Amirreza Masoodi | Computational Modeling | Best Researcher Award

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Assist. Prof. Dr. Amirreza Masoodi | Computational Modeling | Best Researcher Award  🏆

Assistant Professor at Ferdowsi University of Mashhad, Iran.

Dr. Amir R. Masoodi is an accomplished Assistant Professor in Structural Engineering at Ferdowsi University of Mashhad, Iran. His research spans structural stability, nonlinear vibration, composite materials, and advanced computational methods. With extensive academic qualifications and a strong publication record, he has contributed significantly to structural engineering and materials science. Dr. Masoodi’s work includes innovative applications of finite element methods and multiscale analysis, with impactful publications in high-quality international journals. He has also received multiple prestigious awards, highlighting his expertise and leadership in the field.

Profile

Scopus

Orcid

Google Scholar

 

Education 🎓:

Dr. Masoodi holds a Ph.D. in Structural Engineering (Applied Mechanics) from Ferdowsi University of Mashhad, where he specialized in nonlinear finite element analysis of composite shells, graduating with a stellar GPA of 19.41/20. He completed his M.Sc. in Structural Engineering (Stability of Structures) from the same institution, focusing on exact stiffness matrix development for non-prismatic FG beam-columns (GPA: 18.45/20). His academic foundation was laid during his B.Sc. in Civil Engineering at Ferdowsi University, graduating with a GPA of 17.60/20. His education reflects a profound commitment to computational mechanics, stability, and structural dynamics.

Work Experience 💼:

Dr. Masoodi serves as the Director of Physical Resources at Ferdowsi University, blending academic and administrative excellence. He leads engineering projects as the CEO of Pardis Sazeh Manshour Hashtom and acts as a Structural Counselor for Mashhad Electric Energy Distribution Co. His tenure includes roles as an educational supervisor and assistant to the Vice Chancellor for Finance and Administration. Noteworthy projects include designing LSF structures, industrial warehouses, and retrofitting buildings. His professional journey demonstrates a seamless integration of theory and practice, fostering impactful engineering solutions.

Awards and Honors 🏆

Dr. Masoodi’s achievements include recognition as a Distinguished Lecturer by Sadjad University of Technology (2019) and as an Elite Ph.D. Student by the National Elite Foundation of Iran (2016-2018). He was honored as the Top Researcher and Top Ph.D. Student by Ferdowsi University and the Civil Engineering Department. His journey began with a remarkable ranking in the top 0.4% of the B.Sc. entrance exam among 250,000 participants. These accolades underscore his dedication to academic and research excellence.

Research Interests:

Dr. Masoodi’s research encompasses the stability and dynamics of structures, nonlinear vibration, and soil-structure interaction. He is particularly intrigued by composite materials, FGMs, and CNT-reinforced structures. His expertise extends to computational mechanics, multiscale analysis, and the development of finite elements for beams, shells, and other structural components. His innovative work in thermal and mechanical analysis bridges advanced theoretical frameworks with practical engineering applications.

📚 Publications 

  • Vibration of FG-CNT and FG-GNP Sandwich Composite Coupled Conical-Cylindrical-Conical Shell
    • Authors: E. Sobhani, A.R. Masoodi, A. Ahmadi-Pari
    • Citations: 84
    • Year: 2021
  • Free vibration analysis of functionally graded hybrid matrix/fiber nanocomposite conical shells using multiscale method
    • Authors: M. Rezaiee-Pajand, E. Sobhani, A.R. Masoodi
    • Citations: 77
    • Year: 2020
  • Static analysis of functionally graded non-prismatic sandwich beams
    • Authors: M. Rezaiee-Pajand, A.R. Masoodi, M. Mokhtari
    • Citations: 68
    • Year: 2018
  • Nonlinear analysis of FG-sandwich plates and shells
    • Authors: M. Rezaiee-Pajand, E. Arabi, A.R. Masoodi
    • Citations: 67
    • Year: 2019
  • Agglomerated impact of CNT vs. GNP nanofillers on hybridization of polymer matrix for vibration of coupled hemispherical-conical-conical shells
    • Authors: E. Sobhani, A.R. Masoodi, O. Civalek, A.R. Ahmadi-Pari
    • Citations: 62
    • Year: 2021
  • Semi-analytical vibrational analysis of functionally graded carbon nanotubes coupled conical-conical shells
    • Authors: M. Rezaiee-Pajand, E. Sobhani, A.R. Masoodi
    • Citations: 59
    • Year: 2021
  • Exact natural frequencies and buckling load of functionally graded material tapered beam-columns considering semi-rigid connections
    • Authors: M. Rezaiee-Pajand, A.R. Masoodi
    • Citations: 57
    • Year: 2018
  • Natural frequency responses of hybrid polymer/carbon fiber/FG-GNP nanocomposites paraboloidal and hyperboloidal shells based on multiscale approaches
    • Authors: E. Sobhani, A.R. Masoodi
    • Citations: 48
    • Year: 2021
  • Multifunctional trace of various reinforcements on vibrations of three-phase nanocomposite combined hemispherical-cylindrical shells
    • Authors: E. Sobhani, R. Moradi-Dastjerdi, K. Behdinan, A.R. Masoodi
    • Citations: 45
    • Year: 2022
  • Natural frequency analysis of FG-GOP/polymer nanocomposite spheroid and ellipsoid doubly curved shells reinforced by transversely-isotropic carbon fibers
    • Authors: E. Sobhani, A.R. Masoodi, Ö. Civalek, M. Avcar
    • Citations: 42
    • Year: 2022

Conclusion 

Dr. Amir R. Masoodi’s credentials, research achievements, and academic recognition position him as a strong candidate for the Best Researcher Award. His contributions to structural engineering and materials science are both innovative and impactful. While enhancing his global collaborations and securing competitive research funding would further solidify his profile, his current accomplishments and accolades make him highly deserving of this recognition.

 

 

Ghasem Sadeghi Bajestani | Computational Modeling | Best Researcher Award

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Ghasem Sadeghi Bajestani | Computational Modeling | Best Researcher Award  🏆

Vice president for Research and Technology at International University of Imam Reza🎓

Ghasem Sadeghi Bajestani is an Assistant Professor of Medical Engineering at Imam Reza International University in Iran. He holds a Ph.D. in Biomedical Engineering from the University of Science Researches in Tehran. His specialization is in cybernetic systems with a particular interest in brain disorders, especially Autism Spectrum Disorder. Through the application of chaos theory, he seeks to bring new insights into the field of neurodevelopmental disorders.

Professional Profile 

🎓 Education

  • He earned his Bachelor of Science in Electronics from Shiraz University in Fars, Iran.
  • He pursued a Master of Science in Bioelectric Engineering at the Islamic Azad University, Science and Research Branch, in Tehran.
  • He completed his Ph.D. in Bioelectric Engineering at Amirkabir University of Technology, Tehran, from 2011 to 2016.
  • Additionally, he earned a Ph.D. in Biomedical Engineering from the Islamic Azad University, Science and Research Branch, Tehran, between 2010 and 2014.

🏢 Work Experience

Currently, Ghasem Sadeghi Bajestani holds the position of Vice President for Research and Technology in Biomedical Engineering at Imam Reza International University. His role includes overseeing and advancing the university’s research initiatives in medical engineering, with a strong emphasis on neuroengineering and cybernetic applications.

🧬 Skills

  • Cybernetics, particularly in biomedical contexts.
  • Application of chaos theory to study complex neurological conditions.
  • Specialized research in Autism Spectrum Disorder.
  • Proficiency in bioelectric engineering and related fields.

Awards and Honors 🏆

🏅 Although specific awards and honors are not listed, Ghasem Sadeghi Bajestani’s contributions to biomedical engineering are demonstrated through his leadership roles and research output, reflecting his recognition within the academic and professional community.

📚 Teaching Experience

📘 As an Assistant Professor at Imam Reza International University, Ghasem Sadeghi Bajestani engages in teaching and mentoring students. His teaching focuses on medical and biomedical engineering, with a particular emphasis on cybernetic systems and their application in neurodevelopmental research.

🔬 Research Focus

Ghasem Sadeghi Bajestani’s research centers around cybernetics and chaos theory applied to the study of brain disorders, especially Autism Spectrum Disorder. His work aims to utilize processing methods derived from chaos theory to explore and better understand the complexities of neurological and neurodevelopmental disorders.

Conclusion 

Overall, Ghasem Sadeghi Bajestani is a strong contender for the Best Researcher Award. His groundbreaking research in cybernetics and chaos theory, particularly in relation to autism, coupled with his leadership role and academic expertise, make him a deserving candidate. With expanded international collaboration and a broader research scope, his already notable contributions could achieve even greater impact. His current achievements, dedication, and innovative research align well with the prestigious recognition offered by this award.

📚 Publilcation 

  • “Mindfulness-Enhancing Instruction (MEI): Contributions to Electroencephalogram (EEG) Dynamics, Higher Order Thinking Skills (HOTS), and Effective Learning”
  • “Diagnosis of Adult ADHD Using EEG Signals Based on the Spectrogram and Convolutional Neural Networks”
  • “The Impact of Blended Mindfulness Intervention (BMI) on University Students’ Sustained Attention, Working Memory, Academic Achievement, and Electroencephalogram (EEG) Asymmetry”
  • “A Generalized Visibility Graph Algorithm for Analyzing Biological Time Series Having Rotation in Polar Plane”
  • “Diagnosis of Autism Spectrum Disorder Based on Complex Network Features”
  • “PSG Dynamic Changes in Methamphetamine Abuse Using Recurrence Quantification Analysis”
  • “A Hierarchical Model for Autism Spectrum Disorder (HMASD)”
    • Year: Not specified
    • Journal: (Journal not specified in provided data)
    • DOI: 10.17795/rijm39107
  • “Cybernetic Approach in Identification of Brain Pattern Variations in Autism Spectrum Disorder”
    • Year: Not specified
    • Journal: (Journal not specified in provided data)
    • DOI: S101623721650006X

Dr Tanmoy Bhattacharya | Computational Modeling | Best Researcher Award

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Dr Tanmoy Bhattacharya |  External Professor | Best Researcher Award🏆

External Professor at Santa Fe Institute,United States🎓

Tanmoy Bhattacharya is a distinguished scientist and researcher, currently holding the position of Scientist 5 and Laboratory Fellow at Los Alamos National Laboratory (LANL) and serving as an External Professor at the Santa Fe Institute. With a career spanning over three decades, Bhattacharya has made significant contributions to physics, computational biology, and microbiology. He is renowned for his interdisciplinary research, leadership in scientific collaborations, and innovations in computational tools that have had a lasting impact on the scientific community.

Professional Profile 

🧑‍🎓Education🎓

Tanmoy Bhattacharya’s academic journey began at the prestigious Indian Institute of Technology (IIT) Kharagpur, where he earned his B.Sc. in Physics in 1982, followed by an M.Sc. in Physics in 1984 under the guidance of Prof. Debabrata Basu. He then pursued his Ph.D. in Physics at the Tata Institute of Fundamental Research in Bombay, India, completing his dissertation on “Tree Unitarity Breakdown in Spontaneously Broken N=1 Supergravity Theories and Phenomenology of a Superlight Gravitino” in 1989 under the mentorship of Prof. Probir Roy.

💼Work Experience

Bhattacharya’s professional career began with post-doctoral fellowships at Brookhaven National Laboratory, Centre de Energie Atomique in Saclay, and Los Alamos National Laboratory (LANL) between 1989 and 1995. He transitioned to a staff role at LANL in 1995 and has been a significant contributor to the laboratory ever since. His roles have evolved from Limited Term Staff Member to Scientist 5 and Laboratory Fellow, reflecting his growing expertise and leadership within the institution. Additionally, he served as a Professor at the Santa Fe Institute from 2006 to 2017 and continues to contribute as an External Professor.

🛠️Skills

Tanmoy Bhattacharya possesses a wide range of skills, including expertise in theoretical physics, computational biology, and microbiology. His technical skills extend to programming and software development, having contributed to the creation of tools like hyperTeX, the hyperref LaTeX package, and the development of the Apache webserver. His ability to lead large-scale research collaborations and his contributions to computational methods in high-energy physics and lattice quantum chromodynamics demonstrate his proficiency in both scientific research and technical innovation.

🏆Awards and Honors

Bhattacharya has been the recipient of numerous prestigious awards throughout his career. Some of his notable honors include the Los Alamos Distinguished Performance Award (1999, 2022), the Duke CHAVI-ID Outstanding Contributions Award (2015), and recognition as a Highly Cited Researcher by Clarivate Analytics in multiple years (2016, 2018, 2019, 2020). In 2020, he was named a Los Alamos Laboratory Fellow, a testament to his exceptional contributions to the scientific community. Most recently, in 2023, he was recognized among the top scientists in Biology and Biochemistry by research.com and was part of the LANL team that won an R&D 100 award for the “CANDLE” project.

 Membership 🏛️

Tanmoy Bhattacharya is a member of the American Physical Society, actively participating in divisions such as Computational Physics and Particles and Fields. He has held leadership roles in the US Lattice Quantum Chromodynamics (USQCD) collaboration, contributing to the strategic direction of high-energy physics. Additionally, he moderates the hep-lat arXiv and is involved in the International Society of Genetic Genealogy.

Research Focus 🔬

Bhattacharya’s research focuses primarily on theoretical physics, computational biology, and microbiology. His work in lattice quantum chromodynamics (LQCD) has been pivotal in understanding fundamental particles and forces. In the field of computational biology, he has made significant contributions to HIV research and genetic analysis, as evidenced by his work with the HIV Genetics and HIV Database teams at LANL. His interdisciplinary approach allows him to tackle complex problems at the intersection of physics, biology, and computer science, making his research both innovative and impactful across multiple fields.

📖Publications : 

  1. High dimensional predictions of suicide risk in 4.2 million US Veterans using ensemble transfer learning
    🗓️ 2024 | 📰 Scientific Reports | 🧠📈
  2. The pion-nucleon sigma term from Lattice QCD
    🗓️ 2024 | 📰 Proceedings of Science | 💥🔬
  3. Control variates for lattice field theory
    🗓️ 2024 | 📰 Physical Review D | 📊🧮
  4. Prevention efficacy of the broadly neutralizing antibody VRC01 depends on HIV-1 envelope sequence features
    🗓️ 2024 | 📰 Proceedings of the National Academy of Sciences of the United States of America | 🦠💉
  5. Nucleon isovector axial form factors
    🗓️ 2024 | 📰 Physical Review D | ⚛️📏
  6. Deep learning uncertainty quantification for clinical text classification
    🗓️ 2024 | 📰 Journal of Biomedical Informatics | 🤖📚
  7. Confronting the axial-vector form factor from lattice QCD with MINERvA antineutrino-proton data
    🗓️ 2023 | 📰 Physical Review D | 🧪🔬
  8. Quark chromoelectric dipole moment operator on the lattice
    🗓️ 2023 | 📰 Physical Review D | ⚛️⚙️
  9. Electroweak box diagram contribution for pion and kaon decay from lattice QCD
    🗓️ 2023 | 📰 Physical Review D | 📦🔋
  10. nEDM from the theta-term and chromoEDM operators
    🗓️ 2023 | 📰 Proceedings of Science | 🧲📐

Saranya R | Deep Learning | Best Researcher Award

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Mrs. Saranya R | Deep Learning | Best Researcher Award

Mrs. Saranya R Aarupadai Veedu institute of technology, India

“Mrs. Saranya R is a dedicated educator at Aarupadai Veedu Institute of Technology, India, known for her passion for teaching and commitment to student success. With expertise in [mention her area of specialization if known], she brings [number] years of experience in academia, shaping the minds of future engineers and professionals. Mrs. Saranya R is admired for her innovative teaching methods and contributions to [mention any specific academic or research initiatives she’s involved in]. She holds [mention any relevant degrees or qualifications]. Outside academia, she enjoys [mention any hobbies or interests].”

 

Professional Profile:

Education

M.Tech (CSE),SRM University, 2014,Percentage: 87% (First Class with Distinction),BE (CSE),Vels Srinivasa College of Engg and Tech, Anna University, 2009,Percentage: 71%,HSC (Higher Secondary School Certificate),St. Joseph of Cluny Matriculation Higher Secondary School, Neyveli, 2005,Percentage: 83%,SSLC (Secondary School Leaving Certificate),St. Joseph of Cluny Matriculation Higher Secondary School, Neyveli, 2003,Percentage: 63%

 

Field of Interest:

Artificial Intelligence,Blockchain,Computer Networks,C, C++, Java, Python,Software Engineering

Achievements:

Acted as Faculty AdvisorOrganized association inaugural functions,Achieved over 90% results in more than 3 subjects,Published paper on “Enhancing COVID-19 diagnosis from lung CT scans using optimized quantum-inspired complex convolutional neural network with ResNeXt-50” in Biomedical Signal Processing and Control (Q1 journal, impact factor 5.1, cite score 9.8)

Work Experience:

Research Scholar (Full Time),Aarupadai Veedu Institute of Technology,Present,Assistant Professor,Sri Ramanujar Engineering College, Chennai,March 2010 – Present,Trainee Software Developer,Vojus Incorporated,May 2009 – February 2010

Subjects Taught:

Object Oriented Programming,Fundamentals of Computer Programming,Operating Systems,Computer Networks,Object Oriented Analysis and Design,Engineering Economics and Financial Accounting

Publications
  • Enhancing cyber security in WSN using optimized self-attention-based provisional variational auto-encoder generative adversarial network (Meenakshi, B., Karunkuzhali, D. Computer Standards and Interfaces, 2024, 88, 103802) 📚 (2 Citations)
  • Robotic Restroom Hygiene Solutions with IoT and Recurrent Neural Networks for Clean Facilities (Nasreen, A.K., Shenbagapriya, M., Seeni, S.K., … Meenakshi, B., Murugan, S. 7th International Conference on Inventive Computation Technologies, ICICT 2024, pp. 1842–1847) 📚 (0 Citations)
  • Automotive CAN-Based Intelligent Collision Avoidance System using Machine Learning and Cloud Computing (Santhuja, P., Selvi, C., Jehan, C., … Meenakshi, B., Mathivanan, K. Proceedings of the 2024 10th International Conference on Communication and Signal Processing, ICCSP 2024, pp. 1156–1161) 📚 (0 Citations)
  • Agriculture Yield Estimation Using Machine Learning Algorithms (Raman, R., Kantari, H., Gokhale, A.A., … Meenakshi, B., Srinivasan, S. 2024 International Conference on Automation and Computation, AUTOCOM 2024, pp. 187–191) 📚 (11 Citations)
  • Speed and Torque Optimization of Motor Drive Through Intelligent Control Approaches (Kantari, H., Vadivel, M., Jagadeesan, P., … Meenakshi, B., Velmurugan, S. 2024 International Conference on Automation and Computation, AUTOCOM 2024, pp. 192–196) 📚 (0 Citations)
  • A Gradient Boosting Algorithm to Predict Energy Consumption for Home Applications (Sivakumar, V.G., Arunfred, N., Anusha, N., … Meenakshi, B., Sujatha, S. 2024 2nd International Conference on Computer, Communication and Control, IC4 2024) 📚 (0 Citations)
  • Wind Power Forecasting with Support Vector Machines using Sparrow Search Algorithm (Lakshmi, V.V., Giriprasad, S., Vimal, S.P., … Meenakshi, B., Srinivasan, S. 2024 2nd International Conference on Computer, Communication and Control, IC4 2024) 📚 (0 Citations)
  • Smart Renewable Energy Management Using Internet of Things and Reinforcement Learning (Dhayalan, V., Raman, R., Kalaivani, N., … Reddy, R.S., Meenakshi, B. 2024 2nd International Conference on Computer, Communication and Control, IC4 2024) 📚 (0 Citations)
  • Blockchain-enabled joint trust (RF-AOA-HTSA) algorithm-based multiobjective clustering protocol for wireless sensor network (Meenakshi, B., Karunkuzhali, D., Ali, S.M. Concurrency and Computation: Practice and Experience, 2023, 35(28), e7860) 📚 (0 Citations)
  • Enhanced Elman spike neural network for cluster head based energy aware routing in WSN (Meenakshi, B., Karunkuzhali, D. Transactions on Emerging Telecommunications Technologies, 2023, 34(3), e4708) 📚 (5 Citations)

 

Meenakshi B | Computational Modeling | Best Researcher Award

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Dr. Meenakshi B | Computational Modeling | Best Researcher Award

Professor of Sri Sairam Engineering College, India

Dr. Meenakshi B is a distinguished Professor in Information and Communication Engineering 🎓📡, holding an M.E. and Ph.D. in the field. With an extensive teaching career spanning over three decades, she has guided both undergraduate 👨‍🏫 and postgraduate 📖 students. Dr. Meenakshi has a robust publication record, contributing to national and international journals and conferences 🌍📚. She is actively involved in professional development, having attended numerous FDPs, workshops, webinars, and online courses 🎓💻. Her research focuses on energy-efficient wireless sensor networks, and she has received funding for several innovative projects 🌿🔧. Dr. Meenakshi’s achievements include several patents and a book on transmission lines and networks 📘🔬. A member of various prestigious professional bodies, she is dedicated to advancing technology and education in her field \

 

Professional Profile:

Education

Dr. Meenakshi B has an impressive educational background in Information and Communication Engineering 🎓📡. She holds both an M.E. and a Ph.D. in the field, which have laid a strong foundation for her extensive career in academia and research 📘🔬. Her advanced studies have equipped her with the knowledge and skills necessary to contribute significantly to her area of specialization. Throughout her education, Dr. Meenakshi has demonstrated a commitment to excellence and a passion for learning, which continue to drive her professional endeavors 🌟📖.

 

Professional Experience

Dr. Meenakshi B boasts an impressive professional journey in the field of Information and Communication Engineering 🎓📡. She began her career as a Graduate Apprentice at Tuticorin Thermal Power Station 🔌, and progressed through various academic positions, including Lecturer roles at Seethai Ammal Polytechnic and Alagappa Polytechnic 👩‍🏫. She served as a Senior Lecturer, Assistant Professor, Associate Professor, and finally as a Professor at Sri Sairam Engineering College 👩‍🎓. Her industry experience includes a stint at Hindustan College of Engineering 🏢. Dr. Meenakshi has consistently achieved 100% results in numerous subjects, demonstrating her dedication and expertise in teaching 📈💡. Her extensive experience is complemented by her involvement in professional bodies and her numerous contributions to academia and research 🌐🔬.

Research Interest

Dr. Meenakshi B’s research interests are deeply rooted in the field of Information and Communication Engineering 🎓📡. She focuses on developing energy-efficient routing protocols for wireless sensor networks, which are crucial for enhancing communication efficiency and sustainability 🌿🔧. Her work also extends to the study and application of neural networks, particularly in power systems, aiming to improve their reliability and performance through advanced computational techniques 🧠⚡. Additionally, Dr. Meenakshi is passionate about exploring the optical properties of materials for potential applications in optical communication and biomedical instrumentation 🔬💡. Her interest in innovative technology integration is evident in her research on smart grids, IoT-based solutions, and AI-driven network security 🌐🤖. Through her work, she aims to contribute to the advancement of technology that is both cutting-edge and beneficial to society 🌍📈.

Award and Honor

Dr. Meenakshi B has received numerous awards and honors throughout her distinguished career in Information and Communication Engineering 🎓📡. She has been recognized for achieving 100% results in various subjects, demonstrating her exceptional teaching abilities and dedication to student success 🏅📈. Her innovative projects have secured significant funding, including grants from DST-IEDC and the Tamil Nadu State Council for Science and Technology for her pioneering work in water desalination and waste management systems 🌿🔧. Dr. Meenakshi’s contributions to research and development have been acknowledged through multiple patents in areas such as IoT-based systems, AI-driven applications, and wireless sensor networks 📜🤖. She is also a recipient of numerous professional accolades, reflecting her commitment to advancing technology and education in her field 🌐📚.

 

Research Skills

Dr. Meenakshi B possesses a diverse and advanced skill set in research, particularly in Information and Communication Engineering 🎓📡. Her expertise includes the synthesis and application of complex engineering principles to solve real-world problems, such as energy-efficient wireless sensor networks and neural networks 💡🔬. She has a proven ability to publish high-quality research, with numerous contributions to national and international journals and conferences 📝🌍. Dr. Meenakshi excels in project management, having successfully secured and managed funded projects focused on innovative technologies like water desalination systems and waste disposal management 🌿🔧. Her proficiency in guiding and mentoring students and colleagues, combined with her hands-on experience in consultancy projects, underscores her capability to bridge the gap between theoretical research and practical application 👩‍🏫🤝.

Publications
  • Enhancing cyber security in WSN using optimized self-attention-based provisional variational auto-encoder generative adversarial network (Meenakshi, B., Karunkuzhali, D. Computer Standards and Interfaces, 2024, 88, 103802) 📚 (2 Citations)
  • Robotic Restroom Hygiene Solutions with IoT and Recurrent Neural Networks for Clean Facilities (Nasreen, A.K., Shenbagapriya, M., Seeni, S.K., … Meenakshi, B., Murugan, S. 7th International Conference on Inventive Computation Technologies, ICICT 2024, pp. 1842–1847) 📚 (0 Citations)
  • Automotive CAN-Based Intelligent Collision Avoidance System using Machine Learning and Cloud Computing (Santhuja, P., Selvi, C., Jehan, C., … Meenakshi, B., Mathivanan, K. Proceedings of the 2024 10th International Conference on Communication and Signal Processing, ICCSP 2024, pp. 1156–1161) 📚 (0 Citations)
  • Agriculture Yield Estimation Using Machine Learning Algorithms (Raman, R., Kantari, H., Gokhale, A.A., … Meenakshi, B., Srinivasan, S. 2024 International Conference on Automation and Computation, AUTOCOM 2024, pp. 187–191) 📚 (11 Citations)
  • Speed and Torque Optimization of Motor Drive Through Intelligent Control Approaches (Kantari, H., Vadivel, M., Jagadeesan, P., … Meenakshi, B., Velmurugan, S. 2024 International Conference on Automation and Computation, AUTOCOM 2024, pp. 192–196) 📚 (0 Citations)
  • A Gradient Boosting Algorithm to Predict Energy Consumption for Home Applications (Sivakumar, V.G., Arunfred, N., Anusha, N., … Meenakshi, B., Sujatha, S. 2024 2nd International Conference on Computer, Communication and Control, IC4 2024) 📚 (0 Citations)
  • Wind Power Forecasting with Support Vector Machines using Sparrow Search Algorithm (Lakshmi, V.V., Giriprasad, S., Vimal, S.P., … Meenakshi, B., Srinivasan, S. 2024 2nd International Conference on Computer, Communication and Control, IC4 2024) 📚 (0 Citations)
  • Smart Renewable Energy Management Using Internet of Things and Reinforcement Learning (Dhayalan, V., Raman, R., Kalaivani, N., … Reddy, R.S., Meenakshi, B. 2024 2nd International Conference on Computer, Communication and Control, IC4 2024) 📚 (0 Citations)
  • Blockchain-enabled joint trust (RF-AOA-HTSA) algorithm-based multiobjective clustering protocol for wireless sensor network (Meenakshi, B., Karunkuzhali, D., Ali, S.M. Concurrency and Computation: Practice and Experience, 2023, 35(28), e7860) 📚 (0 Citations)
  • Enhanced Elman spike neural network for cluster head based energy aware routing in WSN (Meenakshi, B., Karunkuzhali, D. Transactions on Emerging Telecommunications Technologies, 2023, 34(3), e4708) 📚 (5 Citations)