Md. Nahid Hasan | Computer Science | Best Researcher Awards

Mr. Md. Nahid Hasan | Computer Science | Best Researcher Awards

Mr. Md. Nahid Hasan, Dhaka International University, Bangladesh

Md. Nahid Hasan is a dedicated academic and researcher in Computer Science and Engineering, currently serving as a Lecturer at Dhaka International University. With a strong foundation in software development, machine learning, and data science, he has published several peer-reviewed articles in reputed journals and international conferences. He is known for blending advanced AI techniques with real-world challenges, particularly in health analytics, text classification, biosensors, and cybersecurity. Md. Hasan is pursuing his M.Sc. Engineering in CSE from BUET with a CGPA of 3.75 and previously graduated with distinction from Khulna University. His diverse research has garnered international attention, reflecting his deep curiosity, discipline, and passion for innovation. A former winner of the IEEE YESIST12 Innovation Challenge, he continues to contribute to both academia and industry with impactful research and teaching. Md. Hasan envisions a future driven by ethical AI and smart technologies that elevate human potential.

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Suitability Assessment for Research for Best Researcher Award: Md. Nahid Hasan

Md. Nahid Hasan demonstrates a strong profile for the Research for Best Researcher Award based on his academic background, research contributions, and professional engagement in the field of Computer Science & Engineering. Currently pursuing an M.Sc. in Computer Science & Engineering at Bangladesh University of Engineering and Technology (BUET), he has already established a solid foundation with a B.Sc. degree where he graduated with a commendable GPA of 3.87 and secured the 2nd position in his class.

His employment history highlights consistent academic involvement as a lecturer at reputed universities, including Dhaka International University and Daffodil International University, showcasing his dedication to both teaching and research simultaneously. This professional experience provides him with a practical platform to influence and contribute to academic development.

🎓 Education

Md. Nahid Hasan’s educational journey exemplifies academic excellence and dedication. He is currently pursuing his M.Sc. Engineering in Computer Science and Engineering from the prestigious Bangladesh University of Engineering and Technology (BUET), holding a CGPA of 3.75 with thesis remaining. His undergraduate studies were completed at Khulna University, where he graduated with a CGPA of 3.87 and secured the second position in his class. His strong foundation was built at Dinajpur Govt. College and Dinajpur Zilla School, where he achieved perfect GPAs of 5.00 in both HSC and SSC. Throughout his academic life, he has demonstrated exceptional analytical skills, logical reasoning, and innovative thinking. His curriculum has been enriched with practical programming, AI applications, and research projects, which paved the way for his contributions in machine learning, cybersecurity, and biosensor modeling. This educational background not only underpins his current research but also fuels his ambitions for advancing intelligent technologies.

💼 Professional Experience

Md. Nahid Hasan has steadily progressed through various academic roles, currently holding a Lecturer position in the Department of Computer Science and Engineering at Dhaka International University since January 2024. Prior to this, he served as a Lecturer at Daffodil International University (Jan 2023 – Jan 2024) and previously at Dhaka International University (Feb 2022 – Dec 2022). In these roles, he has taught core CSE subjects, mentored undergraduate research, and contributed to academic course development. His teaching philosophy centers around interactive learning, analytical thinking, and real-world application of computing principles. Outside the classroom, he is actively involved in research collaborations, interdisciplinary projects, and conference presentations. His industry-relevant insight and academic rigor allow him to bridge the gap between theoretical knowledge and emerging technologies. Through his academic appointments, Md. Hasan continues to inspire students, encourage innovation, and strengthen institutional research output in Bangladesh’s higher education landscape.

🏅 Awards and Recognition 

Md. Nahid Hasan’s academic journey is adorned with several accolades that reflect his brilliance and commitment. Notably, he was the Winner of the IEEE YESIST12 Innovation Challenge Track 2021, an internationally recognized competition that celebrates innovative technological solutions. He has also been a recipient of multiple merit-based scholarships throughout his undergraduate studies at Khulna University, a testament to his consistent academic performance and leadership potential. His research works have been accepted and presented at esteemed IEEE international conferences across Europe and Asia. With journal articles published in reputed outlets like Array and EAI Endorsed Transactions on IoT, he is quickly gaining recognition in global research circles. Md. Hasan’s contributions span across machine learning, bioinformatics, and cybersecurity—areas critical to the digital transformation of society. His awards not only highlight his technical abilities but also his potential to drive meaningful change through data-driven innovation.

🌍 Research Skills On Computer Science

Md. Nahid Hasan possesses a rich blend of research skills at the intersection of artificial intelligence, machine learning, and computational modeling. His expertise includes advanced statistical analysis, neural networks (ANN, LSTM, Bi-LSTM), and ensemble learning models, often applied in areas such as mental health prediction, biosensor simulation, natural language processing, and cybersecurity. He is proficient in PyTorch, Python, SQL, and C++, and utilizes LaTeX for scholarly writing. His research often involves building predictive models, performing comparative classifier analyses, and optimizing AI pipelines for complex data systems. He is also skilled in academic publishing, technical documentation, and collaborative research design. With hands-on experience in multiple IEEE conferences, Md. Hasan continues to refine his methodologies through peer feedback, interdisciplinary collaboration, and continual learning. His ability to translate real-world problems into algorithmic solutions exemplifies a future-ready research mindset grounded in ethical and impactful innovation.

📖  Publication Top Notes

  • Title: Computing Confinement Loss of Open-Channels Based PCF-SPR Sensor with ANN Approach
    Authors: N. Islam, M.S.I. Khan, M.N. Hasan, M.A. Yousuf
    Citation: 4
    Year: 2023

  • Title: Computing Optical Properties of Open–Channels Based Plasmonic Biosensor Employing Plasmonic Materials with ML Approach
    Authors: N. Islam, I.H. Shibly, M.M.S. Hasan, M.N. Hasan, M.A. Yousuf
    Citation: 4
    Year: 2023

  • Title: A Comparative Study on Machine Learning Classifiers for Cervical Cancer Prediction: A Predictive Analytic Approach
    Authors: K.M.M. Uddin, I.A. Sikder, M.N. Hasan
    Citation: 1
    Year: 2024

  • Title: An Ensemble Machine Learning-Based Approach for Detecting Malicious Websites Using URL Features
    Authors: K.M.M. Uddin, M.A. Islam, M.N. Hasan, K. Ahmad, M.A. Haque
    Citation: 1
    Year: 2023

  • Title: Stacked Ensemble Method: An Advanced Machine Learning Approach for Anomaly-based Intrusion Detection System
    Authors: A. Rahman, M.S.I. Khan, M.D.Z.A. Eidmum, P. Shaha, B. Muiz, N. Hasan, …
    Citation: — (citation not provided)
    Year: 2025

  • Title: Language Prediction of Twitch Streamers using Graph Convolutional Network
    Authors: M.N. Hasan, N. Saha, M.A. Rahman
    Citation: — (citation not provided)
    Year: 2025

  • Title: Artificial Neural Network-Assisted Confinement Loss Prediction of D-Shaped PCF-SPR Biosensor
    Authors: N. Islam, M.M.S. Hasan, M.N. Hasan, I.H. Shibly, M.A. Yousuf, M.Z. Uddin
    Citation: — (citation not provided)
    Year: 2024

  • Title: Credibility Analysis of Robot Speech Based on Bangla Language Dialect
    Authors: M.N. Hasan, R. Azim, S. Sharmin
    Citation: — (citation not provided)
    Year: 2024

  • Title: A Comparative Study on Machine Learning Classifiers for Early Diagnosis of Cervical Cancer
    Authors: I.A. Sikder, M.N. Hasan, R. Jahan, A. Mohamed, Y. Dirie
    Citation: — (citation not provided)
    Year: 2024

  • Title: Machine Learning Classification Approach for Refractive Index Prediction of D-Shape Plasmonic Biosensor
    Authors: N. Islam, M.N. Hasan, M.M.S. Hasan, I.H. Shibly, M.A. Yousuf, M.Z. Uddin
    Citation: — (citation not provided)
    Year: 2024

Anusha Sowbarnika Veluswamy | Network Security | Women Researcher Award

Dr. Anusha Sowbarnika Veluswamy | Network Security | Women Researcher Award

Dr. Anusha Sowbarnika Veluswamy, Susquehanna University, United States

Dr. V. Anusha Sowbarnika is an Assistant Professor at Susquehanna University, Pennsylvania, USA. With a robust background in information technology, she focuses on cryptography, network security, and AI. Having published several research papers, she specializes in guiding students in advanced computing areas, including data mining, computer architecture, and cyber forensics. Dr. Sowbarnika fosters a multicultural learning environment and integrates critical thinking into her teaching methods, aiming to inspire and motivate students. She has six years of teaching experience and has worked in both academic and administrative roles. Additionally, she has experience in the financial sector, having worked as a Relationship Banker at Clinton Savings Bank.

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Suitability for the Research for Women Researcher Award

V. Anusha Sowbarnika’s background and achievements make her an excellent candidate for the Research for Women Researcher Award. She has demonstrated a strong commitment to both academic excellence and mentorship, particularly in the field of computer science and information technology. As an Assistant Professor at Susquehanna University, she not only teaches undergraduate and graduate students in diverse areas such as Artificial Intelligence, Data Mining, and Cyber Forensics, but also plays a pivotal role in guiding students to develop essential skills for their academic and professional growth.

Her expertise in emerging topics like cryptography, network security, and cloud computing security highlights her ability to contribute to cutting-edge research in the information technology domain. Anusha’s research has been recognized through publications in both national and international journals and conferences, focusing on cryptographic algorithms, cluster analysis, and cloud computing. This indicates her substantial contribution to advancing knowledge in her field, which aligns well with the goals of the Research for Women Researcher Award.

Education

Dr. Anusha Sowbarnika holds a Ph.D. in Information and Communication Engineering from Anna University, India. She completed her Master of Engineering in Computer Science and Engineering from Karpagam University, Coimbatore, India. Her academic journey began with a Bachelor of Engineering in Information Technology from Avinashilingam University for Women, Coimbatore. Her educational background provides a solid foundation for her research in network security, cryptography, and computing. She also holds certifications in teaching, including the ISTQB Certified Tester Foundation Level and certificates in teaching and learning from “Mission 10X” and “Seed”.

Professional Experience

Dr. Sowbarnika's professional career includes roles in academia and banking. At Susquehanna University, she designs and delivers high-quality instruction in computer science, guiding both undergraduate and graduate students. Her expertise spans Artificial Intelligence, Network Security, Data Mining, and Cryptography. Dr. Sowbarnika’s administrative experience includes curriculum design, assessment, and mentoring students. Before her current role, she was an Assistant Professor at Info Institute of Engineering, Kovilpalayam, and GKM College of Engineering & Technology in India. Additionally, she worked as a Relationship Banker at Clinton Savings Bank, providing excellent customer service and facilitating banking operations.

Awards and Recognition

Dr. Sowbarnika has been recognized for her academic excellence and contributions to research in computer science. She has published numerous papers in prestigious national and international journals and conferences, focusing on cryptographic algorithms, network security, and cloud computing. She has received awards for her role in enhancing student learning and engagement. Additionally, Dr. Sowbarnika has completed multiple Faculty Development Programs (FDPs) and workshops on topics such as Big Data Analytics, Cloud Computing, and Data Mining, underscoring her commitment to professional growth.

Research Skills On Network Security

Dr. Sowbarnika’s research expertise includes cryptography, network security, cloud computing security, and cyber forensics. Her work focuses on advanced cryptographic algorithms, data security, and the application of AI in enhancing network security. She has extensive experience in data mining, Python programming, and the development of secure systems in computing. Dr. Sowbarnika is skilled at guiding research projects, collaborating on academic research initiatives, and mentoring students in their research endeavors. Her interdisciplinary approach to solving complex problems in IT makes her a valuable asset to the field.

  Publication Top Notes

  1. Title: The security‐based optimization algorithm for enhancing the energy efficiency of wireless sensor networks
    Authors: V. Anusha Sowbarnika, M. Balasubramani, K. Kavitha
    Journal: International Journal of Communication Systems, 36(16), e5584
    Citations: 3
    Year: 2023

  2. Title: GPU acceleration using CUDA framework
    Authors: P.P. Nambiar, V. Saveetha, S. Sophia, V.A. Sowbarnika
    Journal: International Journal of Innovative Research in Computer and Communication Engineering
    Citations: 3
    Year: 2014

  3. Title: Enhanced security measures in wireless sensor networks: Leveraging random forest and k-means clustering for node replication attack detection
    Authors: V. Anusha Sowbarnika, R. Lokeshkumar, T. Gopalakrishnan, S. Priya, et al.
    Journal: International Journal of Computing and Digital Systems, 16(1), 1–19
    Citations: 2
    Year: 2024

  4. Title: Modeling of metaheuristic-based dual cluster head selection with routing protocol for energy-efficient wireless sensor networks
    Authors: P.K.S.S. Maddikera Krishna Reddy, Anusha Sowbarnika Veluswamy, S. Selvanayaki, C. [others not listed]
    Journal: Soft Computing
    Year: 2025

  5. Title: Improving Security and Communication Protocols in Smart Grid using Deep Learning to Ensure Data Privacy
    Authors: Anusha Sowbarnika Veluswamy, S. Thanga Ramya, D. Praveena, Issac [others not listed]
    Conference: International Conference on Optimization Techniques in the Field of ...
    Year: 2025

  6. Title: Natural Language Processing for Sentiment Analysis in Social Media Techniques and Case Studies
    Authors: A.M.M.V. Anusha Sowbarnika Veluswamy, A. Nagamani, M. SilpaRaj, D. Yobu
    Journal: ITM Web of Conferences, 76, 05004
    Year: 2025

  7. Title: Enhancing the Security and Energy Efficiency by Integrating Grid Based Adversarial Clustering and Ant Colony Optimization (ACO) in Wireless Sensor Networks
    Authors: V.A. Sowbarnika, M. Balasubramani, K. Kavitha
    Journal: International Journal of Advanced Science and Technology, 29(3), 11750–11759
    Year: 2020

  8. Title: Curtailing the Energy Consumption of Wireless Sensor Networks by Genetic Algorithm
    Authors: A.S. Veluswamy, M. Balasubramani, K. Kavitha
    Journal: International Journal of Analytical and Experimental Modal Analysis, 11
    Year: 2019

  9. Title: Evaluating the effects of Cryptographic Algorithms on Different sets of Data
    Authors: A.S. Veluswamy, M. Balasubramani, K. Kavitha
    Conference: SSRG International Journal of Computer Science and Engineering – (ICET’17)
    Year: 2017

  10. Title: Twitter Based Earthquake Alert System
    Authors: N.V. Anitha R., S. Selvakumar, V. Anusha Sowbarnika
    Journal: International Journal of Innovative Research in Computer and Communication Engineering
    Year: 2014

 

AparnaRajesh Atmakuri | Cybersecurity | Women Researcher Award

Dr. AparnaRajesh Atmakuri | Cybersecurity | Women Researcher Award

Dr. AparnaRajesh Atmakuri, Keshav memorial engineering College, India

Dr. AparnaRajesh Atmakuri, also known as Aparna Manikonda, is an esteemed academician and researcher with over 19 years of teaching and 12+ years of research experience. She has made remarkable strides in cybersecurity, cloud computing, IoT, and data analytics. Currently serving as Associate Professor at Centurion University of Technology and Management, she has also held influential positions at institutions like Aryan Institute of Engineering and GNITC. With a strong foundation in Computer Science and Engineering, her work reflects a blend of innovation, dedication, and leadership. A prolific author, Dr. Aparna has published 32+ journal papers, authored multiple books, and holds patents on advanced tech innovations. Known for her contributions to research and curriculum development, she is the recipient of the Best Researcher and Inspiring Professor Awards. Her commitment to securing digital ecosystems and mentoring future technologists continues to influence academia and industry alike.

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Suitability Summary for the Women researcher Award

Dr. Aparna Rajesh Atmakuri, also known as Aparna Manikonda, is an exceptionally qualified candidate for the Research for Women Researcher Award, demonstrating a well-rounded and impactful career in academia and research over nearly two decades. With over 19 years of teaching experience and more than 12 years in active research, Dr. Aparna has consistently shown commitment to innovation, scholarly excellence, and educational leadership. Her roles, including HOD and Associate Professor across top-tier institutions in India, reflect a strong academic foundation and influential leadership capabilities.

Dr. Aparna’s academic credentials are fortified by a Ph.D. in Computer Science and Engineering from VTU, multiple certifications in programming and pedagogy (such as Sun Java and Mission10x), and a diverse portfolio of technical subjects taught at both undergraduate and postgraduate levels. Her research interests span critical and modern technological domains like cybersecurity, blockchain, IoT, cloud computing, and data mining, placing her work at the heart of contemporary computer science challenges. Notably, she has published over 32 research papers in reputed international journals and conferences (including SCI and Scopus indexed), authored three technical books, and delivered numerous talks and chaired sessions in international forums.

Education

Dr. AparnaRajesh holds a Ph.D. in Computer Science and Engineering from VTU, Belagavi (2017–2023), where her research focused on cybersecurity and predictive systems. She earned her M.Tech with Honors in Computer Science from Biju Patnaik University of Technology (2008–2010) with a commendable CGPA of 9.04. Her academic journey began with a B.E. in Information Technology from the same university (2002–2006), where she secured the 7th rank. Alongside formal education, she has attained globally recognized certifications such as Sun Certified Java Programmer 1.5, Oracle Certified Associate/Professional (OCA/OCP), and Mission10X certification from Wipro. Her educational foundation has empowered her to excel in diverse teaching and research roles, equipping her with technical, analytical, and instructional prowess. Dr. Aparna’s blend of strong academic credentials and continued professional development positions her as a thought leader in emerging domains like blockchain, IoT, and cybersecurity.

Professional Experience

With a dynamic career spanning over 19 years, Dr. Aparna has held influential teaching and leadership roles at renowned institutions. Since July 2024, she has served as Associate Professor at Centurion University of Technology and Management. Prior to that, she was HOD and Associate Professor at Aryan Institute of Engineering and Technology (2019–2024), shaping academic policy and research culture. From 2017–2019, she was with GNITC, Hyderabad; and between 2014–2017, she served at CMRIT and BNMIT, Bangalore. Her earlier tenure at NMIT and NIST saw her playing pivotal roles in government-funded research projects. She has coordinated NBA and NAAC accreditations, supervised student projects, organized conferences, and delivered technical talks. Known for her visionary approach, Dr. Aparna blends deep academic insights with practical research implementations, contributing significantly to institution-building and tech-forward curricula.

Awards and Recognition

Dr. Aparna has earned numerous accolades for her academic and research excellence. In 2024, she was honored with the Inspiring Professor Award by Inspiring National Level Awards and the Best Researcher Award by HEAA for her groundbreaking work in cybersecurity and IoT. Her exceptional teaching at NIST earned her the Best Teacher Award for three consecutive years with a stellar student feedback score of 9.8. She was recognized with a publication honorarium and achieved branch-topper status in her M.Tech. program. Her academic journey is also marked by a 7th rank in her undergraduate degree. A prolific author, she has published 32+ international journal papers and 3 patents, besides authoring multiple technical books. She has chaired sessions at global conferences and delivered expert talks. Dr. Aparna’s contributions are a testament to her passion for education, mentorship, and disruptive technological innovation.

Research Skills On Cybersecurity

Dr. AparnaRajesh is a multi-disciplinary researcher skilled in cybersecurity, blockchain, cloud computing, and IoT. Her core expertise lies in developing secure and scalable architectures using advanced machine learning and encryption algorithms. She has actively contributed to DRDO-funded projects, including video summarization and real-time tracking systems, showcasing her hands-on research in defense applications. Her patents demonstrate deep proficiency in AI-based emotion detection, smart public transport, and IoT security. She excels in data mining, digital image processing, and network analysis. Her skill set includes formulating hybrid algorithms for energy-efficient cloud resource management and predictive cyber-attack models using Generative AI. These capabilities are complemented by her experience with industry-standard simulation tools, research publishing, and guiding postgraduate students. Her practical insights into both hardware and software components of secure systems make her a valuable asset to academic and R&D ecosystems.

  Publication Top Notes

  • Title: An efficient approach towards robust routing in MANET
    Authors: M. Aparna, M. Reza, P. Sahu, S. Das
    Citation: 2012 International Conference on Communication Systems and Network Technologies
    Year: 2012

  • Title: An adaptive load balancing strategy in cloud computing based on Map Reduce
    Authors: N. Sowmya, M. Aparna, P. Tijare, N. Nalini
    Citation: 2015 1st International Conference on Next Generation Computing Technologies
    Year: 2015

  • Title: 3-phase leader election algorithm for distributed systems
    Authors: P. Chaparala, A. R. Atmakuri, S. S. S. Rao
    Citation: 2019 3rd International Conference on Computing Methodologies and Communication
    Year: 2019

  • Title: Fine grained security in cloud with cryptographic access control
    Authors: A. Manikonda, N. Nalini
    Citation: 2021 International Conference on Advance Computing and Innovative Technologies in Engineering
    Year: 2021

  • Title: A new method for controlling and maintaining topology in wireless sensor networks
    Authors: A. Zabi, T. Yousuf, A. Manikonda
    Citation: International Journal of Computer Networks & Communications, Volume 6, Issue 4, Page 91
    Year: 2014

  • Title: A-ZHLS: adaptive ZHLS routing protocol for heterogeneous mobile adhoc networks
    Authors: M. V. Narayana, A. Atmakuri
    Citation: International Journal of Engineering & Technology, Volume 7, Issue 3, Pages 1626–1630
    Year: 2018

  • Title: Adaptive enhancement of underwater images
    Authors: J. Majumdar, A. Manikonda, G. M. Venkatesh
    Citation: Proceedings of the Fourth International Conference on Signal and Image Processing
    Year: 2013

  • Title: Energy Efficiency of Wireless Sensor Network by Topology Control Using MEMSIC
    Authors: M. Aparna, S. Behera, M. Reza, R. Jena, R. Atmakuri
    Citation: 2012 International Conference on Communication Systems and Network Technologies
    Year: 2012

  • Title: Throughput analysis by varying the network size in mobile ad hoc network
    Authors: M. Aparna, M. Reza
    Citation: 2011 International Conference on Computational Intelligence and Communication Networks
    Year: 2011

  • Title: A novel access control for cloud services using trust based design
    Authors: M. Aparna, N. Nalini
    Citation: International Conference on Inventive Computation Technologies, Pages 702–710
    Year: 2019

Yukun Shi | Computer Science | Best Scholar Award

Assoc. Prof. Dr. Yukun Shi | Computer Science | Best Scholar Award

Assoc. Prof. Dr. Yukun Shi, Beijing University of Chemical Technology, China

Dr. Yukun Shi is an accomplished researcher and Associate Professor at the Department of Information Science and Technology, Beijing University of Chemical Technology. He specializes in multi-agent systems, control system network attacks, and distributed estimation. Dr. Shi earned his Ph.D. in Control Science and Engineering from Beijing University of Chemical Technology in 2022. His academic journey includes a one-year research visit to the University of Victoria, Canada, in 2021. His contributions to the field are significant, particularly in advancing secure state estimation and consensus control. He has published extensively in top-tier journals, addressing challenges in network security and distributed control. With a strong background in system modeling and cybersecurity, Dr. Shi continues to drive innovations in multi-agent collaboration and resilience against malicious attacks. His research not only contributes to theoretical advancements but also has practical implications for industrial and technological applications worldwide.

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Suitability for the Research for Best Scholar Award – Yukun Shi

Dr. Yukun Shi, an Associate Professor at the Beijing University of Chemical Technology, has demonstrated remarkable academic and research excellence in the field of control science and engineering. His expertise spans critical areas such as multi-agent systems, control system network attacks, distributed estimation, and consensus control, making his contributions highly relevant to modern automation and cybersecurity challenges. His work is particularly notable in the area of secure state estimation, where he has investigated the robustness of networked control systems against malicious sensor attacks, an emerging concern in industrial and cyber-physical systems.

Dr. Shi’s research output includes several publications in prestigious IEEE journals, such as IEEE Transactions on Automation Science and Engineering and IEEE Transactions on Control of Network Systems, highlighting his ability to contribute cutting-edge advancements in his field. His scholarly work is well-cited, reflecting both its impact and recognition within the scientific community. Additionally, his international exposure, including a research visit at the University of Victoria, Canada, underscores his global perspective and collaborative research approach.

🎓 Education 

Dr. Yukun Shi pursued his Ph.D. in Control Science and Engineering at Beijing University of Chemical Technology, graduating in 2022. His doctoral research focused on secure state estimation in multi-agent systems under adversarial conditions, bridging control theory with cybersecurity. As part of his academic development, he undertook a one-year research visit to the University of Victoria, Canada, in 2021, where he collaborated on cutting-edge projects related to network security and control systems. His education provided him with a strong foundation in distributed control, estimation algorithms, and robust filtering techniques. Throughout his studies, Dr. Shi honed his expertise in tackling cyber threats to industrial control systems, laying the groundwork for his future research in resilient multi-agent networks. His academic journey is marked by rigorous training, innovative problem-solving, and contributions to the field of control and automation engineering.

💼 Professional Experience

Dr. Yukun Shi currently serves as an Associate Professor at the Department of Information Science and Technology, Beijing University of Chemical Technology. With a research focus on multi-agent systems, network security, and distributed estimation, he has made significant contributions to securing cyber-physical systems. His professional journey includes leading research projects on sensor attacks, consensus control, and fault-tolerant filtering in distributed networks. Dr. Shi actively collaborates with international institutions to develop advanced methodologies for improving the resilience of control systems against malicious threats. His role extends beyond research, encompassing mentorship, curriculum development, and industry partnerships. He is a sought-after speaker at academic conferences and has peer-reviewed numerous articles in high-impact journals. His dedication to cybersecurity and control engineering has positioned him as a thought leader in the field, driving innovation and practical solutions to safeguard modern industrial and technological infrastructures.

🏅 Awards and Recognition 

Dr. Yukun Shi has received multiple accolades for his pioneering work in control systems and cybersecurity. He has been recognized for his contributions to secure multi-agent systems and networked control security. His research papers have been published in high-impact journals, earning him best paper awards at leading automation and control conferences. Dr. Shi has also been a recipient of prestigious research grants that support his work in developing robust estimation algorithms against cyber threats. His outstanding contributions have been acknowledged by industry associations, positioning him as a key figure in distributed system security. His work has not only influenced academia but also guided practical implementations in industrial automation and cybersecurity frameworks. Additionally, Dr. Shi has served as a reviewer for top-tier journals, further highlighting his expertise and influence in the scientific community. His relentless pursuit of excellence continues to shape the future of secure control systems.

🌍 Research Skills On Computer Science

Dr. Yukun Shi possesses a robust research skill set centered around multi-agent systems, control system security, and distributed estimation. His expertise includes developing secure state estimation techniques to mitigate network attacks in cyber-physical systems. He specializes in designing fault-tolerant control algorithms that enhance the resilience of distributed networks. His research also encompasses consensus control strategies to improve synchronization in multi-agent environments. Dr. Shi is proficient in advanced filtering techniques, such as Kalman filtering and observer design, to ensure accurate system monitoring despite adversarial interference. He actively applies mathematical modeling and optimization methods to enhance decision-making in complex systems. His work in secure control frameworks has broad applications in autonomous systems, industrial automation, and networked infrastructures. With a keen focus on practical implementation, Dr. Shi’s research continues to bridge theoretical advancements with real-world security challenges, contributing to the evolution of resilient cyber-physical networks.

📖 Publication Top Notes

  • Title: Optimal Output-Feedback Controller Design Using Adaptive Dynamic Programming: A Permanent Magnet Synchronous Motor Application
    • Authors: Zhongyang Wang, Huiru Ye, Youqing Wang, Yukun Shi, Li Liang
    • Citation: IEEE Transactions on Circuits and Systems II: Express Briefs
    • Year: 2025
  • Title: Distributed Filter Under Homologous Sensor Attack and Its Application in GPS Meaconing Attack
    • Authors: Yukun Shi, Wenjing He, Li Liang, Youqing Wang
    • Citation: IEEE Transactions on Automation Science and Engineering
    • Year: 2024
  • Title: Event-triggered distributed secure state estimation for homologous sensor attacks
    • Authors: Yukun Shi, Haixin Ma, Jianyong Tuo, Youqing Wang
    • Citation: ISA Transactions
    • Year: 2023
  • Title: Distributed Secure State Estimation of Multi-Agent Systems Under Homologous Sensor Attacks
    • Authors: Yukun Shi, Youqing Wang, Jianyong Tuo
    • Citation: IEEE/CAA Journal of Automatica Sinica
    • Year: 2023
  • Title: Online Secure State Estimation of Multiagent Systems Using Average Consensus
    • Authors: Yukun Shi, Youqing Wang
    • Citation: IEEE Transactions on Systems, Man, and Cybernetics: Systems
    • Year: 2022
  • Title: Asymptotically Stable Filter for MVU Estimation of States and Homologous Unknown Inputs in Heterogeneous Multiagent Systems
    • Authors: Yukun Shi, Changqing Liu, Youqing Wang
    • Citation: IEEE Transactions on Automation Science and Engineering
    • Year: 2022
  • Title: Secure State Estimation of Multiagent Systems With Homologous Attacks Using Average Consensus
    • Authors: Yukun Shi, Changqing Liu, Youqing Wang
    • Citation: IEEE Transactions on Control of Network Systems
    • Year: 2021

Sai Venkatesh Chilukoti | Computer Science | Best Researcher Award

Mr. Sai Venkatesh Chilukoti | Computer Science | Best Researcher Award

Mr. Sai Venkatesh Chilukoti, University of Louisiana at Lafayette, United States

Sai Venkatesh Chilukoti is a dedicated researcher in Computer Engineering, currently pursuing a Ph.D. at the University of Louisiana at Lafayette under Dr. Xiali Hei. With a stellar academic record and a CGPA of 4.0, he specializes in Deep Learning, Network Security, and Cyber-Physical Systems. His research interests span Federated Learning, Differential Privacy, and Machine Learning applications in healthcare and security. Sai Venkatesh has contributed to multiple peer-reviewed journals and conferences, focusing on privacy-preserving AI and identity recognition. As a Research Assistant in the Wireless Embedded Device Security (WEDS) Lab, he has worked on cutting-edge projects integrating AI, privacy-enhancing techniques, and embedded security. With experience as a Teaching Assistant, he mentors students in Neural Networks, Python, and AI-related fields. His passion lies in translating research into real-world applications, particularly in medical imaging and cybersecurity. Sai is fluent in English, Hindi, and Telugu, and has strong technical skills in Python, PyTorch, and TensorFlow.

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Suitability for the Research for Best Researcher Award – Sai Venkatesh Chilukoti

Sai Venkatesh Chilukoti demonstrates an impressive academic and research portfolio, making him a strong contender for the Research for Best Researcher Award. Currently pursuing a Ph.D. in Computer Engineering at the University of Louisiana at Lafayette with a perfect 4.0/4.0 CGPA, he has developed expertise in deep learning, distributed computing, network security, and cyber-physical systems. His academic credentials are further strengthened by a solid foundation in electronics and communication engineering at the undergraduate level.

His research contributions are notable, particularly in privacy-preserving deep learning, federated learning, and medical AI applications. His work on diabetic retinopathy classification, gastrointestinal cancer prediction, and differential privacy models for healthcare data showcases both technical depth and real-world impact. His involvement in cutting-edge machine learning techniques, including LSTMs, Transformers, and convolutional networks, highlights his ability to innovate within the field. Furthermore, his research assistantship in Wireless Embedded Device Security (WEDS) Lab and role as a teaching assistant demonstrate both research rigor and mentorship capabilities.

🎓 Education 

Sai Venkatesh Chilukoti is currently pursuing a Ph.D. in Computer Engineering at the University of Louisiana at Lafayette (2021-2025, expected), under the supervision of Dr. Xiali Hei, with a perfect CGPA of 4.0. His coursework includes Deep Learning, Network Security, Distributed Computing, and Cyber-Physical Systems. His research focuses on privacy-preserving AI, federated learning, and deep learning model optimization.

He completed his B.Tech. in Electronics and Communication Engineering at Velagapudi Ramakrishna Siddhartha Engineering College (2017-2021), earning a CGPA of 8.53/10. His undergraduate studies encompassed AI, Python, Artificial Neural Networks, and Digital Signal Processing.

Throughout his education, Sai has actively engaged in research projects, including identity recognition using mmWave radar sensors, privacy-aware medical imaging, and deep learning applications in cybersecurity. His academic journey reflects a strong foundation in computational intelligence and a commitment to solving real-world challenges through innovative AI techniques.

💼 Professional Experience

Sai Venkatesh Chilukoti has extensive research and teaching experience, specializing in Deep Learning, Cybersecurity, and Federated Learning. As a Research Assistant at the Wireless Embedded Device Security (WEDS) Lab (2021-present), he has worked on privacy-preserving AI models, security solutions for embedded devices, and deep learning-based medical imaging applications. His work includes designing federated learning frameworks for decentralized AI and developing privacy-aware deep learning techniques.

As a Teaching Assistant for Neural Networks (2024-present), Sai mentors students in probability, calculus, and AI programming using PyTorch and Scikit-learn.

He has led numerous projects, such as statistical analysis of COVID-19 data, AI-driven financial forecasting, and deep learning applications in 3D printing quality control. His expertise extends to programming in Python, C, SQL, and MATLAB, along with experience in cloud computing and AI model deployment. He has also reviewed papers for IEEE Access and other reputed journals.

🏅 Awards and Recognition 

Sai Venkatesh Chilukoti has been recognized for his outstanding contributions to AI research, deep learning, and cybersecurity. He has received multiple conference paper acceptances, including at the Hawai’i International Conference on System Sciences (HICSS-56) and CHSN2021. His work on privacy-preserving AI has been published in high-impact journals like BMC Medical Informatics and Decision Making and Electronic Commerce Research and Applications.

He has also earned certifications in Deep Learning Specialization (Coursera), AI for Everyone (deeplearning.ai), and Applied Machine Learning in Python (University of Michigan). His research in Federated Learning has gained attention for its innovative approach to privacy protection in healthcare AI models. Additionally, Sai has contributed as a reviewer for IEEE Access and Euro S&P, demonstrating his expertise in computer security and AI ethics. His contributions to machine learning, cybersecurity, and privacy-aware AI continue to impact both academic and industrial domains.

🌍 Research Skills On Computer Science

Sai Venkatesh Chilukoti specializes in Federated Learning, Differential Privacy, and Deep Learning model optimization. His expertise spans AI-driven cybersecurity, identity recognition using mmWave radar sensors, and privacy-preserving medical imaging. He has worked extensively with machine learning frameworks such as PyTorch, TensorFlow, and Scikit-learn.

Sai has developed AI models for secure collaborative learning, utilizing techniques like DP-SGD for privacy preservation. His research also explores transformer-based architectures, convolutional networks, and ensemble learning methods to enhance predictive performance. He has integrated advanced optimization techniques, including adaptive gradient clipping and label smoothing, into deep learning pipelines.

He has hands-on experience with federated learning platforms like Flower and privacy-preserving AI models in medical data analysis. His work in statistical modeling, computer vision, and neural networks has contributed to breakthroughs in security and healthcare AI. Sai’s research aims to advance AI applications while maintaining ethical and privacy standards.

📖 Publication Top Notes

  • A reliable diabetic retinopathy grading via transfer learning and ensemble learning with quadratic weighted kappa metric
      • Authors: Sai Venkatesh Chilukoti, Liqun Shan, Vijay Srinivas Tida, Anthony S. Maida, Xiali Hei
      • Journal: BMC Medical Informatics and Decision Making
      • Volume: 24, Issue 1
      • Article Number: 37
      • Year: 2024
  • Privacy-Preserving Deep Learning Model for Covid-19 Disease Detection
      • Authors: Vijay Srinivas Tida, Sai Venkatesh Chilukoti, Sonya H. Y. Hsu, Xiali Hei
      • Conference: 56th Hawaii International Conference on System Sciences
      • Year: 2023
  • Single Image Multi-Scale Enhancement for Rock Micro-CT Super-Resolution Using Residual U-Net
    • Authors: Liqun Shan, Chengqian Liu, Yanchang Liu, Yazhou Tu, Sai Venkatesh Chilukoti
    • Journal: Applied Computing and Geosciences
    • Year: 2024
  • Kernel-Segregated Transpose Convolution Operation
    • Authors: Vijay Srinivas Tida, Sai Venkatesh Chilukoti, Sonya H. Y. Hsu
    • Conference: 56th Hawaii International Conference on System Sciences
    • Year: 2023
  • Modified ResNet Model for MSI and MSS Classification of Gastrointestinal Cancer
    • Authors: Sai Venkatesh Chilukoti, C. Meriga, M. Geethika, T. Lakshmi Gayatri, V. Aruna
    • Book Title: High Performance Computing and Networking: Select Proceedings of CHSN 2021
    • Year: 2022
  • Enhancing Unsupervised Rock CT Image Super-Resolution with Non-Local Attention
    • Authors: Chengqian Liu, Yanchang Liu, Liqun Shan, Sai Venkatesh Chilukoti, Xiali Hei
    • Journal: Geoenergy Science and Engineering
    • Volume: 238
    • Article Number: 212912
    • Year: 2024
  • Method for Performing Transpose Convolution Operations in a Neural Network
    • Inventors: Vijay Srinivas Tida, Sonya Hsu, Xiali Hei, Sai Venkatesh Chilukoti, Yazhou Tu
    • Patent Application: US Patent App. 18/744,260
    • Year: 2024
  • IdentityKD: Identity-wise Cross-modal Knowledge Distillation for Person Recognition via mmWave Radar Sensors
    • Authors: Liqun Shan, Rujun Zhang, Sai Venkatesh Chilukoti, Xingli Zhang, Insup Lee
    • Conference: ACM Multimedia Asia
    • Year: 2024
  • Facebook Report on Privacy of fNIRS Data
    • Authors: M. I. Hossen, Sai Venkatesh Chilukoti, Liqun Shan, Vijay Srinivas Tida, Xiali Hei
    • Preprint: arXiv preprint arXiv:2401.00973
    • Year: 2024

Chaitanya Rahalkar | Cybersecurity | Excellence in Innovation

Mr. Chaitanya Rahalkar | Cybersecurity | Excellence in Innovation

👤 Mr. Chaitanya Rahalkar, Georgia Institute of Technology, United States

Chaitanya Rahalkar is an accomplished cybersecurity professional and entrepreneur, renowned for his expertise in security engineering and advanced system architecture. He holds a Master of Science in Cybersecurity from Georgia Institute of Technology and a Bachelor’s degree in Computer Engineering from Savitribai Phule Pune University. As the CEO and Founder of OmniChat AI, he has architected cutting-edge multimodal AI platforms that integrate text, audio, image, and video processing. His professional journey includes pivotal roles at prestigious organizations such as Block Inc. (formerly Square), Meta (formerly Facebook), and Praetorian Security. Chaitanya has contributed to major security projects, including penetration tests, vulnerability assessments, and the development of cloud-native security systems. His academic research has been published in notable journals, with works focusing on secure systems, blockchain, and privacy-preserving technologies. Chaitanya is passionate about advancing cybersecurity solutions to address emerging digital threats.

Professional Profile

Scopus 

Google Scholar

🌟 Summary of Suitability for the Award

Chaitanya Rahalkar stands out as an exemplary candidate for the Research for Excellence in Innovation award, thanks to his profound contributions to both cybersecurity and the broader tech industry. With an academic background in cybersecurity, including a Master’s degree from Georgia Institute of Technology, he has developed expertise in numerous technical fields such as cloud services, web frameworks, security engineering tools, and advanced cybersecurity methodologies. His innovative work is evident through both his academic research and professional endeavors, where he has made significant strides in enhancing security, optimizing cloud infrastructure, and developing cutting-edge technologies.

In his role as CEO and Founder of OmniChat AI, Chaitanya spearheaded the development of a multimodal LLM API platform, successfully integrating text, image, video, and audio processing. This platform simplifies developer implementation, a breakthrough in multimodal AI application development. His leadership resulted in strategic partnerships with 20+ companies and a notable increase in monthly recurring revenue.

🎓 Education

Chaitanya Rahalkar earned a Master of Science in Cybersecurity from the prestigious Georgia Institute of Technology, Atlanta, where he maintained a perfect GPA of 4.0/4.0. During his time at Georgia Tech, he specialized in network security, cryptography, and secure computer systems, while also serving as a teaching assistant for courses like Applied Cryptography. Prior to that, he completed a Bachelor of Engineering in Computer Engineering from Savitribai Phule Pune University, Pune, with an exceptional GPA of 9.6/10. His academic foundation has equipped him with a deep understanding of security engineering, blockchain technologies, and cryptographic methods. His educational pursuits reflect a strong commitment to both theoretical knowledge and practical application in the cybersecurity domain. These qualifications, paired with his research contributions, have made him a respected figure in the cybersecurity field.

💼 Professional Experience

Chaitanya Rahalkar has a diverse and impactful professional background in cybersecurity and software engineering. As the CEO and Founder of OmniChat AI, he designed a multimodal LLM API platform, integrating AI for text, image, video, and audio processing, which dramatically simplifies implementation for developers. His role at Block Inc. (formerly Square) as a Software Security Engineer involved building cloud-native security systems and optimizing security pipelines at the enterprise level. At Praetorian Security, Chaitanya led over 100 security audits and penetration tests for clients like Nordstrom, Amazon, and Salesforce. His efforts helped identify over 200 security vulnerabilities and enhanced security protocols across various platforms. Chaitanya also contributed to Meta (formerly Facebook), where he developed fuzzing harnesses and identified vulnerabilities within the WhatsApp Payment Engine. His expertise has made him a key player in ensuring robust security across platforms and systems.

🏅 Awards and Recognition

Chaitanya Rahalkar has received significant recognition for his contributions to the cybersecurity field. He is an AWS SAA Certified Cloud Practitioner and an OSCP candidate, both of which reflect his deep understanding of cloud security and offensive security practices. His academic work has been published in prominent journals, showcasing his thought leadership in cybersecurity, privacy preservation, and blockchain technologies. Notably, his research on “Content Moderation Schemes in End-to-End Encrypted Systems” and “Privacy-Preserving Techniques in Bitcoin” has garnered attention in the cybersecurity community. Chaitanya’s innovative approach to security engineering has earned him a reputation for pioneering security solutions in both academia and industry. His work has helped shape security strategies for major organizations, and his contributions to the field continue to influence the development of secure systems and ethical hacking practices.

🌍 Research Skills On Cybersecurity

Chaitanya Rahalkar possesses advanced research skills in cybersecurity, with a particular focus on system security, vulnerability assessments, and cryptographic techniques. His experience spans various research domains, including blockchain security, privacy-preserving technologies, and penetration testing. During his research tenure at the Center for Police Research (India), Chaitanya developed a proof of concept for an automated WiFi security analyzer, contributing to ethical hacking efforts for law enforcement. At Pune Institute of Computer Technology, he studied side-channel attacks targeting virtualized operating systems and contributed to the development of a meta-classifier-based model for attack detection. His published work, including papers on blockchain and cryptography, reflects his proficiency in cutting-edge research methodologies. Chaitanya’s ability to bridge theoretical knowledge with practical application enables him to tackle complex cybersecurity challenges and deliver impactful solutions that enhance the security landscape.

📖 Publication Top Notes

  • Content addressed P2P file system for the web with blockchain-based meta-data integrity
    Authors: C. Rahalkar, D. Gujar
    Citation: International Conference on Advances in Computing, Communication and …
    Year: 2019
  • Poster: Using generative adversarial networks for secure pseudorandom number generation
    Authors: R. Oak, C. Rahalkar, D. Gujar
    Citation: Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications …
    Year: 2019
  • A Secure Password Manager
    Authors: C. Rahalkar, D. Gujar
    Citation: International Journal of Computer Applications 178 (44), 5-9
    Year: 2019
  • A Diamond Model Analysis on Twitter’s Biggest Hack
    Authors: C. Rahalkar
    Citation: arXiv preprint arXiv:2306.15878
    Year: 2023
  • Automated Fuzzing Harness Generation for Library APIs and Binary Protocol Parsers
    Authors: C. Rahalkar
    Citation: arXiv preprint arXiv:2306.15596
    Year: 2023
  • SoK: Content Moderation Schemes in End-to-End Encrypted Systems
    Authors: C. Rahalkar, A. Virgaonkar
    Citation: arXiv preprint arXiv:2208.11147
    Year: 2022
  • Designing a Secure Device-to-Device File Transfer Mechanism
    Authors: C. Rahalkar, A. Virgaonkar
    Citation: arXiv preprint arXiv:2411.13827
    Year: 2024
  • Analyzing Trends in Tor
    Authors: C. Rahalkar, A. Virgaonkar, K. Varadan
    Citation: arXiv preprint arXiv:2208.11149
    Year: 2022
  • Summarizing and Analyzing the Privacy-Preserving Techniques in Bitcoin and other Cryptocurrencies
    Authors: C. Rahalkar, A. Virgaonkar
    Citation: arXiv preprint arXiv:2109.07634
    Year: 2021
  • End-To-End Lung Cancer Diagnosis On Computed Tomography Scans Using 3D CNN And Explainable AI
    Authors: C. Rahalkar, A. Virgaonkar, D. Gujar, S. Patkar
    Citation: International Journal of Computer Applications 176 (15), 1-6
    Year: 2020

 

Sheeja Rani S | Computer Science Award | Best Researcher Award

Dr. Sheeja Rani S | Computer Science Award | Best Researcher Award

👤 Dr. Sheeja Rani S, American University of Sharjah, United Arab Emirates

Dr. Sheeja Rani S is a visionary researcher and academician specializing in Computer Science and Engineering, with a strong focus on Wireless Sensor Networks, IoT, and Smart Grids. She earned her Ph.D. from Noorul Islam Centre for Higher Education in 2023, where her thesis emphasized energy-efficient clustering algorithms for wireless sensor networks. Her academic journey is complemented by over a decade of teaching and research experience, where she worked on innovative solutions in cybersecurity, cloud computing, and machine learning. Currently serving as a Postdoctoral Research Assistant at the American University of Sharjah, Dr. Sheeja collaborates with leading experts on cutting-edge projects. With over 20 journal papers, numerous conference contributions, and a passion for impactful research, she strives to advance technology and foster intellectual growth. Her mission is to combine her expertise and mentorship skills to inspire future innovators while contributing to meaningful explorations in academia and beyond.

Professional Profile

scopus

google scholar

🌟 Evaluation of Dr. Sheeja Rani S for the Research for Best Researcher Award

Summary of Suitability

Dr. Sheeja Rani S stands out as a highly qualified candidate for the “Research for Best Researcher Award,” showcasing an exceptional academic trajectory, prolific research output, and impactful contributions to multiple interdisciplinary domains. With a Ph.D. in Computer Science and Engineering focusing on improving energy efficiency in wireless sensor networks (WSNs), her research has addressed critical challenges in IoT, cloud computing, and smart grid technologies. These fields are not only contemporary but also pivotal for sustainable and secure technological advancements.

🎓 Education 

  • Ph.D. in Computer Science and Engineering (2023)
    Noorul Islam Centre for Higher Education
    Thesis: Improving Energy Efficiency Based on Clustering Algorithms for Wireless Sensor Networks.
  • M.E. in Computer Science and Engineering (2012)
    Noorul Islam Centre for Higher Education
  • M.Sc. Integrated Software Engineering (2009)
    Anna University, Chennai

Dr. Sheeja’s academic pursuits are rooted in innovation, particularly in optimizing computational techniques for energy efficiency and data security. Her Ph.D. research laid a foundation for creating advanced clustering mechanisms in wireless sensor networks, while her postgraduate and undergraduate studies focused on mastering computer science fundamentals and software engineering. She remains committed to lifelong learning and applying her knowledge to address emerging technological challenges.

💼  Professional Experience 

  • Postdoctoral Research Assistant (2023-Present)
    American University of Sharjah

    • Research on cybersecurity, smart grids, and cloud computing.
    • Published 12 journal papers in high-impact areas like IoT and machine learning.
  • Research Assistant (2022-2023)
    University of Sharjah

    • Focused on IoT, WSNs, and cloud computing.
    • Published 11 journal papers on financial distress prediction and IoT advancements.
  • Assistant Professor (2012-2021)
    John Cox Memorial CSI Institute of Technology

    • Taught advanced programming and database systems.
    • Managed academic coordination and examination processes.

Dr. Sheeja’s professional journey showcases a blend of teaching, research, and academic leadership, reflecting her dedication to advancing the field of computer science.

🏅 Awards and Recognitions 

  • Best Researcher Award (2023) – Recognized for impactful research in IoT and WSN.
  • Academic Excellence Award (2021) – Awarded for outstanding teaching and mentorship.
  • Research Grant Award (2022) – Funded for innovative studies on machine learning and cybersecurity.
  • Publication Excellence Award (2023) – Honored for prolific contributions to reputed journals.

Dr. Sheeja has consistently received accolades for her exceptional academic and research contributions. Her achievements reflect her dedication to excellence and her ability to produce innovative solutions that address global challenges.

🌍  Research Skills On Computer Science Award 

Dr. Sheeja’s research expertise spans:

  • Wireless Sensor Networks (WSN): Energy-efficient routing and clustering.
  • IoT: Developing secure and scalable architectures for smart environments.
  • Machine Learning: Applying predictive models for financial and cybersecurity domains.
  • Smart Grids: Integration of AI for optimal energy distribution.
  • Cloud Computing: Enhancing reliability and fault tolerance in virtualized environments.

📖 Publication Top Notes

Improved buffalo optimized deep feed forward neural learning based multipath routing for energy-efficient data aggregation in WSN
    • Authors: SS Rani, KS Sankar
    • Citation: Measurement: Sensors 27, 100662
    • Cited by: 8
    • Year: 2023
Optimized deep learning for Congestion-Aware continuous target tracking and boundary detection in IoT-Assisted WSN
    • Authors: AM Khedr, SS Rani, M Saad
    • Citation: IEEE Sensors Journal 23 (7), 7938-7948
    • Cited by: 8
    • Year: 2023
Enhancing Supply Chain Management with Deep Learning and Machine Learning Techniques: A Review
    • Authors: SSR Khedr, Ahmed M
    • Citation: Journal of Open Innovation: Technology, Market, and Complexity, 100379
    • Cited by: 5
    • Year: 2024
Hybridized Dragonfly and Jaya algorithm for optimal sensor node location identification in mobile wireless sensor networks
    • Authors: AM Khedr, SS Rani, M Saad
    • Citation: The Journal of Supercomputing 79 (15), 16940-16962
    • Cited by: 4
    • Year: 2023
Enhancing financial distress prediction through integrated Chinese Whisper clustering and federated learning
    • Authors: AI Al Ali, AM S S Rani Khedr
    • Citation: Journal of Open Innovation: Technology, Market, and Complexity 10 (3), 100344
    • Cited by: 2
    • Year: 2024