Dr. Uma Jothi | Team Building and Team Management | Excellence in Research

Dr. Uma Jothi | Team Building and Team Management | Excellence in Research

Amrita University, India

Dr. J. Uma is an accomplished academic and researcher in the fields of information technology, cloud computing, artificial intelligence, and cybersecurity. She holds a B.Tech in Information Technology, an M.E. in Computer Science and Engineering with distinction, and has submitted her Ph.D. thesis in Information and Communication Engineering at Anna University. With more than twelve years of academic experience, she has served as Assistant Professor in leading engineering institutions, contributing significantly to teaching, curriculum development, and research mentorship. Her research focuses on cloud resource allocation, deep reinforcement learning, intelligent optimization algorithms, blockchain technologies, IoT-based systems, and data security. She has published impactful journal articles in reputed outlets like Transactions on Emerging Telecommunications Technologies and Springer’s Lecture Notes in Networks and Systems, along with several book chapters and conference papers. Her work includes innovations in heuristic optimization, adversarial defenses in deep learning, and smart healthcare IoMT solutions. She is also a published patent holder in IoT-based agriculture monitoring systems and employee training platforms. Dr. Uma has organized major AICTE- and RGNIYD-funded programs, contributing to national-level capacity building in data science, IoT, and smart city technologies. Her career reflects a strong commitment to advancing research, innovation, and academic excellence.

Profiles:  ORCID

Featured Publications

Dr. Chan Young Park | Risk Management | Best Researcher Award

Dr. Chan Young Park | Risk Management | Best Researcher Award

Texas A&M University | South Korea
Profile:  Scopus 

Featured Publications

Baek, S., Park, C. Y., & Jung, W. (2025). Automated safety risk management guidance enhanced by retrieval-augmented large language model. Automation in Construction, 176, 106255.

Assoc. Prof. Dr. Ankit Chaudhary | Strategic Leadership | Best Researcher Award

Assoc. Prof. Dr. Ankit Chaudhary | Strategic Leadership | Best Researcher Award

Jawaharlal Nehru University | India

Profiles: Google Scholar | Scopus

Featured Publications

Raheja, J. L., Chaudhary, A., & Singal, K. (2011). Tracking of fingertips and centers of palm using KINECT. 2011 IEEE 3rd International Conference on Computational Intelligence, Modelling and Simulation (CIMSIM), 248–252.

Pandy, H., Chaudhary, A., & Mehrotra, D. (2014). A comparative review of approaches to prevent premature convergence in GA. Applied Soft Computing, 24, 1047–1077.

Chaudhary, A., Raheja, J. L., Das, K., & Raheja, S. (2011). Intelligent approaches to interact with machines using hand gesture recognition in natural way: A survey. International Journal of Computer Science and Engineering Survey (IJCSES), 2(1), 122–133.

Raheja, J. L., Kumar, S., & Chaudhary, A. (2013). Fabric defect detection based on GLCM and Gabor filter: A comparison. Optik, 124(23), 6469–6474.

Raheja, J. L., Mishra, A., & Chaudhary, A. (2016). Indian Sign Language recognition using SVM. Pattern Recognition and Image Analysis, 26(2), 434–441.

Prof. Samir Ladaci | Control Engineering | Best Researcher Award

Prof. Samir Ladaci | Control Engineering | Best Researcher Award

Ecole Nationale Polytechnique Algiers | Algeria

Author Profile

Google Scholar

Early Academic Pursuits

S. Ladaci’s academic journey began with a deep engagement in the theoretical and mathematical foundations of control engineering, where he explored the emerging concept of fractional calculus and its application to adaptive control. His early scholarly focus combined rigorous mathematical analysis with practical engineering insights, aiming to extend traditional control theory into the fractional domain. This early period was characterized by an eagerness to investigate the unique properties of fractional-order systems—systems described by non-integer order differential equations—and their potential in achieving more robust and flexible control strategies. Through collaborations with fellow scholars such as A. Charef and J.J. Loiseau, he developed a foundational understanding of both the opportunities and the mathematical challenges in bridging fractional calculus with adaptive control techniques.

Professional Endeavors

Throughout his professional career, S. Ladaci has actively pursued research and publication in high-impact journals, contributing to the advancement of fractional-order control systems. He has collaborated extensively with a network of international researchers, including K. Rabah, Y. Bensafia, and M. Assabaa, which has allowed his work to maintain both theoretical depth and practical applicability. His research output spans various aspects of fractional adaptive control, from theoretical formulations to advanced simulation studies, making substantial contributions to engineering science and control theory. His professional endeavors also extend to exploring fuzzy systems, sliding mode control, and adaptive gain techniques, creating a multidimensional portfolio that bridges mathematical theory with engineering practice.

Contributions and Research Focus

S. Ladaci’s primary research focus lies in the integration of fractional calculus into adaptive control strategies, aiming to overcome limitations of conventional integer-order control systems. His notable contributions include developing fractional order adaptive high-gain controllers for linear systems, designing sliding mode control configurations for synchronizing disturbed fractional-order chaotic systems, and proposing robust adaptive control methods grounded in strictly positive realness conditions. These works not only expanded theoretical understanding but also provided practical frameworks for controlling complex and uncertain systems. Furthermore, his research into fuzzy adaptive control with Nussbaum gains addressed the challenges of unknown control gain signs in chaotic systems, reflecting his commitment to solving non-trivial, real-world engineering problems.

Accolades and Recognition

The impact of S. Ladaci’s research is evident in the consistent citation and recognition his work has received across multiple respected journals such as Nonlinear Dynamics, Communications in Nonlinear Science and Numerical Simulation, IEEE/CAA Journal of Automatica Sinica, and IET Control Theory & Applications. His papers are widely referenced within the control systems community, highlighting the relevance and applicability of his contributions. Recognition of his work has come not only from academia but also from engineering practitioners who seek robust and innovative control strategies. His collaborations with leading institutions and publication in internationally recognized platforms serve as a testament to the scholarly and applied value of his work.

Impact and Influence

S. Ladaci’s influence in the field of fractional adaptive control has been significant in shaping both the theoretical discourse and the applied engineering approaches to system control. His works have contributed to broadening the scope of adaptive control to include fractional-order dynamics, enabling engineers to design controllers that can handle a wider range of system uncertainties and disturbances. By addressing stability issues, robustness, and adaptive gain configurations, his research has provided solutions applicable to a variety of fields, from mechanical and electrical engineering to complex systems in science and technology. This influence is evident in the way his methodologies have been adopted, extended, and cited by other researchers working in nonlinear systems, chaos control, and adaptive algorithms.

Legacy and Future Contributions

The legacy of S. Ladaci’s work lies in his pioneering efforts to merge fractional calculus with adaptive control, thereby opening new avenues for research and application. His publications continue to serve as foundational references for scholars and engineers working on control strategies for complex and uncertain systems. Moving forward, his research trajectory suggests a growing emphasis on integrating intelligent control techniques—such as fuzzy logic and machine learning—with fractional-order systems to enhance adaptability and predictive capabilities. This blend of fractional calculus with modern computational intelligence tools positions his future work to have a lasting impact on the next generation of control technologies, offering solutions that are not only mathematically rigorous but also practically resilient.

Notable Publications

On fractional adaptive control

Authors: Ladaci, S.; Charef, A.
Journal: Nonlinear Dynamics
Year: 2006

Fractional order adaptive high-gain controllers for a class of linear systems

Authors: Ladaci, S.; Loiseau, J.J.; Charef, A.
Journal: Communications in Nonlinear Science and Numerical Simulation
Year: 2008

A fractional adaptive sliding mode control configuration for synchronizing disturbed fractional-order chaotic systems

Authors: Rabah, K.; Ladaci, S.
Journal: Circuits, Systems, and Signal Processing
Year: 2020

Robust fractional adaptive control based on the strictly positive realness condition

Authors: Ladaci, S.; Charef, A.; Loiseau, J.J.
Journal: Uniwersytet Zielonogórski
Year: 2009

Fuzzy adaptive control of fractional order chaotic systems with unknown control gain sign using a fractional order Nussbaum gain

Authors: Khettab, K.; Ladaci, S.; Bensafia, Y.
Journal: IEEE/CAA Journal of Automatica Sinica
Year: 2016

Conclusion

S. Ladaci’s academic and professional journey reflects a sustained commitment to advancing the field of control engineering through the innovative application of fractional calculus. From his early theoretical investigations to his influential publications in adaptive, sliding mode, and fuzzy control, he has consistently contributed to expanding the horizons of control theory and practice. His work has left a lasting mark on both scholarly literature and applied engineering, inspiring further research and fostering technological innovation. As the field evolves, his integration of fractional calculus with adaptive and intelligent control methods stands as both a legacy and a forward-looking pathway, ensuring his continued influence in the discipline.