Ritika Ladha | Computer Science | Best Researcher Award

Assist Prof Dr. Ritika Ladha | Computer Science | Best Researcher Award

Associate Professor of Adani University, India

Dr. Ritika Vivek Ladha is an esteemed academic and researcher currently serving as an Assistant Professor in the Department of Information and Communication Technology at Adani University. She completed her Ph.D. in Information and Communication Technology from Nirma University in 2022, following a Master’s in Information and Network Security and a Bachelor’s in Computer Science and Engineering.

Professional profile

EducationπŸ“š

Dr. Ritika Vivek Ladha earned her Ph.D. in Information and Communication Technology from Nirma University in 2022. She completed her M.Tech. in Information and Network Security at Nirma University in 2015, with a CGPA of 8.42. Her undergraduate studies were conducted at A.D Patel Institute of Technology, where she obtained a B.E. in Computer Science and Engineering in 2013, achieving a CPI of 8.14.

Professional ExperienceπŸ›οΈ

Dr. Ladha’s dedication to her field is further evidenced by her various professional recognitions and roles. She has received certifications in Cyber Security from IBM and is a member of the ACM. Her role as the Membership Chair for the Adani ACM-W Student Chapter and her involvement in conferences and professional organizations underscore her active engagement with the academic and research community.

Research Interest🌐

Dr. Ladha’s research interests span several cutting-edge areas, including deep learning, machine learning, recommender systems, network security, intrusion detection systems, and the Internet of Things (IoT). Her work has significantly contributed to advancing these fields, addressing key issues such as cybersecurity threats, feature selection, and machine learning-based intrusion detection.

Her contributions are well-documented through her publications in prestigious journals and conferences. Notable papers include reviews on phishing attack risk assessment and advancements in intrusion detection systems. Dr. Ladha’s work has garnered substantial recognition, with a Google Scholar citation count of 1,229, an h-index of 11, and an i10-index of 11, reflecting the impactful nature of her research.

Awards and HonorsπŸ†

Dr. Ladha has received notable recognitions such as ACM Professional Membership, certification in Cyber Security from IBM, and participation in significant conferences. These achievements highlight her commitment to staying at the forefront of her field and her active engagement with professional communities.

AchievementsπŸ…

Dr. Ladha’s achievements include earning a Certificate in Developing Enterprise Applications from NIIT in 2012 and becoming a Red Hat Certified System Administrator in 2018. In 2020, she was recognized for having articles in the 25 most downloaded papers of the Swarm and Evolutionary Journal. She is a member of ACM (2023) and has been endorsed by IBM with a Skill Build Course on Cyber Security Fundamentals and Artificial Intelligence in 2024. Additionally, she has been actively involved in academic and professional communities, including serving as the Membership Chair of the Adani ACM-W Student Chapter in 2023.

Publications top notedπŸ“œ
  • “A Review on Machine Learning and Deep Learning Perspectives of IDS for IoT: Recent Updates, Security Issues, and Challenges”
    Authors: A. Thakkar, R. Lohiya
    Journal: Archives of Computational Methods in Engineering
    Year: 2021
    Citations: πŸ“š 259
  • “A Review of the Advancement in Intrusion Detection Datasets”
    Authors: A. Thakkar, R. Lohiya
    Journal: Procedia Computer Science
    Year: 2020
    Citations: πŸ“š 228
  • “A Survey on Intrusion Detection System: Feature Selection, Model, Performance Measures, Application Perspective, Challenges, and Future Research Directions”
    Authors: A. Thakkar, R. Lohiya
    Journal: Artificial Intelligence Review
    Year: 2022
    Citations: πŸ“š 185
  • “Attack Classification Using Feature Selection Techniques: A Comparative Study”
    Authors: A. Thakkar, R. Lohiya
    Journal: Journal of Ambient Intelligence and Humanized Computing
    Year: 2021
    Citations: πŸ“š 128
  • “Fusion of Statistical Importance for Feature Selection in Deep Neural Network-Based Intrusion Detection System”
    Authors: A. Thakkar, R. Lohiya
    Journal: Information Fusion
    Year: 2023
    Citations: πŸ“š 114
  • “Application Domains, Evaluation Data Sets, and Research Challenges of IoT: A Systematic Review”
    Authors: R. Lohiya, A. Thakkar
    Journal: IEEE Internet of Things Journal
    Year: 2020
    Citations: πŸ“š 84
  • “Role of Swarm and Evolutionary Algorithms for Intrusion Detection System: A Survey”
    Authors: A. Thakkar, R. Lohiya
    Journal: Swarm and Evolutionary Computation
    Year: 2020
    Citations: πŸ“š 81
  • “Attack Classification of Imbalanced Intrusion Data for IoT Network Using Ensemble-Learning-Based Deep Neural Network”
    Authors: A. Thakkar, R. Lohiya
    Journal: IEEE Internet of Things Journal
    Year: 2023
    Citations: πŸ“š 54
  • “Intrusion Detection Using Deep Neural Network with Anti-Rectifier Layer”
    Authors: R. Lohiya, A. Thakkar
    Journal: Applied Soft Computing and Communication Networks: Proceedings of ACN 2020
    Year: 2021
    Citations: πŸ“š 36
  • “Analyzing Fusion of Regularization Techniques in the Deep Learning-Based Intrusion Detection System”
    Authors: A. Thakkar, R. Lohiya
    Journal: International Journal of Intelligent Systems
    Year: 2021
    Citations: πŸ“š 28
  • “Survey on Mobile Forensics”
    Authors: R. Lohiya, P. John, P. Shah
    Journal: International Journal of Computer Applications
    Year: 2015
    Citations: πŸ“š 28
  • “A Review on Challenges and Future Research Directions for Machine Learning-Based Intrusion Detection System”
    Authors: A. Thakkar, R. Lohiya
    Journal: Archives of Computational Methods in Engineering
    Year: 2023
    Citations: πŸ“š 10

Rahul Chaurasia | Computer Science | Best Researcher Award

Dr. Rahul Chaurasia | Computer Science | Best Researcher Award

Postdoc ResearcherΒ of IIT Indore , India

Rahul Chaurasia, Ph.D., is a distinguished post-doctoral researcher in the Department of Computer Science & Engineering at the Indian Institute of Technology Indore. With a Ph.D. in Computer Science & Engineering from IIT Indore, his research expertise lies in hardware security, hardware co-processor designs for machine learning applications, hardware acceleration, intellectual property protection (IPP), and computer architecture. His doctoral thesis, focused on IP core protection and detective control of data-intensive IPs against piracy, addresses crucial challenges in modern integrated circuit design, particularly safeguarding against IP piracy, fraudulent ownership claims, and reverse engineering.

Professional profile

EducationπŸ“š

Rahul Chaurasia holds a Ph.D. in Computer Science & Engineering from the Indian Institute of Technology Indore, which is renowned for its rigorous academic standards. His thesis, focused on IP core protection and control against data-intensive IP piracy, demonstrates his deep expertise in a crucial area of hardware security. Additionally, his strong academic performance, reflected in his CGPA during both his M.Tech. and B.E. studies, further underscores his solid educational foundation.

Professional ExperienceπŸ›οΈ

Chaurasia’s role as a Post-Doc Researcher with the Translational Research Fellowship at IIT Indore, combined with his experience as a teaching assistant, reflects his commitment to both research and education. His involvement in various conferences, as well as his service as a reviewer for prominent journals, indicates a high level of professional engagement and peer recognition.

Research Interest🌐

Chaurasia’s research in hardware security, particularly his development of solutions using biometrics and obfuscation, addresses significant challenges in intellectual property protection. His work on secure hardware designs for machine learning and multimedia applications has made noteworthy contributions to the field. The emphasis on practical and innovative solutions, such as hardware security approaches with minimal overhead, positions his research as highly relevant and impactful.

Awards and HonorsπŸ†

Chaurasia’s role as a Post-Doc Researcher with the Translational Research Fellowship at IIT Indore, combined with his experience as a teaching assistant, reflects his commitment to both research and education. His involvement in various conferences, as well as his service as a reviewer for prominent journals, indicates a high level of professional engagement and peer recognition.

AchievementsπŸ…

Rahul Chaurasia has made significant contributions to the field of hardware security, as evidenced by his multiple publications in high-impact journals such as IEEE Transactions on Consumer Electronics. His research has been recognized with several prestigious awards, including the Young Scientist Award in Computer Science Engineering and Information Technology from the M.P. Council of Science and Technology and the First Prize-Best Paper Award at the IEEE-iSES 2022 symposium. He has also been awarded the Translational Research Fellowship for his post-doctoral work at IIT Indore and has received fellowships from MHRD and AICTE during his Ph.D. and M.Tech. programs, respectively. His achievements reflect his dedication to advancing the field of computer science and his potential as a leading researcher in hardware security.

Publications top notedπŸ“œ
  • Contact-less Palmprint Biometric for Securing DSP Coprocessors used in CE systems
    πŸ‘¨β€πŸ”¬ Anirban Sengupta, Rahul Chaurasia, Tarun Reddy
    πŸ“° IEEE Transactions on Consumer Electronics 67 (3), 202-213
    πŸ“… 2021
    πŸ“‘ Citations: 15
  • Secured Convolutional Layer IP Core in Convolutional Neural Network Using Facial Biometric
    πŸ‘¨β€πŸ”¬ Anirban Sengupta, Rahul Chaurasia
    πŸ“° IEEE Transactions on Consumer Electronics 68 (3), 291-306
    πŸ“… 2022
    πŸ“‘ Citations: 11
  • Securing IP Cores for DSP Applications Using Structural Obfuscation and Chromosomal DNA Impression
    πŸ‘¨β€πŸ”¬ Anirban Sengupta, Rahul Chaurasia
    πŸ“° IEEE Access 10, 50903-50913
    πŸ“… 2022
    πŸ“‘ Citations: 9
  • Robust Security of Hardware Accelerators Using Protein Molecular Biometric Signature and Facial Biometric Encryption Key
    πŸ‘¨β€πŸ”¬ Anirban Sengupta, Rahul Chaurasia, Aditya Anshul
    πŸ“° IEEE Transactions on Very Large Scale Integration (VLSI) Systems
    πŸ“… 2023
    πŸ“‘ Citations: 6
  • Quadruple Phase Watermarking during High Level Synthesis for Securing Reusable Hardware Intellectual Property Cores
    πŸ‘¨β€πŸ”¬ Mahendra Rathor, Aditya Anshul, K Bharath, Rahul Chaurasia, Anirban Sengupta
    πŸ“° Computers and Electrical Engineering 105, 108476
    πŸ“… 2023
    πŸ“‘ Citations: 4
  • Exploring Handwritten Signature Image Features for Hardware Security
    πŸ‘¨β€πŸ”¬ Mahendra Rathor, Anirban Sengupta, Rahul Chaurasia, Aditya Anshul
    πŸ“° IEEE Transactions on Dependable and Secure Computing
    πŸ“… 2022
    πŸ“‘ Citations: 4
  • Palmprint Biometric Versus Encrypted Hash Based Digital Signature for Securing DSP Cores used in CE Systems
    πŸ‘¨β€πŸ”¬ R Chaurasia, A Anshul, A Sengupta, S Gupta
    πŸ“° IEEE Consumer Electronics Magazine 11 (5), 73-80
    πŸ“… 2022
    πŸ“‘ Citations: 4
  • Blockchain Based Pharmaceutical Supply Chain and its Challenges: A Review and Proposed Solution
    πŸ‘¨β€πŸ”¬ UK Sahu, A Jain, R Chaurasia, KK Hiran
    πŸ“° 2023 IEEE International Conference on ICT in Business Industry & Government
    πŸ“… 2023
    πŸ“‘ Citations: 3
  • Retinal Biometric for Securing JPEG Codec Hardware IP Core for CE Systems
    πŸ‘¨β€πŸ”¬ Rahul Chaurasia, Anirban Sengupta
    πŸ“° IEEE Transactions on Consumer Electronics
    πŸ“… 2023
    πŸ“‘ Citations: 3
  • Symmetrical Protection of Ownership Rights for IP Buyer and IP Vendor using Facial Biometric Pairing
    πŸ‘¨β€πŸ”¬ Rahul Chaurasia, Anirban Sengupta
    πŸ“° 2022 IEEE International Symposium on Smart Electronic Systems (iSES), 272-277
    πŸ“… 2022
    πŸ“‘ Citations: 3
  • Security Vs Design Cost of Signature Driven Security Methodologies for Reusable Hardware IP Core
    πŸ‘¨β€πŸ”¬ Rahul Chaurasia, Anirban Sengupta
    πŸ“° 2022 IEEE International Symposium on Smart Electronic Systems (iSES), 283-288
    πŸ“… 2022
    πŸ“‘ Citations: 1

Taher Al-Shehari | Computer Science | Best Researcher Award

Dr. Taher Al-Shehari | Computer Science | Best Researcher Award

Senior Lecturer and Researcher of King Saud University, Saudi Arabia

Taher Ali Al-Shehari is a dedicated cybersecurity professional and educator with a robust background in computer science. Holding a Bachelor’s degree from King Khalid University and a Master’s degree from King Fahd University of Petroleum and Minerals, Taher has demonstrated exceptional academic performance and a commitment to the field. His career spans various roles, from technical support and research assistant to full-time lecturer and researcher at King Saud University. His objective is to advance cybersecurity research and education through innovative practices, contributing significantly to his institution and the broader academic community.

Professional profile

EducationπŸ“š

Taher’s educational background is exemplary. He graduated with honors from King Khalid University with a Bachelor in Computer Science, boasting an impressive GPA of 4.7/5. He continued to excel academically, earning a Master’s in Computer Science from King Fahd University of Petroleum and Minerals with a GPA of 3.348/4. His strong educational foundation in computer science positions him as a knowledgeable and capable researcher in his field.

Professional ExperienceπŸ›οΈ

Taher’s extensive professional experience underscores his capability and versatility. He has held various roles, from technical support and customer services to research assistant and data analyst, and now serves as a full-time lecturer and researcher at King Saud University. His responsibilities have included teaching numerous technical courses, conducting specialized training programs, and participating in curriculum development. His involvement in a research group at the Deanship of Scientific Research further solidifies his research credentials.

Research Interest🌐

Taher has contributed significantly to the field of cybersecurity through various research projects and publications. His research interests include text plagiarism detection, code similarity detection, geographic information systems, and information security. He has published several impactful papers, often serving as the corresponding author, indicating his leading role in these studies

Awards and HonorsπŸ†

Taher’s achievements have been recognized through numerous awards and honors. These include appreciation certificates from various institutions for his contributions to data analysis, academic progression, question bank development, and technical course offerings. Notably, he won an award for designing the best Information Security technical syllabus, showcasing his expertise and innovative approach in the field of cybersecurity education.

AchievementsπŸ…

Taher Ali Al-Shehari’s achievements reflect his expertise and dedication in cybersecurity. He has received numerous accolades, including appreciation certificates for his contributions to data analysis, academic progression, and curriculum development. Notably, he won an award for designing the best Information Security technical syllabus at King Saud University. His research contributions are significant, with publications in reputable journals and conferences on topics such as operating system fingerprinting, insider threat detection, and web browser security. His work has been widely recognized, underscoring his impact and leadership in the field. πŸ“šπŸ”πŸ†

Publications top notedπŸ“œ
  • “An Insider Data Leakage Detection Using One-Hot Encoding, Synthetic Minority Oversampling and Machine Learning Techniques”
    Year: 2021
    Journal: Entropy
    Citations: 117 πŸ“Š
  • “A Multi-Tiered Framework for Insider Threat Prevention”
    Year: 2021
    Journal: Electronics
    Citations: 36 πŸ›‘οΈ
  • “Empirical Detection Techniques of Insider Threat Incidents”
    Year: 2020
    Journal: IEEE Access
    Citations: 35 πŸ”
  • “Improving Operating System Fingerprinting Using Machine Learning Techniques”
    Year: 2014
    Journal: International Journal of Computer Theory and Engineering
    Citations: 29 πŸ’»
  • “Techniques and Countermeasures for Preventing Insider Threats”
    Year: 2022
    Journal: PeerJ Computer Science
    Citations: 16 🚫
  • “An Empirical Study of Web Browsers’ Resistance to Traffic Analysis and Website Fingerprinting Attacks”
    Year: 2018
    Journal: Cluster Computing Journal
    Citations: 14 🌐
  • “SCBC: Smart City Monitoring with Blockchain Using Internet of Things for and Neuro Fuzzy Procedures”
    Year: 2023
    Journal: Mathematical Biosciences and Engineering
    Citations: 12 πŸ™οΈ
  • “Wireless Video Streaming Over Data Distribution Service Middleware”
    Year: 2012
    Conference: IEEE International Conference on Computer Science and Automation Engineering
    Citations: 9 πŸ“Ί
  • “Random Resampling Algorithms for Addressing the Imbalanced Dataset Classes in Insider Threat Detection”
    Year: 2023
    Journal: International Journal of Information Security
    Citations: 6 πŸ“‰
  • “Insider Threat Detection Model Using Anomaly-Based Isolation Forest Algorithm”
    Year: 2023
    Journal: IEEE Access
    Citations: 4 🌲
  • “Enhancing Insider Threat Detection in Imbalanced Cybersecurity Settings Using the Density-Based Local Outlier Factor Algorithm”
    Year: 2024
    Journal: IEEE Access
    Citations: 1 🧩
  • “Insider Threat Detection in Cyber-Physical Systems: A Systematic Literature Review”
    Year: 2024
    Journal: Computers and Electrical Engineering
    Citations: β€” πŸ“š
  • “TumorGANet: A Transfer Learning and Generative Adversarial Network-Based Data Augmentation Model for Brain Tumor Classification”
    Year: 2024
    Journal: IEEE Access
    Citations: β€” 🧠
  • “S2DN: Design of Robust Authentication Protocol with Session Key Establishment in Multi-Controller Based Software-Defined VANETs”
    Year: 2024
    Journal: Vehicular Communications
    Citations: β€” πŸš—
  • “Mining the Opinions of Software Developers for Improved Project Insights: Harnessing the Power of Transfer Learning”
    Year: 2024
    Journal: IEEE Access
    Citations: β€” πŸ”„

Padmini MS | Computer Science | Best Researcher Award

Mrs. Padmini MS | Computer Science | Best Researcher Award

Associate Professor of The National Institute of Engineering, India

Padmini M.S. is an accomplished Assistant Professor in the Department of Computer Science and Engineering at The National Institute of Engineering, Mysore, with over 13 years of experience in teaching and research πŸ“š. She is currently pursuing her Ph.D. part-time at VTU, showcasing her dedication to continuous learning and professional growth πŸŽ“. Padmini holds an M.Tech. in Computer Networks and a B.E. in Computer Science, reflecting her strong academic foundation πŸ–₯️. Her research interests span IoT, energy efficiency, and smart environments, with numerous publications in reputable journals and international conferences 🌐. Padmini is known for her excellent communication skills, problem-solving ability, and adaptability to the latest technologies, making her a valuable team player and passionate educator πŸ‘©β€πŸ«.

Professional profile

EducationπŸ“š

Padmini M.S. is currently pursuing a Ph.D. part-time at VTU, with plans to take her comprehensive viva shortly. She holds an M.Tech. in Computer Networks from The National Institute of Engineering, Mysore, with a score of 78.5%, and a B.E. in Computer Science from Coorg Institute of Technology, with a score of 72.5%.

Professional ExperienceπŸ›οΈ

She has over 13 years of experience as an Assistant Professor in the Department of Computer Science and Engineering at The National Institute of Engineering, Mysore. Previously, she worked as a Software Engineer at Mach India Private LTD, Bangalore, for one year.

Research Interest🌐

Padmini M.S.’s research covers a wide range of topics, including IoT, energy efficiency, smart environments, and autonomous systems. Her work on “Energy Efficient Smart Street Lighting System” and “Critical Analysis of Life Span Improvement Techniques in Energy Constraints Edge IoT Devices” demonstrates her focus on practical applications and sustainability.

Awards and HonorsπŸ†

Padmini M.S. has been recognized for her significant contributions to the field of Computer Science and Engineering through various awards and honors πŸ…. She has received accolades for her innovative research on IoT, energy efficiency, and smart environments, showcased through her numerous publications in esteemed journals and presentations at international conferences πŸ“š. Her work has not only advanced academic knowledge but also demonstrated practical applications, earning her respect and recognition in the academic community 🌟. Padmini’s dedication to teaching and research excellence is evident in her commitment to continuous learning and her role as a valued mentor and educator πŸ‘©β€πŸ«.

AchievementsπŸ…
  • πŸ… Over 13 years of experience as an Assistant Professor in Computer Science and Engineering at The National Institute of Engineering, Mysore.
  • πŸ“š Published numerous papers in reputable journals and presented at international conferences.
  • πŸŽ“ Currently pursuing a Ph.D. part-time at VTU, with a strong academic background including an M.Tech. in Computer Networks and a B.E. in Computer Science.
  • 🌐 Conducted significant research in IoT, energy efficiency, and smart environments.
  • πŸ–₯️ Authored impactful papers such as “Energy Efficient Smart Street Lighting System” and “Critical Analysis of Life Span Improvement Techniques in Energy Constraints Edge IoT Devices”.
  • πŸ‘©β€πŸ« Recognized for excellent communication skills, problem-solving ability, and adaptability to new technologies.
  • 🌟 Highly respected in the academic community for her innovative research and practical applications.
  • πŸ“œ Demonstrated commitment to continuous learning and professional growth through her ongoing Ph.D. studies and research initiatives.
Publications top notedπŸ“œ
  • Critical Analysis of Life Span Improvement Techniques in Energy Constraints Edge IoT Devices
    • Authors: Padmini, M.S., Kuzhalvaimozhi, S.
    • Year: 2023
    • Journal: SN Computer Science
    • Citations: 0
    • πŸ“œπŸ“†0️⃣
  • Energy aware reliable routing model for sensor network enabled internet of things environment
    • Authors: Srikantha, P.M., Kuzhalvaimozhi, S., Silli, S.M., Verma, T., Manjunatha, V.
    • Year: 2023
    • Journal: Indonesian Journal of Electrical Engineering and Computer Science
    • Citations: 0
    • πŸŒπŸ”‹0️⃣
  • Energy Efficient Smart Street Lighting System
    • Authors: Padmini, M.S., Rajkumar, R., Prahlada, Galagali, S.S., Reddy, K.N.
    • Year: 2022
    • Conference: International Conference on Artificial Intelligence and Data Engineering, AIDE 2022
    • Citations: 1
    • πŸ’‘πŸ™οΈ1️⃣
  • An Implementation of Gesture-Controlled Autonomous Drone
    • Authors: Padmini, M.S., Kuzhalivaimozhi, S., Simha, P.V., Singh, P., Abhinandan, A.
    • Year: 2022
    • Conference: Proceedings – 2nd International Conference on Smart Technologies, Communication and Robotics 2022, STCR 2022
    • Citations: 0
    • πŸšπŸ€–0️⃣

Deepa Mulimani | Computer Science | Best Researcher Award

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 πŸŽ“. 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 πŸ“Š. 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 πŸ“š.

Professional profile

EducationπŸ“š

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 ExperienceπŸ›οΈ

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.

ResearchπŸ†

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 notedπŸ“œ
  • 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 πŸ”„
    • 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 βš–οΈ
    • Authors: Mulimani, D., Patil, P.R., Totad, S.G.
    • Year: 2023
    • Citations: 0
  • Weighted Averaging Ensemble Model for Concept Drift Adaptation in Streaming Data βš™οΈ
    • 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 πŸ’‘
    • Authors: Mulimani, D., Seeri, S.V., Patil, P., Kulkarni, S.
    • Year: 2017
    • Citations: 0

Rithish S V | Computer Science | Best Researcher Award

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 πŸŒπŸ“Š. With a strong foundation in Microservices Architecture and cloud-native application design and deployment β˜οΈπŸ’», he is actively enhancing his skills in Salesforce development πŸš€. Rithish’s projects, such as developing a cloud monitoring app on Kubernetes and an emergency assistance app called “Emergify” πŸš¨πŸ“±, 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 πŸŒŸπŸ—£οΈ. His awards and certifications further validate his dedication and excellence in the field of computer science πŸ†πŸŽ–οΈ.

Professional profile

EducationπŸ“š

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 ExperienceπŸ›οΈ

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.

SkillsπŸ†

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 notedπŸ“œ
  • 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 homophilyβ€”the tendency of individuals to associate and bond with similar othersβ€”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

Mrs. Kalpa Subbaiah | Computer Science | Women Researcher Award

VP-Lead Data Scientist of JP Morgan Chase, India

πŸ‘©β€πŸ’Ό 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

EducationπŸ“š

πŸŽ“ 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. πŸ“š

Professional ExperienceπŸ›οΈ

πŸ‘©β€πŸ’Ό Mrs. Kalpa Subbaiah boasts a robust professional journey with 16 years of experience, including 8 in Data Science. She has held roles at HP πŸ–₯️, Bosch πŸ› οΈ, Insofe 🏫, Microsoft πŸ’Ό, 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🌐

πŸ” 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) πŸ€–, Computer Vision πŸ–ΌοΈ, 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. πŸ“ŠπŸ“ˆ

Awards and HonorsπŸ†

πŸ† 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.

AchievementsπŸ…
  • πŸ“œ Published a research paper on Aspect-Based Sentiment Analysis using Weakly Supervised Learning.
  • πŸ‘©β€πŸ’» Successfully led and completed large, complex data science projects across various industries.
  • πŸ’Ό Served as a Microsoft Open Hack Coach and Lead for serverless, AI knowledge mining, and Modern Data Warehouse.
  • πŸ“Š 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.
  • πŸŽ“ Certified in multiple prestigious certifications, including AWS Machine Learning Specialty and Microsoft Azure Data Scientist.
  • πŸ€– 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.
CertificatesπŸ› οΈ
  • πŸ† AWS Certified: Machine Learning Specialty
  • πŸŽ“ Microsoft Certified: Azure Data Scientist
  • πŸ’Ό Microsoft Certified: Azure AI Engineer Associate
  • πŸš€ Microsoft: Open Hack Serverless Tech Lead
  • πŸ“Š Microsoft Certified: Data Engineer Associate
  • 🏫 Post-Graduation Certificate in β€œBig Data Analytics & Optimization” from Insofe (International School of Engineering)
  • πŸ€– Microsoft Certified: Azure AI Fundamentals
  • πŸ“ˆ Microsoft Certified: Azure Data Fundamentals
Publications top notedπŸ“œ
  • 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 πŸ“‰

Himanshi Babbar | Networking | Best Researcher Award

Himanshi Babbar | Networking | Best Researcher Award

Dr . HimanshiBabbar ,Chitkara University Institute of Engineering and Technology , India

Dr. Himanshi Babbar is an accomplished academic with extensive experience in the field of computer science and technology. She currently serves as an Assistant Professor, Research (CURIN) at Chitkara University, where she has been since February 2022. Her prior roles include working as a Full-time Research Scholar at Chitkara University and as an Assistant Professor at the Chandigarh Group of Colleges and Aryans Group of Colleges. Her teaching portfolio spans a range of undergraduate and postgraduate courses, including Computer Networks, Database Management Systems, Web Technologies, and Programming in various languages. Dr. Babbar’s research interests are centered around advanced networking topics such as Software Defined Networking (SDN), Internet of Things (IoT), Intrusion Detection Systems (IDS), and Deep Learning. Her work aims to enhance network efficiency, security, and integration with emerging technologies.

Publication profile

google scholar

Scopus Profile

ORCID

Education

Himanshi Babbar has an extensive and impressive educational background. She completed her Postdoctoral research at Zayed University, a public university in the UAE, from 2021 to 2022. Following this, she earned her PhD from Chitkara University, Punjab, a private university, between 2018 and 2021. Both of these prestigious qualifications were awarded upon completion. Prior to her PhD, Himanshi completed her Master of Computer Applications (MCA) at Chitkara University, Punjab, from 2012 to 2015, achieving a CGPA of 7.91. She also holds a Bachelor of Computer Applications (BCA) from Chitkara Institute of Engineering and Technology, Punjab, under Punjab Technical University, where she graduated with an impressive 83.0% between 2009 and 2012. Her earlier education includes completing Class XII at ICL Public School in Rajpura under the CBSE board in 2009, with a percentage of 72.6%. She also completed her Class X education at the same school in 2007, securing a percentage of 57.8%

Experience

Dr. Himanshi Babbar is currently serving as an Assistant Professor, Research (CURIN) at Chitkara University, Rajpura, Punjab Campus, since February 2022. Before this role, she was a Full-time Research Scholar at the same institution from November 2018 to December 2021. During her tenure as a Research Scholar, she taught several undergraduate courses, including “Computer Networks and Cisco Packet Tracer” at the 1st year level, “Database Management System” at the 2nd year level, and “Introduction to Web Technologies” also at the 2nd year level. Prior to her current position, Dr. Babbar worked as an Assistant Professor at the Chandigarh Group of Colleges, Landran (Mohali) from June 2016 to November 2017. Here, she taught courses such as “Digital Circuit and Logic Design”, “Software Engineering”, “System Analysis and Design (SAD)”, and “Oracle” at the 2nd year undergraduate level. Additionally, she supervised “Minor and Major Projects” at the 3rd year undergraduate level. She is also experienced in teaching “Workshop on Web Development” and “Java” at the 3rd year undergraduate level, as well as “Programming in C” at the 2nd year MBA (IT) level. Earlier in her career, Dr. Babbar held the position of Assistant Professor at the Aryans Group of Colleges, Chandigarh from August 2015 to November 2015. During this period, she taught “Information Technology” at the 1st year postgraduate level, “Digital Circuit and Logic Design” at the 2nd year undergraduate level, and “Programming in Java” at the 3rd year undergraduate level.

 

Research focus

Dr. Himanshi Babbar’s areas of expertise and research interests include Software Defined Networking, Internet of Things, Intrusion Detection Systems, and Deep Learning. These fields reflect her deep engagement with cutting-edge technologies and their applications, showcasing her commitment to advancing knowledge and innovation in these domains

Skills:

Dr. Himanshi Babbar possesses a strong technical skill set, including proficiency in programming languages such as C, C++, and Python. Her software skills include experience with development environments and tools like Eclipse, Turbo C++, Dev C++, Code-Blocks, ORACLE, NetBeans, and Mininet. She is adept at using various operating systems, including Windows 8, Windows 7, Windows XP, and Ubuntu 18.04 LTS. Additionally, Dr. Babbar is skilled in using Overleaf (LATEX) for document preparation, Origin for data analysis, and MS-Office Suite (Word, Excel, PowerPoint) for general office tasks.

Publication top notes

  • Security framework for internet-of-things-based software-defined networks using blockchain
    • Year: 2022
    • Journal: IEEE Internet of Things Journal
    • Authors: S Rani, H Babbar, G Srivastava, TR Gadekallu, G Dhiman
    • πŸ“…πŸ”’πŸŒ
  • An optimized approach of dynamic target nodes in wireless sensor network using bio inspired algorithms for maritime rescue
    • Year: 2022
    • Journal: IEEE Transactions on Intelligent Transportation Systems
    • Authors: S Rani, H Babbar, P Kaur, MD Alshehri, SH Shah
    • πŸ“…πŸš’πŸ”„
  • An efficient and lightweight deep learning model for human activity recognition using smartphones
    • Year: 2021
    • Journal: Sensors
    • Authors: Ankita, S Rani, H Babbar, S Coleman, A Singh, HM Aljahdali
    • πŸ“…πŸ“±πŸ§ 
  • Load balancing algorithm for migrating switches in software-defined vehicular networks
    • Year: 2021
    • Journal: Comput. Mater. Contin
    • Authors: H Babbar, S Rani, M Masud, S Verma, D Anand, N Jhanjhi
    • πŸ“…πŸš—πŸ”„
  • Energy‐Efficient Routing Protocol for Next‐Generation Application in the Internet of Things and Wireless Sensor Networks
    • Year: 2022
    • Journal: Wireless Communications and Mobile Computing
    • Authors: R Dogra, S Rani, H Babbar, D Krah
    • πŸ“…πŸ”‹πŸ“‘
  • Intelligent edge load migration in SDN-IIoT for smart healthcare
    • Year: 2022
    • Journal: IEEE Transactions on Industrial Informatics
    • Authors: H Babbar, S Rani, SA AlQahtani
    • πŸ“…πŸ₯πŸ”„
  • A genetic load balancing algorithm to improve the QoS metrics for software defined networking for multimedia applications
    • Year: 2022
    • Journal: Multimedia Tools and Applications
    • Authors: H Babbar, S Parthiban, G Radhakrishnan, S Rani
    • πŸ“…πŸŽ₯πŸ”„
  • Load balancing algorithm on the immense scale of internet of things in SDN for smart cities
    • Year: 2021
    • Journal: Sustainability
    • Authors: H Babbar, S Rani, D Gupta, HM Aljahdali, A Singh, F Al-Turjman
    • πŸ“…πŸ™οΈπŸ”„
  • Cloud based smart city services for industrial internet of things in software-defined networking
    • Year: 2021
    • Journal: Sustainability
    • Authors: H Babbar, S Rani, A Singh, M Abd-Elnaby, BJ Choi
    • πŸ“…β˜οΈπŸ™οΈ
  • Software-defined networking framework securing internet of things
    • Year: 2020
    • Journal: Integration of WSN and IoT for Smart Cities
    • Authors: H Babbar, S Rani
    • πŸ“…πŸ”’πŸ“‘

Prakhar Consul | Computer Science | Best Researcher Award

Prakhar Consul | Computer Science | Best Researcher Award

Mr Prakhar Consul, Bennett University, India

Prakhar Consul is an Assistant Professor and Ph.D. candidate at Bennett University, specializing in Internet-of-Things, Mobile Edge Computing, and Deep Reinforcement Learning. He holds an M.Tech. in Electronics and Communication from Sharda University and a B.Tech. from Shobhit University. With a robust teaching background in subjects like Microprocessors and Embedded Systems, his research focuses on computational offloading and resource allocation for UAV-assisted Mobile Edge Computing in 5G networks. Prakhar has taught at Dewan V S Institute, Neelkanth Group of Institutions, and I A M R Group of Institutions. πŸŽ“πŸ“‘πŸ€–πŸ“˜

Publication profile

google scholar

Education

Dr. Prakhar Consul is a Ph.D. candidate in Computer Science Engineering at Bennett University, India, expected to complete in Nov. 2024. Their thesis focuses on computational offloading and resource allocation in mobile edge computing using machine learning in 5G networks πŸ“‘. They hold an M.Tech in Electronics and Communication from Sharda University (2015) with a thesis on microstrip patch antennas πŸ“Ά. Dr. Prakhar Consul also has a B.Tech in Electronics and Communication from Shobhit University (2013) and completed their senior secondary education at J.A.S. Inter College 🏫. Their academic journey is marked by excellence and innovation in engineering and technology πŸ’‘.

Experience

Dr. Prakhar Consul served as an Assistant Professor in the Department of Electronics and Communication Engineering at Dewan V S Institute of Engineering and Technology (DVSIET), Meerut, India, from January 2020 to October 2021. Prior to this, they worked at Neelkanth Group of Institutions (NGI), Meerut, from August 2018 to January 2020 in the Department of Electronics and Electrical Engineering. From August 2015 to August 2018, they were part of the Department of Electronics and Communication Engineering at I A M R Group of Institutions, Meerut. Their extensive teaching experience highlights their dedication to education and engineering. πŸ“šπŸ”ŒπŸ‘¨β€πŸ«

Research focus

P. Consul’s research focuses on advancing wireless communication systems, with an emphasis on energy efficiency, security, and optimization in emerging technologies. His work includes developing innovative antenna designs, such as microstrip and U-slotted patch antennas, and enhancing energy-efficient schemes for mobile edge computing (MEC) using federated learning and reinforcement learning. He explores security in UAV-assisted systems, with solutions for secure computation and resource allocation in blockchain-assisted cyber-physical systems. His research also covers dual and triple band gap antennas and resource optimization strategies for digital twin-empowered UAV networks. πŸš€πŸ“‘πŸ”

Publication top notes

Triple band gap coupled microstrip U-slotted patch antenna using L-slot DGS for wireless applications

Federated learning based energy efficient scheme for MEC with NOMA underlaying UAV

Power allocation scheme based on DRL for CF massive MIMO network with UAV

Security reassessing in UAV-assisted cyber-physical systems based on federated learning

Deep reinforcement learning based energy consumption minimization for intelligent reflecting surfaces assisted D2D users underlaying UAV network

FLBCPS: federated learning based secured computation offloading in blockchain-assisted cyber-physical systems

A review of different vulnerabilities of security in a layered network

A hybrid secure resource allocation and trajectory optimization approach for mobile edge computing using federated learning based on WEB 3.0

A Hybrid Task Offloading and Resource Allocation Approach For Digital Twin-Empowered UAV-Assisted MEC Network Using Federated Reinforcement Learning For Future Wireless Network

Federated reinforcement learning based task offloading approach for MEC-assisted WBAN-enabled IoMT

Srinivas Bhattiprolu | Computer Science | Best Researcher Award

Dr. Srinivas Bhattiprolu | Computer Science | Best Researcher Award

Associate Professor of Aditya College of Engineering and Technology, India

Dr. Srinivas Bhattiprolu is an esteemed educator and researcher in the field of computer science, specializing in image processing. He earned his Ph.D. from JNTUK, Kakinada in November 2021, adding to his impressive academic credentials, which include an M.Tech. from RVR & JC College of Engineering and an M.Sc. from Ideal Degree College. With over 16 years of teaching experience, Dr. Bhattiprolu has held positions at various prestigious institutions such as Aditya College of Engineering & Technology, Swami Vivekananda Institute of Technology, and Pragati Engineering College. His dedication to education is evident through his consistent academic achievements and contributions to the field of computer science. Dr. Bhattiprolu is committed to advancing knowledge and nurturing the next generation of technology professionals. πŸ“–πŸŽ“πŸ‘¨β€πŸ«

Professional profile

EducationπŸ“š

Dr. Srinivas Bhattiprolu has an impressive academic background in computer science. He earned his Ph.D. in Computer Science from JNTUK, Kakinada, specializing in image processing, in November 2021. Prior to this, he completed his M.Tech. in Computer Science and Engineering from RVR & JC College of Engineering, affiliated with Acharya Nagarjuna University, in 2007, securing a distinction with 73.2%. Dr. Bhattiprolu also holds an M.Sc. in Computer Science from Ideal Degree College, affiliated with Andhra University, which he completed in 2004 with a first-class score of 65.1%. His academic journey began with a B.Sc. in Mathematics, Electronics, and Computer Science from RIMS Degree College, affiliated with Andhra University, where he graduated in 2001 with a first-class score of 62.5%. He completed his 12th grade from the Board of Intermediate Education in 1998 with a first-class score of 71.1%, and his 10th grade from the Board of Secondary Education in 1996 with a first-class score of 79.7%. πŸ“œπŸ‘¨β€πŸŽ“

Professional ExperienceπŸ›οΈ

Dr. Srinivas Bhattiprolu has amassed 16 years of extensive teaching experience in computer science. Currently, he serves as an Assistant Professor at Aditya College of Engineering & Technology, Surampalem, a position he has held since December 2020. Previously, he was an Assistant Professor at Swami Vivekananda Institute of Technology, Secunderabad from July 2018 to December 2019, where he was ratified by JNT University, Hyderabad in 2019. From July 2017 to June 2018, Dr. Bhattiprolu taught at Nishitha College of Engineering and Technology, Hyderabad, and was ratified by JNT University, Hyderabad in 2018. His tenure at Pragati Engineering College, Surampalem, spanned from June 2010 to July 2017, during which he progressed from Assistant to Associate Professor and was ratified by JNT University, Kakinada in 2010. Earlier in his career, from November 2007 to May 2010, he served as an Assistant Professor at Sreenidhi Institute of Science and Technology, Hyderabad, receiving ratification from JNT University, Hyderabad in 2009. Dr. Bhattiprolu’s commitment to education and his contributions to the academic community are truly commendable. πŸŽ“πŸ…πŸ“˜

Research Interest🌐

Dr. Srinivas Bhattiprolu’s research interests are deeply rooted in the field of computer science, with a particular focus on image processing. His work explores advanced techniques in image analysis, enhancement, and recognition, aiming to develop innovative solutions for real-world applications. Dr. Bhattiprolu is passionate about leveraging machine learning and artificial intelligence to enhance image processing methodologies, striving to push the boundaries of what is possible in digital imaging. His research also delves into the integration of computer vision with other emerging technologies to address complex challenges in various domains. Through his dedication and expertise, Dr. Bhattiprolu contributes significantly to the advancement of knowledge and technology in the realm of image processing. πŸ“·πŸ€–πŸ“ˆ

Awards and HonorsπŸ†

Dr. Srinivas Bhattiprolu has received numerous accolades throughout his distinguished career. His exceptional contributions to the field of computer science and education have earned him recognition and respect from both academic and professional communities. Notably, he was ratified as an Assistant Professor by JNT University, Hyderabad in 2009, 2018, and 2019, and by JNT University, Kakinada in 2010, highlighting his consistent excellence in teaching and research. These ratifications are a testament to his expertise, dedication, and significant impact on the academic institutions he has been a part of. Dr. Bhattiprolu’s commitment to advancing the field of computer science continues to be acknowledged through these prestigious honors. πŸŒŸπŸ“œπŸ‘

Research skillπŸ”¬

Dr. Srinivas Bhattiprolu possesses a robust set of research skills that underpin his contributions to the field of computer science. His expertise in image processing is complemented by a deep understanding of machine learning and artificial intelligence, enabling him to develop advanced algorithms for image analysis and recognition. Dr. Bhattiprolu is proficient in various programming languages and software tools essential for conducting high-level research. His analytical skills and attention to detail ensure the accuracy and reliability of his findings. Additionally, he excels in data interpretation and the practical application of theoretical concepts, which significantly enhances the relevance and impact of his research. Dr. Bhattiprolu’s ability to integrate interdisciplinary approaches further strengthens his research capabilities, making him a versatile and innovative scholar. πŸ”§πŸ“ŠπŸ€–

AchievementsπŸ…
  • πŸŽ“ Successfully earned a Ph.D. in Computer Science with a specialization in Image Processing from JNTUK, Kakinada, in Nov-2021.
  • πŸ… Secured M.Tech. (Computer Science and Engineering) with 73.2% Distinction from RVR & JC College of Engineering, Acharya Nagarjuna University, in 2007.
  • πŸ“œ Completed M.Sc. in Computer Science with 65.1% First Class from Ideal Degree College, Andhra University, in 2004.
  • πŸ‘¨β€πŸ« Accumulated 16 years of teaching experience across multiple prestigious institutions.
  • πŸ† Ratified as an Assistant Professor by JNT University, Hyderabad in 2009, 2018, and 2019, and by JNT University, Kakinada in 2010.
  • πŸ” Developed advanced image processing algorithms integrating machine learning and AI techniques.
  • πŸ“š Contributed significantly to the academic community through innovative research and publications.
  • πŸ’Ό Currently serving as an Assistant Professor at Aditya College of Engineering & Technology, Surampalem, since Dec-2020.
  • 🌟 Recognized for excellence in both teaching and research within the computer science field.
ProjectsπŸ› οΈ
  • πŸ“· Advanced Image Processing Techniques: Developed algorithms for enhanced image analysis and recognition, integrating machine learning and AI methodologies.
  • 🧠 AI-Driven Medical Imaging Solutions: Created innovative solutions for medical imaging to improve diagnostic accuracy using AI and computer vision.
  • πŸ€– Machine Learning in Pattern Recognition: Led a project focused on applying machine learning techniques for advanced pattern recognition in various applications.
  • 🌍 Environmental Monitoring Systems: Developed systems for real-time environmental monitoring using image processing and remote sensing technologies.
  • πŸš— Autonomous Vehicle Navigation: Contributed to the development of navigation systems for autonomous vehicles, leveraging computer vision and sensor fusion.
  • πŸ” Security Surveillance Enhancement: Implemented advanced image processing techniques to enhance the capabilities of security surveillance systems.
  • πŸ“Š Big Data Analysis for Image Processing: Worked on projects involving the analysis and processing of large datasets to improve image processing algorithms.
  • πŸ”§ Software Tools for Image Analysis: Developed user-friendly software tools to facilitate the analysis and manipulation of digital images for various applications.
  • 🌟 Interdisciplinary Research Projects: Engaged in interdisciplinary projects combining computer science with other fields to address complex research challenges.
  • πŸ’‘ Innovation in Educational Technology: Created educational tools and platforms utilizing image processing to enhance learning experiences in computer science education.
Publications top notedπŸ“œ
  • Accelerating Autonomous Vehicle Safety through Real-Time Immersive Virtual Reality Gaming Simulations
    • Authors: Kiran, A., Salunkhe, S.S., Srinivas, B., Altaf Ahmed, M., Venkata Naga Ramesh, J.
    • Year: 2024
    • Citations: 0 πŸ“‰
  • A Review on Sentiment Analysis of Twitter Data for Diabetes Classification and Prediction
    • Authors: Akhila, A.M.S., Gayathri, C., Srinivas, B., Devi, B.S.K.
    • Year: 2022
    • Citations: 1 πŸ“ˆ
  • Second Order Derivative Cross Diagonal Matrix Approach for CBIR
    • Authors: Srinivas, B., Venkata Krishna, V., Sumalatha, L.
    • Year: 2020
    • Citations: 0 πŸ“‰
  • A New Framework for CBIR Using Odd and Even Tetra Texton Matrix
    • Authors: Srinivas, B., Krishna, V.V., Sumalatha, L.
    • Year: 2020
    • Citations: 2 πŸ“ˆ
  • Advanced Local Direction Cross Diagonal Matrix
    • Authors: Srinivas, B., Venkata Krishna, V., Sumalatha, L.
    • Year: 2019
    • Citations: 4 πŸ“ˆ