Nunzio Alberto Borghese | Computer Science | Best Researcher Award

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Prof. Nunzio Alberto Borghese | Computer Science | Best Researcher Award

Full professor at Università degli Studi di MIlano, Italy

Professor N. Alberto Borghese is a renowned researcher in computational intelligence and its application to real-world problems. He graduated magna cum laude in Electrical Engineering from Politecnico di Milan and has held significant academic positions, including Full Professor at the University of Milan. His research focuses on innovative methods such as multi-scale hierarchical neural networks, adaptive clustering, and statistical data processing, with particular emphasis on limited processing time. He has made notable contributions to e-Health and robotics, integrating AI, service robots, virtual communities, and smart objects to improve healthcare and welfare systems. With over 90 journal papers, 140+ conference papers, and 16 international patents, he has a strong academic and industrial impact. He has led several high-profile projects funded by the European Commission and Italian government, including REWIRE, MOVECARE, and AIRCA. His work continues to advance the intersection of AI, robotics, and healthcare, addressing critical societal needs.

Professional Profile 

Education

Professor N. Alberto Borghese received his education in Electrical Engineering, graduating magna cum laude in 1986 from Politecnico di Milan, one of Italy’s leading institutions. This strong academic foundation laid the groundwork for his extensive research career. His academic journey furthered through his role as a tenured researcher at the National Research Council (CNR) from 1987 to 2000, where he began developing his expertise in computational intelligence. This led to his appointment as an Associate and later Full Professor at the Department of Computer Science, University of Milan (UNIMI). At UNIMI, he also directs the Laboratory of Applied Intelligent Systems, where he has mentored students and led cutting-edge research projects. Professor Borghese’s education and professional development have been marked by continuous innovation, research leadership, and a commitment to applying his knowledge to real-world challenges, particularly in e-Health, robotics, and AI.

Professional Experience

Professor N. Alberto Borghese has had a distinguished professional career, beginning as a tenured researcher at the National Research Council (CNR) from 1987 to 2000. During this time, he built a strong foundation in computational intelligence. He then transitioned to the University of Milan (UNIMI), where he became an Associate Professor and later a Full Professor in the Department of Computer Science. At UNIMI, he also directs the Laboratory of Applied Intelligent Systems, where he leads innovative research projects focused on AI, robotics, and e-Health. Throughout his career, he has contributed to over 90 journal papers, more than 140 conference papers, and holds 16 international patents. Professor Borghese has led several major research projects funded by the European Commission, including REWIRE, MOVECARE, and FITREHAB, and has been involved in multiple Italian government-funded initiatives. His work bridges academia and industry, addressing pressing societal needs in healthcare and welfare through technological advancements.

Research Interest

Professor N. Alberto Borghese’s research interests lie primarily in the field of computational intelligence, focusing on the development and application of advanced algorithms to solve real-world problems. He specializes in multi-scale hierarchical neural networks, adaptive clustering, and statistical data processing, with an emphasis on optimizing solutions for limited processing time. His work extends to the integration of Artificial Intelligence (AI) and robotics, particularly in the domains of e-Health and e-Welfare. Professor Borghese has pioneered the use of service robots, virtual communities, and smart objects, creating innovative platforms that enhance healthcare and welfare systems. His research also explores the intersection of AI with healthcare technologies such as exer-games, aiming to improve accessibility and promote well-being. Additionally, he has a strong focus on interdisciplinary collaboration, leading several European and Italian research projects that combine AI, robotics, and human-centered design to address societal challenges in health, aging, and rehabilitation.

Award and Honor

Professor N. Alberto Borghese has received numerous awards and honors throughout his distinguished academic and research career. His recognition stems from his innovative contributions to computational intelligence, AI, and robotics, particularly in the fields of e-Health and e-Welfare. With over 90 journal papers and 140+ conference papers, his research has garnered widespread acclaim, reflected in his h-index of 42. He has also been honored for his extensive intellectual property contributions, holding 16 international patents. His leadership in research has been recognized through his involvement in high-profile projects funded by the European Commission and Italian government, such as REWIRE (FP7), MOVECARE (H2020), and AIRCA (2023-2025). These honors not only underline his academic excellence but also highlight his impact on advancing technology in healthcare and welfare systems. His continued success in securing major funding and his role in shaping interdisciplinary research make him a highly respected figure in his field.

Conclusion

Based on his exceptional academic qualifications, pioneering research in computational intelligence and e-Health, leadership in high-profile projects, and impressive publication and patent record, N. Alberto Borghese is a highly suitable candidate for the Best Researcher Award. Addressing minor improvements in public engagement and cross-disciplinary impact could further strengthen his candidacy. Nonetheless, his proven expertise and contributions make him a deserving nominee.

Publications Top Noted

  • Kinematic determinants of human locomotion
    • Authors: N. Alberto Borghese, L. Bianchi, F. Lacquaniti
    • Year: 1996
    • Citations: 553
  • Different brain correlates for watching real and virtual hand actions
    • Authors: D. Perani, F. Fazio, N. A. Borghese, M. Tettamanti, S. Ferrari, J. Decety, …
    • Year: 2001
    • Citations: 402
  • Autocalibration of MEMS accelerometers
    • Authors: I. Frosio, F. Pedersini, N. A. Borghese
    • Year: 2008
    • Citations: 261
  • Time-varying mechanical behavior of multijointed arm in man
    • Authors: F. Lacquaniti, M. Carrozzo, N. A. Borghese
    • Year: 1993
    • Citations: 202
  • Internal models of limb geometry in the control of hand compliance
    • Authors: F. Lacquaniti, N. A. Borghese, M. Carrozzo
    • Year: 1992
    • Citations: 197
  • Reading the reading brain: a new meta-analysis of functional imaging data on reading
    • Authors: I. Cattinelli, N. A. Borghese, M. Gallucci, E. Paulesu
    • Year: 2013
    • Citations: 188
  • A functional-anatomical model for lipreading
    • Authors: E. Paulesu, D. Perani, V. Blasi, G. Silani, N. A. Borghese, U. De Giovanni, …
    • Year: 2003
    • Citations: 163
  • The role of vision in tuning anticipatory motor responses of the limbs
    • Authors: F. Lacquaniti
    • Year: 1993
    • Citations: 151
  • Exergaming and rehabilitation: A methodology for the design of effective and safe therapeutic exergames
    • Authors: M. Pirovano, E. Surer, R. Mainetti, P. L. Lanzi, N. A. Borghese
    • Year: 2016
    • Citations: 148
  • Self-adaptive games for rehabilitation at home
    • Authors: M. Pirovano, R. Mainetti, G. Baud-Bovy, P. L. Lanzi, N. A. Borghese
    • Year: 2012
    • Citations: 146
  • Transient reversal of the stretch reflex in human arm muscles
    • Authors: F. Lacquaniti, N. A. Borghese, M. Carrozzo
    • Year: 1991
    • Citations: 144
  • Computational intelligence and game design for effective at-home stroke rehabilitation
    • Authors: N. A. Borghese, M. Pirovano, P. L. Lanzi, S. Wüest, E. D. de Bruin
    • Year: 2013
    • Citations: 139
  • Automatic detection of powdery mildew on grapevine leaves by image analysis: Optimal view-angle range to increase the sensitivity
    • Authors: R. Oberti, M. Marchi, P. Tirelli, A. Calcante, M. Iriti, A. N. Borghese
    • Year: 2014
    • Citations: 128
  • Usability and effects of an exergame-based balance training program
    • Authors: S. Wüest, N. A. Borghese, M. Pirovano, R. Mainetti, R. van de Langenberg, …
    • Year: 2014
    • Citations: 121
  • Pattern recognition in 3D automatic human motion analysis
    • Authors: G. Ferrigno, N. A. Borghese, A. Pedotti
    • Year: 1990
    • Citations: 121

Deepa Mulimani | Computer Science | Best Researcher Award

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Mrs. Deepa Mulimani | Computer Science | Best Researcher Award

Assistant Professor of KLE Technological University, Hubballi, India

Deepa Mulimani is a dedicated and highly experienced Assistant Professor in Computer Science and Applications with over 19 years of expertise 🌟. Renowned for her higher cognitive training methodologies, exceptional communication skills, and technical documentation prowess, she has consistently provided stellar support to both professors and students 🎓. Proficient in data management, machine learning, big data analytics, and programming languages such as Python, Java, C, C++, and C#, Deepa’s versatile skill set is complemented by her impressive academic and administrative capabilities 📊. Her commitment to lifelong learning is evident through her numerous Coursera certifications, including scalable machine learning and deep learning 🧠. Deepa’s innovative teaching methods, curriculum development, and student research guidance at KLE Technological University have significantly impacted her students’ academic progress 🌱. Her robust publication record, featuring research on concept drift adaptation, deep learning, and streaming data mining, showcases her active contribution to the scientific community 📚.

Professional profile

Education📚

Deepa holds a Master of Science in Computer Science from Karnatak University, Dharwad, where she was the University Rank II, and a Bachelor of Computer Applications from Karnatak Science College, Dharwad, also with University Rank II. Her academic achievements underscore her strong foundational knowledge and academic excellence.

Professional Experience🏛️

As an Assistant Professor at KLE Technological University, Hubli, Karnataka, since 2008, Deepa has applied innovative teaching methods, revised curricula, and designed courses for MCA students. She has also created blended learning materials and collaborated with industry leaders for student training in robotic process automation (RPA). Her previous role as a lecturer at KLES’s College of Business Administration involved educating BBA students and coordinating cultural activities.

Research🏆

Currently, Deepa is pursuing research in Big Data Analytics with a focus on streaming data mining. Her ongoing research endeavors align well with contemporary challenges in data science and analytics, demonstrating her commitment to advancing knowledge in this field.

Publications top noted📜
  • Impact analysis of real and virtual concept drifts on the predictive performance of classifiers 🧠
    • Authors: Benni, R., Totad, S., Mulimani, D., Kg, K.
    • Year: 2024
    • Citations: 0
  • Online Detection and Adaptation of Concept Drift in Streaming Data Classification 🔄
    • Authors: Mulimani, D., Patil, P., Totad, S., Benni, R.
    • Year: 2024
    • Citations: 0
  • Heuristic Approach for Detecting and Neutralizing Black Hole Attacks in Wireless Sensor Networks 🌐
    • Authors: Benni, R., Kittur, M.M., Patil, P., Mulimani, D.
    • Year: 2023
    • Citations: 0
  • Adaptive Classifier to Address Concept Drift in Imbalanced Data Streams ⚖️
    • Authors: Mulimani, D., Patil, P.R., Totad, S.G.
    • Year: 2023
    • Citations: 0
  • Weighted Averaging Ensemble Model for Concept Drift Adaptation in Streaming Data ⚙️
    • Authors: Mulimani, D., Kanakaraddi, S.G., Totad, S.G., Patil, P.R.
    • Year: 2022
    • Citations: 3
  • Experiential Learning Enhancing User Interface Design Skills through Cognitive Action 💡
    • Authors: Mulimani, D., Seeri, S.V., Patil, P., Kulkarni, S.
    • Year: 2017
    • Citations: 0

Rithish S V | Computer Science | Best Researcher Award

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Mr. Rithish S V | Computer Science | Best Researcher Award

Student of Amrita University, India

Rithish S V is a passionate Computer Science student at Amrita Viswa Vidyapeetham specializing in Cloud Computing and Machine Learning 🌐📊. With a strong foundation in Microservices Architecture and cloud-native application design and deployment ☁️💻, he is actively enhancing his skills in Salesforce development 🚀. Rithish’s projects, such as developing a cloud monitoring app on Kubernetes and an emergency assistance app called “Emergify” 🚨📱, showcase his innovative approach and technical prowess. Fluent in multiple programming languages and proficient in various cloud and DevOps tools, Rithish exemplifies a blend of technical expertise and effective communication skills 🌟🗣️. His awards and certifications further validate his dedication and excellence in the field of computer science 🏆🎖️.

Professional profile

Education📚

Rithish has consistently excelled academically, currently pursuing a B.Tech in Computer Science and Engineering at Amrita Viswa Vidyapeetham with a GPA of 8.2. He completed his higher secondary education at Sri Lathangi Vidya Mandir with an impressive percentage of 91.6 and his secondary school education with a percentage of 93.6.

Professional Experience🏛️

Rithish S V is a dedicated Computer Science student with a strong focus on Cloud Computing and Machine Learning, demonstrating a profound understanding of Microservices Architecture and cloud-native application design and deployment. He is actively honing his skills in Salesforce development and showcases proficiency in problem-solving, communication, and team management, ensuring efficient project execution.

Skills🏆

Rithish is proficient in multiple programming languages, including Python, C++, and Java, and possesses expertise in cloud and DevOps tools such as AWS, Google Cloud Platform, Kubernetes, and Docker. He also has knowledge in networking, blockchain (solidity), and various development languages like SQL, JS, HTML, React.js, and CSS. His soft skills include team management, analytical thinking, problem-solving, and effective communication.

Publications top noted📜
  • Title: Echoes of Truth: Unraveling Homophily in Attributed Networks for Rumor DetectionAuthors: Rithish S.V., Prabu C.R., Anuush M.B., Deepthi L.R.

    Journal: Procedia Computer Science, 2024, Volume 233, Pages 184–193

    Abstract: The paper “Echoes of Truth: Unraveling Homophily in Attributed Networks for Rumor Detection” presents innovative research on identifying and mitigating the spread of rumors in social networks. By leveraging homophily—the tendency of individuals to associate and bond with similar others—the authors developed algorithms that effectively detect rumor sources within attributed networks. This study provides significant insights into network dynamics and offers practical solutions for improving information reliability in digital communication platforms.

Kalpa Subbaiah | Computer Science | Women Researcher Award

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Mrs. Kalpa Subbaiah | Computer Science | Women Researcher Award

VP-Lead Data Scientist of JP Morgan Chase, India

👩‍💼 Mrs. Kalpa Subbaiah is a seasoned Data Scientist with 16 years of experience, including 8 in Data Science. She holds advanced degrees in Machine Learning and AI. Certified in AWS, Azure, and Microsoft technologies, Kalpa excels in Azure Databricks, Machine Learning, and AI Cognitive Services. She is proficient in processing streaming and batch data and building cloud deployment pipelines. A published researcher in sentiment analysis, she is recognized for her strong analytical and project management skills.

Professional profile

Education📚

🎓 Mrs. Kalpa Subbaiah holds a Master of Science in Machine Learning and Artificial Intelligence from Liverpool John Moores University, UK. She also earned a Post-Graduation Diploma in Machine Learning and AI from the International Institute of Information Technology, Bangalore, and a Post-Graduation Certificate in Big Data Analytics & Optimization from Insofe (International School of Engineering). Additionally, Kalpa has a Bachelor’s degree in Computer Science and Engineering from Vishweshwaraiah Technological University, completed in 2006. 📚

Professional Experience🏛️

👩‍💼 Mrs. Kalpa Subbaiah boasts a robust professional journey with 16 years of experience, including 8 in Data Science. She has held roles at HP 🖥️, Bosch 🛠️, Insofe 🏫, Microsoft 💼, and JP Morgan Chase 🏦. As a Microsoft Open Hack Coach and Lead, she specializes in serverless, AI knowledge mining, and Modern Data Warehouse. Her expertise spans Azure Databricks, Azure Machine Learning, and AI Cognitive Services, where she excels in processing streaming and batch data, building models, and creating cloud deployment pipelines.

Research Interest🌐

🔍 Mrs. Kalpa Subbaiah is deeply interested in advancing the fields of Machine Learning, Deep Learning, and AI. Her research focuses on Natural Language Processing (NLP) 🤖, Computer Vision 🖼️, and GenAI technologies like lang chain, transformers, and OpenAI. She has a keen interest in Aspect-Based Sentiment Analysis, particularly using Weakly Supervised Learning. Kalpa is also passionate about developing end-to-end machine learning pipelines, integrating Big Data components, and leveraging frameworks such as TensorFlow, sklearn, and NLTK to solve complex data science problems. 📊📈

Awards and Honors🏆

🏆 Mrs. Kalpa Subbaiah has received numerous awards and honors throughout her career. She has been recognized for her exceptional contributions to Data Science and AI, including publishing a research paper on Aspect-Based Sentiment Analysis using Weakly Supervised Learning. As a certified professional in AWS Machine Learning Specialty, Microsoft Azure Data Scientist, Azure AI Engineer Associate, and more, she has consistently demonstrated her expertise and leadership. Additionally, she has earned accolades for her roles as a Microsoft Open Hack Coach and Lead in serverless, AI knowledge mining, and Modern Data Warehouse.

Achievements🏅
  • 📜 Published a research paper on Aspect-Based Sentiment Analysis using Weakly Supervised Learning.
  • 👩‍💻 Successfully led and completed large, complex data science projects across various industries.
  • 💼 Served as a Microsoft Open Hack Coach and Lead for serverless, AI knowledge mining, and Modern Data Warehouse.
  • 📊 Developed end-to-end machine learning pipelines and integrated Big Data components like Azure Event Hubs, Synapse, Stream Analytics, Spark Structured Streaming, Hadoop, Kafka, and Spark.
  • 🎓 Certified in multiple prestigious certifications, including AWS Machine Learning Specialty and Microsoft Azure Data Scientist.
  • 🤖 Expert in leveraging advanced machine learning frameworks such as TensorFlow, sklearn, OpenCV, and NLTK.
  • 🧠 Recognized for strong analytical and team player skills, consistently delivering impactful data science solutions.
  • 🌟 Created and shared knowledge through blogs on Medium and machine learning videos on the Microsoft community channel.
Certificates🛠️
  • 🏆 AWS Certified: Machine Learning Specialty
  • 🎓 Microsoft Certified: Azure Data Scientist
  • 💼 Microsoft Certified: Azure AI Engineer Associate
  • 🚀 Microsoft: Open Hack Serverless Tech Lead
  • 📊 Microsoft Certified: Data Engineer Associate
  • 🏫 Post-Graduation Certificate in “Big Data Analytics & Optimization” from Insofe (International School of Engineering)
  • 🤖 Microsoft Certified: Azure AI Fundamentals
  • 📈 Microsoft Certified: Azure Data Fundamentals
Publications top noted📜
  • Author: Kalpa Subbaiah, Bolla B.K.
  • Title: Aspect Category Learning and Sentimental Analysis Using Weakly Supervised Learning
  • Journal: Procedia Computer Science
  • Year: 2024
  • Volume: 235
  • Pages: 1246–1257
  • Citations: 0 📉

Sayyed Ahmed | Computer Science | Best Scholar Award

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Mr. Sayyed Ahmed | Computer Science | Best Scholar Award

Assistant Professor of  Aligarh Muslim University, India

Dr. Sayyed Usman Ahmed is a dedicated academic and researcher in the field of computer engineering, specializing in artificial intelligence and legal reasoning. He has been recognized for his contributions with awards such as the Best Paper Award (2022-23) and the Visvesvaraya Part-Time PhD Fellowship (2018-19). His teaching and research continue to inspire and shape the next generation of engineers and technologists.

Publication profile

Education

Dr. Sayyed Usman Ahmed holds a Ph.D. in Computer Engineering from Aligarh Muslim University (AMU), India, where he conducted research on “Decision Intelligence in Augmentation of Legal Reasoning” under the supervision of Prof. Nesar Ahmad. His thesis was submitted on March 6, 2024. He earned his M.Tech in Computer Engineering from Rajasthan Technical University (2012-2014) with a thesis on evaluating the efficiency and effectiveness of code reading techniques, supervised by Dr. Rajendra Purohit. He completed his B.Tech in Computer Engineering from AMU (2003-2007), with a project on fingerprint detection systems under the guidance of Prof. M. Sarosh Umar and Prof. Syed Atiqur Rahman.

Experience

Dr. Ahmed has extensive experience in academia and industry. He is currently an Assistant Professor at AMU, teaching courses in software engineering, data structures, information security, and programming labs. He has also served as a Deputy Head of the Information Technology department at Jodhpur Institute of Engineering and Technology, where he contributed significantly to teaching, course development, and departmental administration. In the industry, he has worked as an Application Software Engineer at Computer Science Corporation, focusing on software maintenance, bug fixes, and enhancements. Additionally, he has served in various capacities at the Computer Centre of AMU, including roles as a Programmer and Technical Consultant.

Research focus

Dr. Ahmed’s research interests encompass artificial intelligence, machine learning, natural language processing, and decision intelligence. He has published extensively in journals and conferences, focusing on areas such as sentiment analysis, depression detection from social media posts, rumor-free social networks, and news article summarization. His recent research includes a framework for legal case brief generation using natural language processing and smart contract generation through NLP and blockchain.

Publication top notes

1. Ahmad, T., Ahamad, M., Ahmed, S. U., Ahmad, N. (2022) Short question-answers
assessment using lexical and semantic similarity based features, Journal of Discrete
Mathematical Sciences and Cryptography, 25:7, 2057-2067, DOI:
10.1080/09720529.2022.2133245 [ESCI & Scopus]

2. Ahmed, S. U., Ahmad, T., Ahmad, N. (2022). Sentiment Analysis Techniques for
Depression Detection from Micro-Blogging Social Media Post. NueroQuantology
DOI: 10.14704/NQ.2022.20.12.NQ77265 [Scopus]

3. Ahmad, T., Ahmed, S. U., Ali, S. O., & Khan, R. (2020). Beginning with exploring the
way for rumor free social networks. Journal of Statistics and Management Systems, 23(2),
231-238. https://doi.org/10.1080/09720510.2020.1724623 [Web of Science]

4. Ahmad, T., Ahmed, S. U., Ahmad, N., Aziz, A., Mukul, L. (2020). News Article
Summarization: Analysis and Experiments on Basic Extractive Algorithms. International
Journal of Grid and Distributed Computing, 13(2), 2366 – 2379. [Web of Science]

5. Ahmed, S. U. (2018). Monitoring Unscheduled Leaves using IVR. Global Journal of
Computer Science and Technology, 18(1), 7–9. [Peer-reviewed]

6. Ahmed, S. U., & Purohit, R. (2014). Evaluating Efficiency and Effectiveness of Code
Reading Technique with an Emphasis on Enhancing Software Quality. International
Journal of Computer Applications, 2, 32-36. [Peer-reviewed]

7. Ahmed, S. U., Azmi, M. A., Badgujar, C., (2014). How to design and test safety critical
software systems. International Journal of Advances in Computer Science and Technology,
3(1), 19-22. [Peer-reviewed]

8. Ahmed, S. U., Sahare, S. A., & Ahmed, A. (2013). Automatic test case generation using
collaboration UML diagrams. World Journal of Science and Technology. 2, [Peerreviewed]

9. Ahmed, S. U., & Azmi, M. A. (2013). A Novel Model Based Testing (MBT) approach for
Automatic Test Case Generation. International Journal of Advanced Research in
Computer Science, 4(11), 81-83. [Peer-reviewed]

Journal Publications (Under Review)
1. Ahmed, S. U., Ahmed, N., Ahmad, T. (2023) A Rhetorical Role Relatedness (RRR)
framework for Legal Case Brief Generation Natural Language Processing Journal
(Elsevier, Submitted)

Anup Burange | Computer Science | Best Researcher Award

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Dr. Anup Burange | Computer Science | Best Researcher Award

Assistant Professor of Prof. Ram Meghe Institute of Technology & Research, Badnera, India

Dr. Anup W. Burange is an esteemed academic based in Amravati, Maharashtra, India. He serves as an Assistant Professor in the IT department at Prof Ram Meghe Institute of Technology & Research 👩‍🏫. With a Ph.D. in Computer Science & Engineering from SGB Amravati University 🎓, he excels in teaching core IT subjects and has published around 20 articles 📚. As a departmental Training & Placement coordinator, he has engaged over 50 companies for campus placements 🎓. Dr. Burange’s dedication is reflected in consistently high student evaluations 📈 and his extensive technical expertise 🤖📊.

Professional profile
Education📚

Dr. Anup W. Burange has an impressive educational background in the field of Information Technology. He earned his Ph.D. in Computer Science & Engineering from SGB Amravati University in February 2024 🎓. Prior to that, he completed his Master of Engineering in Information Technology at Prof. Ram Meghe Institute of Technology & Research, Amravati, Maharashtra, in June 2014, achieving an aggregate pointer of 8.38 🎓. He also holds a Bachelor of Engineering degree in Information Technology from Sipna’s College of Engineering & Technology, Amravati University, Maharashtra, which he completed in June 2011 with an aggregate of 69.14% 🎓. Dr. Burange’s academic journey began with his Higher Secondary Certificate (HSC) from the Maharashtra State Board, where he scored 73% 📜, followed by his Secondary School Certificate (SSC) from the same board, with a score of 76.66% 📜

Professional Experience🏛️

Dr. Anup W. Burange has extensive professional experience as an Assistant Professor in the IT department at Prof Ram Meghe Institute of Technology & Research in Badnera-Amravati, Maharashtra, India, a position he has held since November 2011 👩‍🏫. He teaches core IT subjects such as Computer Architecture & Organization, Operating Systems, and various programming languages (C, C++, Java, Python) 📚. As the departmental Training & Placement coordinator since 2014, Dr. Burange has successfully engaged over 50 companies for campus placements 🎓. He consistently receives high student evaluations, with scores exceeding 85% over the past four years 📈. Additionally, he has published about 20 articles in reputed journals and guided more than 50 students in their final year projects 👨‍💻. He also served as a masking officer for end semester examinations 📝.

Research Interest🌐

Dr. Anup W. Burange’s research interests lie in the realms of Information Technology and Computer Science, with a strong focus on emerging technologies. He is deeply engaged in exploring advancements in Artificial Intelligence 🤖, Machine Learning 📈, and Data Science 📊. His work also delves into the development and optimization of programming languages like C, C++, Java, and Python 🐍. Dr. Burange is passionate about enhancing educational methodologies and integrating innovative technological solutions in IT education 🎓. His commitment to research is reflected in his numerous publications and contributions to reputable journals 📚.

Awards and Honors🏆

Dr. Anup W. Burange has been recognized for his exemplary contributions to academia and research with several awards and honors 🏆. He has consistently achieved student evaluations exceeding 85% over the past four years, highlighting his dedication to teaching excellence 📈. As a testament to his research prowess, Dr. Burange has published approximately 20 articles in well-reputed journals 📚. His efforts in facilitating campus placements have also been commendable, successfully engaging over 50 companies for Prof Ram Meghe Institute of Technology & Research 🎓. Dr. Burange’s accolades reflect his commitment to advancing the field of Information Technology and education.

Research skill🔬

Dr. Anup W. Burange possesses a robust set of research skills in the field of Information Technology and Computer Science. He is proficient in Artificial Intelligence 🤖 and Machine Learning 📈, with a keen ability to apply these technologies to real-world problems. Dr. Burange excels in programming languages such as C, C++, Java, and Python 🐍, leveraging these skills for data analysis and algorithm development. His expertise extends to Data Science 📊, where he employs statistical methods and data visualization techniques. Dr. Burange is also adept at academic writing and publishing, with around 20 articles in reputed journals 📚, showcasing his ability to conduct and disseminate impactful research.

Achievements🏅
  • 🏆 High Student Evaluation Scores: Consistently received student evaluations exceeding 85% over the past four years 📈.
  • 🎓 Successful Campus Placements: Engaged over 50 companies for campus placements at Prof Ram Meghe Institute of Technology & Research.
  • 📚 Research Publications: Published around 20 articles in well-reputed journals, contributing significantly to the field of Information Technology.
  • 👨‍💻 Guided Final Year Projects: Supervised more than 50 student final year projects, focusing on innovative IT solutions and technologies.
  • 📝 Academic Leadership: Served as a masking officer for end semester examinations, demonstrating leadership and organizational skills.
Projects🛠️
  • 🧑‍💻 Student Final Year Projects: Guided over 50 student projects on topics such as Artificial Intelligence 🤖, Machine Learning 📈, and Data Science 📊.
  • 💻 Programming Solutions Development: Worked on projects involving optimization and development using programming languages like C, C++, Java, and Python 🐍.
  • 📊 Data Visualization Tools: Developed tools for effective data visualization and analysis.
  • 🕵️‍♂️ Real-Time Detection Systems: Contributed to projects involving real-time detection and monitoring systems.
  • 📚 Educational Methodologies: Implemented innovative approaches to enhance IT education and practical learning experiences.
Publications📜
  • Article
    Title: Safeguarding the Internet of Things: Elevating IoT routing security through trust management excellence
    Authors: Burange, A.W., Deshmukh, V.M., Thakare, Y.A., Shelke, N.A.
    Journal: Computer Standards and Interfaces
    Year: 2025
    Citations: 0 🔍
  • Book Chapter
    Title: Different Security Breaches in Patients’ Data and Prevailing Ways to Counter Them
    Authors: Burange, A.W., Deshmukh, V.M.
    Book: Machine Learning in Healthcare and Security: Advances, Obstacles, and Solutions
    Year: 2024
    Pages: 149–159
    Citations: 0 🔍
  • Article
    Title: Securing IoT Attacks: A Machine Learning Approach for Developing Lightweight Trust-Based Intrusion Detection System
    Authors: Burange, A.W., Deshmukh, V.M.
    Journal: International Journal on Recent and Innovation Trends in Computing and Communication
    Year: 2023
    Volume: 11(7), pp. 14–22
    Citations: 0 🔍
  • Article
    Title: Trust based secured Routing system for low powered networks
    Authors: Burange, A.W., Deshmukh, V.M.
    Journal: Journal of Integrated Science and Technology
    Year: 2023
    Volume: 11(1), 431
    Citations: 2 🔍
  • Conference Paper
    Title: Detection of Rank, Sybil and Wormhole Attacks on RPL Based Network Using Trust Mechanism
    Authors: Burange, A.W., Deshmukh, V.M.
    Conference: CEUR Workshop Proceedings
    Year: 2021
    Volume: 3283, pp. 152–162
    Citations: 1 🔍
  • Conference Paper
    Title: Secured Routing System for Low Energy Networks
    Authors: Burange, A.W., Deshmukh, V.M.
    Conference: Lecture Notes in Networks and Systems
    Year: 2021
    Volume: 164, pp. 165–173
    Citations: 0 🔍
  • Conference Paper
    Title: Implementation of security algorithm and achieving energy efficiency for increasing lifetime of wireless sensor network
    Authors: Misalkar, H., Nikam, U., Burange, A.
    Conference: Communications in Computer and Information Science
    Year: 2019
    Volume: 839, pp. 298–307
    Citations: 0 🔍
  • Conference Paper
    Title: Security in MQTT and CoAP Protocols of IoT’s application layer
    Authors: Burange, A., Misalkar, H., Nikam, U.
    Conference: Communications in Computer and Information Science
    Year: 2019
    Volume: 839, pp. 273–285
    Citations: 2 🔍
  • Conference Paper
    Title: Increasing lifespan and achieving energy efficiency of wireless sensor network
    Authors: Misalkar, H.D., Burange, A.W., Nikam, U.V.
    Conference: 2016 International Conference on Information Communication and Embedded Systems (ICICES 2016)
    Year: 2016
    Citations: 3 🔍
  • Conference Paper
    Title: Review of Internet of Things in development of smart cities with data management & privacy
    Authors: Burange, A.W., Misalkar, H.D.
    Conference: 2015 International Conference on Advances in Computer Engineering and Applications (ICACEA 2015)
    Year: 2015
    Pages: 189–195
    Citations: 48 🔍