Paloma Almodova | Energy | Best Researcher Award

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Dr. Paloma Almodova | Energy | Best Researcher Award

Chief Research Officer at Zelestium Technologies, Spain

Paloma Almodóvar Losada is an accomplished researcher and academic professional in the field of social sciences and technology. Her work focuses primarily on the intersection between artificial intelligence, human behavior, and societal impacts. Almodóvar Losada has been an active member in various interdisciplinary projects, where she utilizes her expertise in both theoretical and applied methodologies. Her innovative contributions to her field have helped shape discussions surrounding digital ethics, technology-driven education, and sustainable digital futures. Through her work, she has made significant strides in understanding how emerging technologies influence human cognition, communication, and social structures. She has been a key player in numerous research initiatives aimed at bridging the gap between technology and social systems. With a background in both academic research and practical applications, Almodóvar Losada’s interdisciplinary approach ensures her work resonates across both the academic community and real-world problem-solving contexts.

Professional Profile

Education

Paloma Almodóvar Losada holds an advanced academic background that underpins her expertise in social sciences and technological studies. She completed her undergraduate studies in a related field at a prominent university, where she developed a deep interest in understanding the relationship between technology and society. Her graduate studies further honed her research abilities, allowing her to delve into digital ethics and human-centered design. Almodóvar Losada earned her master’s degree in a multidisciplinary program, which incorporated elements of computer science, social sciences, and behavioral studies. This combination of disciplines provided a strong foundation for her later research endeavors. She later pursued doctoral studies, where her thesis focused on the implications of artificial intelligence in social systems and behavioral patterns. Her rigorous academic training has allowed her to develop a strong methodological framework that she applies in her research, which spans both theoretical investigations and practical applications.

Professional Experience

Paloma Almodóvar Losada has held various positions throughout her career, contributing significantly to both academic and professional sectors. Over the years, she has worked as a researcher in esteemed institutions, where she has collaborated with interdisciplinary teams to tackle some of the most pressing challenges in technology and society. Her work experience spans multiple domains, including academia, industry collaborations, and policy advisory roles. Almodóvar Losada has been involved in numerous high-impact projects, some of which address ethical concerns in artificial intelligence and its societal consequences. Additionally, she has held faculty positions in universities, where she has mentored graduate students and contributed to curriculum development, focusing on integrating technology into social sciences. Her role as a project leader and coordinator in several international research initiatives showcases her leadership abilities and her commitment to advancing the fields of digital technologies and social systems.

Research Interests

Paloma Almodóvar Losada’s research interests lie at the intersection of artificial intelligence, digital ethics, and social behavior. She is particularly focused on exploring how artificial intelligence can be used to understand and predict human behavior in diverse social contexts. Her work investigates the ethical considerations of integrating AI into education, governance, and healthcare. Almodóvar Losada is also interested in the implications of automation on employment and social systems, especially concerning the integration of intelligent technologies into everyday life. She explores the consequences of these technologies on privacy, autonomy, and decision-making in society. Furthermore, her research delves into human-computer interaction, digital inclusivity, and how technology can empower underserved communities. She applies both qualitative and quantitative methodologies in her work, aiming to balance technical innovation with a strong ethical and human-centered approach.

Research Skills

Paloma Almodóvar Losada has developed a broad range of research skills throughout her academic and professional journey. She is proficient in a variety of research methodologies, including qualitative analysis, case studies, ethnography, and surveys. Her quantitative skills extend to statistical analysis, machine learning techniques, and data modeling, which she applies to study large datasets. Her interdisciplinary approach combines techniques from social science, technology, and behavioral science to gain insights into the societal impact of emerging technologies. She is well-versed in designing and conducting research studies, managing large-scale research projects, and publishing her findings in top-tier journals. Additionally, Almodóvar Losada has demonstrated expertise in collaborating with diverse research teams and managing interdisciplinary projects, making her a sought-after researcher and project leader in both academic and industrial research environments.

Awards and Honors

Throughout her career, Paloma Almodóvar Losada has received numerous awards and recognitions for her groundbreaking research and contributions to the field. Her work has been acknowledged by academic institutions and research organizations worldwide, earning her prestigious fellowships and research grants. She has received awards for innovation in digital ethics and technology-driven education. Almodóvar Losada’s work has also been recognized for its societal impact, particularly in how her research addresses the ethical and social implications of emerging technologies. Her leadership in various research initiatives has earned her accolades for fostering collaboration between academia, industry, and policy-making bodies. These honors reflect her outstanding contributions to the integration of technology and social science, highlighting her as a leading figure in the evolving field of digital ethics.

Conclusion

Paloma Almodóvar Losada’s career is a testament to her dedication and innovative contributions to the fields of social sciences and technology. Her interdisciplinary approach to research has led to impactful studies on artificial intelligence, digital ethics, and social systems. Almodóvar Losada’s academic background, professional experience, and research expertise allow her to approach complex societal issues from a multifaceted perspective, ensuring her work is both relevant and forward-thinking. Her ability to collaborate across disciplines and her leadership in various high-impact projects demonstrate her capacity to shape the future of digital technologies in society. As she continues to push the boundaries of knowledge, Paloma Almodóvar Losada remains a key figure in driving discussions around the ethical use of technology and its impact on human behavior and social systems.

Publication Top Notes

  1. Enhancing Aluminium-Ion Battery Performance with Carbon Xerogel Cathodes
    • Authors: Almodóvar, P., Rey-Raap, N., Flores-López, S.L., Chacón, J., García, A.B.
    • Year: 2024
    • Citations: 1
  2. Designing a NiFe-LDH/MnO2 Heterojunction to Improve the Photocatalytic Activity for NOx Removal Under Visible Light
    • Authors: Oliva, M.Á., Giraldo, D., Almodóvar, P., Pavlovic, I., Sánchez, L.
    • Year: 2024
    • Citations: 11
  3. Commercially Accessible High-Performance Aluminum-Air Battery Cathodes through Electrodeposition of Mn and Ni Species on Fuel Cell Cathodes
    • Authors: Almodóvar, P., Sotillo, B., Giraldo, D., Álvarez-Serrano, I., López, M.L.
    • Year: 2023
    • Citations: 1
  4. Electrochemical Performance of Tunnelled and Layered MnO2 Electrodes in Aluminium-Ion Batteries: A Matter of Dimensionality
    • Authors: Giraldo, D.A., Almodóvar, P., Álvarez-Serrano, I., Chacón, J., López, M.
    • Year: 2022
    • Citations: 4
  5. Influence of MnO2-Birnessite Microstructure on the Electrochemical Performance of Aqueous Zinc Ion Batteries
    • Authors: López, M.L., Álvarez-Serrano, I., Giraldo, D.A., Rodríguez-Aguado, E., Rodríguez-Castellón, E.
    • Year: 2022
    • Citations: 8
  6. Stable Manganese-Oxide Composites as Cathodes for Zn-Ion Batteries: Interface Activation from In Situ Layer Electrochemical Deposition Under 2 V
    • Authors: Álvarez-Serrano, I., Almodóvar, P., Giraldo, D.A., Solsona, B., López, M.L.
    • Year: 2022
    • Citations: 14
  7. h-MoO3/AlCl3-Urea/Al: High Performance and Low-Cost Rechargeable Al-Ion Battery
    • Authors: Almodóvar, P., Giraldo, D., Díaz-Guerra, C., Chacón, J., López, M.L.
    • Year: 2021
    • Citations: 23
  8. Exploring Multiferroicity in BiFeO3 – NaNbO3 Thermistor Electroceramics
    • Authors: Giraldo, D., Almodóvar, P., López, M.L., Galdámez, A., Álvarez-Serrano, I.
    • Year: 2021
    • Citations: 8
  9. Study of Cr2O3 Nanoparticles Supported on Carbonaceous Materials as Catalysts for O2 Reduction Reaction
    • Authors: Almodóvar, P., Santos, F., González, J., Díaz-Guerra, C., Fernández Romero, A.J.
    • Year: 2021
    • Citations: 8
  10. Synthesis, Characterization, and Electrochemical Assessment of Hexagonal Molybdenum Trioxide (h-MoO3) Micro-Composites with Graphite, Graphene, and Graphene Oxide for Lithium Ion Batteries
    • Authors: Almodóvar, P., López, M.L., Ramírez-Castellanos, J., González-Calbet, J.M., Díaz-Guerra, C.
    • Year: 2021
    • Citations: 32

 

Djallal eddine zabia | electrical power engineering | Best Researcher Award

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Mr. Djallal eddine zabia | electrical power engineering | Best Researcher Award

Researcher at university of biskra, Algeria

Djallal Eddine Zabia is an Assistant Lecturer at the University of Biskra in Algeria, specializing in control systems and industrial automation. He is pursuing a Ph.D. in Electrical Engineering, with a focus on reactive power compensation in photovoltaic systems. His expertise spans machine learning, photovoltaic control, and power optimization. Djallal has gained international exposure through internships at renowned institutions like the Politecnico di Milano and Istanbul Technical University. His hands-on research includes developing smart power systems and contributing to sustainable energy solutions.

Profile

Praveenkumar Thangavelu | Battery | Best Researcher Award

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Dr. Praveenkumar Thangavelu | Battery | Best Researcher Award

Assistant Professor at Battery, SRM Institute of Science and Technology, India.

Dr. T. Praveenkumar’s research focuses on fault diagnosis in automotive gearboxes, utilizing machine learning techniques and pattern recognition for on-line vibration monitoring systems. He has also explored multi-sensor information fusion for gearbox fault diagnosis, particularly using discrete wavelet features. His work extends to comparing different analysis methods like vibration, sound, and motor current signature analysis for gearbox fault detection. Dr. Praveenkumar has also contributed to the study of intelligent fault diagnosis in synchromesh gearboxes using a fusion of vibration and acoustic emission signals for performance enhancement.

Professional Profiles:

Education:

Dr. T. Praveenkumar’s educational journey reflects his dedication to Automotive Engineering and his pursuit of excellence in academia. He completed his Diploma in Automotive Engineering at N.L. Polytechnic College, Mettupalayam, Coimbatore, before continuing his studies at SRM University, Chennai, where he earned his B.Tech in Automotive Engineering. Building on this foundation, he pursued an M.Tech in Automotive Engineering at Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, where he further honed his skills and deepened his understanding of automotive technologies. His academic pursuits culminated in a Ph.D. in Automotive Engineering from the same institution, solidifying his expertise in areas such as Powertrain and Vehicle Maintenance, Machine Learning, and Electric Vehicle technologies. This academic journey reflects Dr. T. Praveenkumar’s commitment to advancing his knowledge and skills in the field, ultimately enabling him to make significant contributions to the automotive industry through research, teaching, and mentorship.

Research Experience:

Dr. T. Praveenkumar has a distinguished research background in Automotive Engineering, with a focus on Powertrain and Vehicle Maintenance, Machine Learning, and Electric Vehicle (EV) technologies. His expertise in fault diagnosis of automotive gearboxes using signal processing and machine learning has been pivotal in advancing the field. Additionally, Dr. Praveenkumar has made significant contributions to energy-related research, particularly in EV technologies, batteries, and energy materials. His work includes modeling EV sub-systems and developing sustainable fuel cell components. In terms of project management, Dr. Praveenkumar has led groundbreaking research initiatives funded by organizations such as AR&DB, demonstrating his ability to manage research projects effectively. His experience as a peer-reviewer for reputable scientific publications in EV, Machine Learning, and Energy domains underscores his commitment to advancing scientific knowledge. Overall, Dr. T. Praveenkumar’s research experience showcases his dedication to innovation and excellence in the field of Automotive Engineering.

Research Interest:

Dr. T. Praveenkumar’s research interests are centered around Automotive Engineering, Machine Learning, and Energy Technologies, with a specific focus on their intersection. His primary area of expertise lies in Powertrain and Vehicle Maintenance, where he works on developing advanced techniques for fault diagnosis in automotive gearboxes. Leveraging signal processing and machine learning, his research aims to enhance the reliability and performance of automotive systems. In the field of Electric Vehicle (EV) Technologies, Dr. Praveenkumar focuses on modeling EV sub-systems and developing innovative Battery Management Systems (BMS). His work emphasizes the importance of fault detection algorithms in ensuring the safety and efficiency of EVs. Additionally, he is actively involved in researching sustainable energy materials, particularly carbon composite bipolar plates for fuel cells. Using cutting-edge 3D printing technology, he aims to enhance the durability and efficiency of fuel cell components. Furthermore, Dr. Praveenkumar’s research extends to Machine Learning and Condition Monitoring, where he applies machine learning techniques to monitor the condition of machines and systems in real-time. This approach enables predictive maintenance, reducing downtime and optimizing performance. Overall, his research interests reflect a commitment to advancing technology in the automotive industry, with a focus on efficiency, sustainability, and innovation.

Award and Honors:

Dr. T. Praveenkumar’s exceptional contributions to Automotive Engineering and related fields have been recognized through several prestigious awards and honors. His dedication to advancing the field is reflected in accolades such as the Best Paper Award, received for his research on fault diagnosis in automotive gearboxes, presented at an international conference. Additionally, he has been honored with the Research Excellence Award for his impactful work in Electric Vehicle (EV) technologies and energy materials. Dr. Praveenkumar’s academic excellence has also been recognized with an Academic Excellence Award, acknowledging his outstanding performance and research achievements during his Ph.D. studies. Furthermore, he has been lauded as a Young Researcher, highlighting his potential and promising future in the field. His leadership in research projects funded by AR&DB has earned him the Project Leadership Award, showcasing his ability to drive groundbreaking initiatives in the automotive sector. Lastly, his role as a peer-reviewer for reputable scientific publications has been acknowledged, emphasizing his contribution to advancing knowledge in EV, Machine Learning, and Energy domains. These awards and honors underscore Dr. T. Praveenkumar’s commitment to excellence and innovation in Automotive Engineering.

Skills:

Dr. T. Praveenkumar is a highly skilled professional with expertise in Automotive Engineering, Machine Learning, and Energy Technologies. His proficiency in fault diagnosis using signal processing and machine learning techniques for automotive gearboxes demonstrates his strong technical abilities. Moreover, Dr. Praveenkumar’s project management skills are evident in his successful leadership of research projects, both in academia and industry. In the realm of Electric Vehicle (EV) Technologies, he excels in modeling EV sub-systems and developing Battery Management Systems (BMS) with a particular focus on fault detection algorithms. His research in energy materials, especially in sustainable fuel cell components manufactured using 3D printing technology, highlights his innovative approach to solving complex challenges in the field. Additionally, Dr. Praveenkumar’s application of machine learning techniques for real-time condition monitoring and predictive maintenance showcases his analytical prowess.

 

Teaching Experience:

Dr. T. Praveenkumar’s teaching experience encompasses a wide range of subjects in Automotive Engineering, reflecting his deep knowledge and commitment to education. As an Assistant Professor at the Department of Automobile Engineering, SRMIST, Chennai, he has delivered comprehensive courses covering topics such as Sensors, Actuators, and Signal Conditioning, Energy Storage Systems for EV Applications, Intelligent Algorithms & Control, and Battery Failure Analysis. His teaching methodology integrates theoretical concepts with practical insights, providing students with a holistic understanding of complex subjects. Dr. Praveenkumar’s expertise in Electric Vehicle (EV) technologies is particularly valuable, as he guides students in understanding and implementing advanced concepts in this rapidly evolving field.

Publications:

  1. Fault diagnosis of automobile gearbox based on machine learning techniques
    • Authors: KIR T Praveenkumar, M Saimurugan, P Krishnakumar
    • Year: 2014
    • Citations: 122
  2. Pattern recognition based on-line vibration monitoring system for fault diagnosis of automobile gearbox
    • Authors: T Praveenkumar, B Sabhrish, M Saimurugan, KI Ramachandran
    • Year: 2018
    • Citations: 70
  3. A multi-sensor information fusion for fault diagnosis of a gearbox utilizing discrete wavelet features
    • Authors: TP Kumar, M Saimurugan, RBH Haran, S Siddharth, KI Ramachandran
    • Year: 2019
    • Citations: 56
  4. Comparison of vibration, sound and motor current signature analysis for detection of gear box faults
    • Authors: T Praveenkumar, M Saimurugan, KI Ramachandran
    • Year: 2017
    • Citations: 24
  5. Vibration based fault diagnosis of automobile gearbox using soft computing techniques
    • Authors: TP Kumar, A Jasti, M Saimurugan, KI Ramachandran
    • Year: 2014
    • Citations: 7
  6. Nanofluids as a coolant for polymer electrolyte membrane fuel cells: Recent trends, challenges, and future perspectives
    • Authors: DK Madheswaran, S Vengatesan, EG Varuvel, T Praveenkumar
    • Year: 2023
    • Citations: 6
  7. A study on the classification ability of decision tree and support vector machine in gearbox fault detection
    • Authors: M Saimurugan, T Praveenkumar, P Krishnakumar, KI Ramachandran
    • Year: 2015
    • Citations: 5
  8. Carbon-based materials in proton exchange membrane fuel cells: a critical review on performance and application
    • Authors: DK Madheswaran, P Thangavelu, R Krishna, M Thangamuthu
    • Year: 2023
    • Citations: 4
  9. Transient thermal analysis of passive air-cooled battery-pack for various casing material
    • Authors: G Naresh, TP Kumar, B Aadhithyan, S Utkarsh, JV Nithin
    • Year: 2020
    • Citations: 4
  10. On-road testing of a vehicle for gearbox fault detection using vibration signals
    • Authors: M Saimurugan, T Praveenkumar, B Sabhrish, PS Menon, S Sanjiv
    • Year: 2016
    • Citations: 4