Year: 2021
  • Cited by: 2

Significance of Software Engineering Phases in the Development of a Software Application: Case Study

  • Authors: S.A. Deshmukh, S.L. Kasar
  • Chapter in Book: Designing User Interfaces with a Data Science Approach, Pages 111-132
  • Publisher: IGI Global
  • Year: 2022
  • Cited by: 1

Student Performance Prediction Based on Multiple-Choice Question Test Using Neural Network in the VLab Platform

  • Authors: S.A. Deshmukh, R.S. Vaidya, V.D. Kamuni, S. Gaikwad
  • Journal: Theoretical Issues in Ergonomics Science
  • Volume: 25(3), Pages 330-342
  • Year: 2024

Analysis of Challenges in Decentralized Storage Framework for Sharing Medical Data

  • Authors: S.A. Deshmukh, S.L. Kasar, Y. Chichani
  • Conference: 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
  • Year: 2023

Virtual Lab Simulator for Software Engineering Experiment Report to Evaluate Student Assessment

  • Authors: S.A. Deshmukh, G. Tripathi
  • Conference: International Conference on Innovations in Computer Science and Engineering
  • Year: 2022

An Improvised on Mining Frequent Item Sets on Large Uncertain Databases

  • Author: M.S.A. Deshmukh
  • Journal: International Journal for Scientific Research & Development
  • Volume: 24(4), Pages 1769-1772
  • Year: 2017

Khondaker Mamun | Computer Interaction | Best Researcher Award

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Dr. Khondaker Mamun | Computer Interaction | Best Researcher Award

Professor at United International University, Bangladesh

Summary:

Dr. Khondaker Mamun is a distinguished academic and researcher with a prolific career in the fields of computer science and medical engineering. He completed his Postdoctoral research at the Institute of Biomaterials and Biomedical Engineering (IBBME) at the University of Toronto, Canada, in collaboration with the Holland Bloorview Kids Rehabilitation Hospital. Dr. Mamun earned his PhD in Computer Science and Medical Engineering from the University of Southampton, UK, focusing on pattern identification of movement-related states in biosignals. He also holds an MSc in Computer Science and Engineering from the Bangladesh University of Engineering and Technology (BUET), and a BSc in Computer Science and Engineering from Ahsanullah University of Science and Technology (AUST), where he graduated first in his class. Dr. Mamun’s research interests span across biomedical signal processing, machine learning, and assistive technology. He has a strong publication record and has been involved in various significant research projects. His contributions to academia and research have earned him recognition and accolades in his field. Currently, Dr. Mamun is dedicated to advancing the frontiers of biomedical engineering and improving healthcare outcomes through innovative technological solutions.

 

Profile:

Education:

Dr. Khondaker Mamun’s educational background is extensive and distinguished. He completed his Postdoctoral research at the Institute of Biomaterials and Biomedical Engineering (IBBME) at the University of Toronto, Ontario, Canada, in collaboration with the Holland Bloorview Kids Rehabilitation Hospital. He earned his PhD in Computer Science and Medical Engineering from the University of Southampton, UK, in 2012. His dissertation, “Pattern Identification of Movement Related States in Biosignals,” was supervised by Prof. Shouyan Wang, Director of the Biomedical Electronics Department at the Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, China. His PhD examiners were Prof. John Stein from the University of Oxford and Dr. David Simpson from the University of Southampton. Dr. Mamun also holds an MSc in Computer Science and Engineering from the Bangladesh University of Engineering and Technology (BUET), where he completed a dissertation on “Memory Efficient Data Structure for Static Huffman Tree” under Prof. Md. Mostofa Akbar in 2007. He began his academic journey with a BSc in Computer Science and Engineering from Ahsanullah University of Science and Technology (AUST) in Dhaka, Bangladesh, graduating first in his class in 2002. His undergraduate dissertation, “Architecture of Enterprise Resource Planning (ERP) for a Group of Companies,” was supervised by Dr. Tamjidul Hoque from the University of New Orleans, USA.

Professional Experience:

Dr. Khondaker Mamun has garnered extensive professional experience across academia and research institutions. He is currently serving as a Professor in the Department of Computer Science and Engineering at United International University, Dhaka, Bangladesh. Previously, he held a postdoctoral position at the Institute of Biomaterials and Biomedical Engineering (IBBME) at the University of Toronto, Canada, collaborating closely with the Holland Bloorview Kids Rehabilitation Hospital. During his tenure at the University of Toronto, Dr. Mamun worked on advanced biomedical engineering projects, focusing on assistive technology and biosignal processing. Before his postdoctoral work, Dr. Mamun completed his PhD at the University of Southampton, UK, where he specialized in the pattern identification of movement-related states in biosignals. His academic journey also includes significant teaching and research roles at various institutions. Throughout his career, Dr. Mamun has been involved in numerous research projects, contributing to the fields of biomedical signal processing, machine learning, and assistive technology. His work has led to several publications in high-impact journals and conferences, reflecting his commitment to advancing scientific knowledge and practical applications in healthcare technology.

Research Interests:

Dr. Khondaker Mamun’s research interests are diverse and multidisciplinary, focusing on the intersection of technology and healthcare. His primary areas of interest include biomedical signal processing, where he works on developing advanced algorithms for analyzing biosignals to improve patient care and diagnostic accuracy. He is also deeply engaged in assistive technology, aiming to create innovative solutions that enhance the quality of life for individuals with disabilities. Additionally, Dr. Mamun explores machine learning and artificial intelligence applications in healthcare, particularly in the development of intelligent systems for real-time health monitoring and decision support. His research contributions extend to neuroengineering, where he investigates the neural mechanisms underlying movement and the development of neuroprosthetics. Through his work, Dr. Mamun seeks to bridge the gap between cutting-edge technology and practical healthcare solutions, driving advancements in medical technology and improving patient outcomes.

Skills:

Dr. Khondaker Mamun possesses a diverse set of skills that showcase his extensive experience and multidisciplinary expertise. He is proficient in biomedical signal processing, enabling him to analyze and interpret complex biomedical signals for improved diagnostic and therapeutic outcomes. His skills in machine learning and artificial intelligence are applied to healthcare applications, including real-time health monitoring and predictive analytics. Dr. Mamun excels in assistive technology development, designing innovative devices and systems to enhance the quality of life for individuals with disabilities. His expertise in neuroengineering involves exploring neural mechanisms and developing neuroprosthetics and brain-computer interface technologies. Additionally, he has strong capabilities in data analysis and statistical modeling, essential for processing and interpreting large datasets in medical research. Dr. Mamun is also proficient in software development, utilizing various programming languages and tools in biomedical research and healthcare technology. His project management skills ensure effective oversight of interdisciplinary research projects from conception to execution. He is excellent at collaboration and teamwork, working with healthcare professionals, engineers, and researchers to achieve common goals. Dr. Mamun is experienced in academic writing and publishing, authoring research papers and articles for prestigious journals and conferences. Furthermore, he is committed to teaching and mentoring, fostering the next generation of innovators in biomedical engineering and healthcare technology.

Conclution:

Dr. Khondaker Mamun’s exceptional academic background, extensive research experience, significant contributions to digital health and biomedical engineering, and active engagement in both academic and professional communities make him an outstanding candidate for the Best Researcher Award. His work in establishing AIMS Lab and CMED Health highlights his commitment to innovation and practical applications of research, further cementing his suitability for this prestigious recognition.

Publication Tob Noted:

Progress in Brain Computer Interface: Challenges and Opportunities

  • Authors: S. Saha, K.A. Mamun, K. Ahmed, R. Mostafa, G.R. Naik, S. Darvishi, …
  • Journal: Frontiers in Systems Neuroscience
  • Year: 2021
  • Volume: 15
  • Article ID: 578875
  • Citations: 284

Technological Advancements and Opportunities in Neuromarketing: A Systematic Review

  • Authors: F.S. Rawnaque, K.M. Rahman, S.F. Anwar, R. Vaidyanathan, T. Chau, …
  • Journal: Brain Informatics
  • Year: 2020
  • Volume: 7
  • Pages: 1-19
  • Citations: 138

Cloud-Based Framework for Parkinson’s Disease Diagnosis and Monitoring System for Remote Healthcare Applications

  • Authors: K.A. Al Mamun, M. Alhussein, K. Sailunaz, M.S. Islam
  • Journal: Future Generation Computer Systems
  • Year: 2017
  • Volume: 66
  • Pages: 36-47
  • Citations: 81

A Critical Review on World University Ranking in Terms of Top Four Ranking Systems

  • Authors: F. Anowar, M.A. Helal, S. Afroj, S. Sultana, F. Sarker, K.A. Mamun
  • Book: New Trends in Networking, Computing, E-learning, Systems Sciences, and …
  • Year: 2015
  • Citations: 61

Telemonitoring Parkinson’s Disease Using Machine Learning by Combining Tremor and Voice Analysis

  • Authors: M.S.R. Sajal, M.T. Ehsan, R. Vaidyanathan, S. Wang, T. Aziz, K.A.A. Mamun
  • Journal: Brain Informatics
  • Year: 2020
  • Volume: 7
  • Issue: 1
  • Article ID: 12
  • Citations: 56

Exploration of EEG-based Depression Biomarkers Identification Techniques and Their Applications: A Systematic Review

  • Authors: A. Dev, N. Roy, M.K. Islam, C. Biswas, H.U. Ahmed, M.A. Amin, F. Sarker, …
  • Journal: IEEE Access
  • Year: 2022
  • Volume: 10
  • Pages: 16756-16781
  • Citations: 44