Carlos Javier Morales Pérez | Signal Processing and Acquisition | Best Researcher Award

Dr. Carlos Javier Morales Pérez | Signal Processing and Acquisition | Best Researcher Award

Investigador Posdoctoral | Universidad Autónoma de Querétaro (UAQ), Campus San Juan del Río | Mexico

Best Researcher Award

Strengths for the Award

  1. Research Excellence: Dr. Morales Pérez has a robust research portfolio, with multiple publications in high-impact journals such as IEEE Transactions and the International Journal of Dynamics and Control. His work on fault detection in electrical machines and signal processing is cutting-edge, addressing both theoretical and practical challenges in the field.
  2. Professional Recognition: He has been recognized as a National Researcher Level 1 by CONAHCyT, a prestigious acknowledgment of his contributions to science and technology in Mexico. Additionally, his highest GPA achievement during his PhD and awards like the Student Travel Award by IEEE highlight his academic excellence.
  3. Teaching and Mentoring: As an educator, he has taught advanced courses in electronics at various institutions and supervised graduate theses. This shows his commitment to nurturing the next generation of engineers and researchers.
  4. Collaborative Engagements: Dr. Morales Pérez is actively involved in reviewing for top journals and participating in academic committees, indicating his influence and respect in the research community.

Areas for Improvement

  1. Expanding International Collaboration: While Dr. Morales Pérez has a solid national presence, expanding his collaborations internationally could further elevate his research impact and visibility. Engaging in more cross-border research projects or co-authoring papers with international researchers could be beneficial.
  2. Diversification of Research: While his focus on signal processing and electrical machines is commendable, exploring interdisciplinary applications of his research, such as in biomedical engineering or environmental monitoring, could enhance the broader relevance and application of his work.
  3. Increased Citation Metrics: Although his citation metrics are respectable, working on increasing his research’s visibility through more conference presentations, open-access publications, and active dissemination on platforms like ResearchGate could improve these numbers.

Conclusion

Dr. Carlos Javier Morales Pérez is a highly qualified candidate for the “Best Researcher Award,” with notable achievements in the field of electronics, particularly in fault detection and signal processing. His solid academic and professional record, combined with his teaching and mentoring roles, underscores his potential to continue contributing significantly to his field. With minor improvements in international collaboration and diversification of research areas, Dr. Morales Pérez’s work could achieve even greater recognition on a global scale.

📜 Short Bio

Carlos Javier Morales Pérez is a dedicated electronics engineer and a National Researcher Level 1 (CONAHCyT, Mexico) with about five years of professional experience. His expertise lies in instrumentation, measurement, and control, with a strong focus on advanced signal and image processing techniques for rotating electrical machines. Currently, he is a postdoctoral researcher at the Universidad Autónoma de Querétaro (UAQ), Mexico, where he continues to explore his research interests in digital systems, FPGAs, embedded systems, and signal/image acquisition & processing.

Profile

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🎓 Education

Carlos holds a PhD in Electronics (2021) and an MSc in Electronics (2017) from the Instituto Nacional de Astrofísica, Óptica y Electrónica in Puebla, Mexico. He completed his BEng in Electronics in 2013 from Instituto Tecnológico Superior de Comalcalco in Tabasco, Mexico. His academic journey has been marked by exceptional achievements, including graduating with the highest GPA in his PhD program.

💼 Experience

Carlos began his career in the oil and gas industry, working as an Instrumentation and Control Engineer from 2013 to 2015, and earlier as a Technician from 2008 to 2012. His industrial experience spans calibrations, configurations, and the integration of devices and systems in both onshore and offshore facilities. He has also built a robust teaching portfolio, lecturing at various institutions, including the Universidad Autónoma de Querétaro and Universidad Tecnológica de Puebla, where he teaches courses ranging from Digital Systems to Evolutionary Computation.

🔬 Research Interests

Carlos’s research is deeply rooted in the fields of instrumentation and measurement, with specific interests in digital systems, FPGAs, embedded systems, and signal/image processing. He is particularly focused on applying these technologies to diagnose and monitor faults in electrical machines, contributing valuable insights to the field of advanced signal processing techniques.

🏆 Awards

Carlos has received numerous awards, including being recognized as a National Researcher Level 1 by CONAHCyT (2022-2027). He was also honored as the Guest Speaker at the INAOE graduation ceremony in 2021 and awarded the Highest Grade Point Average in his PhD program. His earlier accolades include a Student Travel Award by IEEE in 2017 and an Academic Excellence recognition by ANFEI in 2014.

📚 Publications

Carlos has contributed significantly to the field of electronics, with publications in renowned journals and conferences. Some of his key works include:

Incipient Inter-Turn Short Circuit Detection in Induction Motors Using Cumulative Distribution Function and the EfficientNetv2 Model (2024) – Machines (MDPI) DOI

Cited in various articles focused on electrical machine diagnostics.

Induction Machine Bearing Fault Detection Using Empirical Wavelet Transform (2022) – Shock and Vibration (Hindawi) DOI

This study has been referenced in papers exploring fault detection methodologies.

Noise Reduction in Electrical Signal Using OMP Algorithm Based on DCT and DSC Dictionaries (2021) – IEEE Transactions on Instrumentation and Measurement DOI

Frequently cited in research related to signal processing techniques.

Diagnostic of Combined Mechanical and Electrical Faults in ASD-powered Induction Motor Using MODWT and a Lightweight 1D CNN (2021) – IEEE Transactions on Industrial Informatics DOI

Influential in the field of industrial informatics and machine fault detection.

On Maximizing the Positive Lyapunov Exponent of Chaotic Oscillators Applying DE and PSO (2019) – International Journal of Dynamics and Control, vol. 7, no. 7 DOI

Cited in studies exploring chaotic systems and optimization algorithms.

 

 

Dr. Mir Asif Iquebal | Bioinformatics and Computational Biology | Best Researcher Award

Dr. Mir Asif Iquebal | Bioinformatics and Computational Biology | Best Researcher Award

Dr. Mir Asif Iquebal, ICAR-Indian Agricultural Statistics Research Institute, India

Dr. Mir Asif Iquebal is a distinguished academician with a Ph.D. in Agricultural Statistics earned in 2008 from ICAR-Indian Agricultural Research Institute, New Delhi, India 🎓. His doctoral expertise lies in advanced statistical methods, showcased in his thesis, “A Study on Some Nonlinear Time-series Models in Agriculture.” Prior, he excelled, securing the first rank in M.Sc. Agricultural Statistics in 2004, focusing on “Estimation of Heritability of Threshold Characters Using Auxiliary Traits.” Dr. Iquebal’s commitment to excellence in agricultural statistics is evident throughout his educational journey. With over sixteen years of extensive experience, he currently serves as a Senior Scientist at the Division of Agricultural Bioinformatics, ICAR-IASRI, contributing significantly to Computational Biology and Statistical modeling 🌐. His diverse professional background includes roles at ICAR-Indian Institute of Pulses Research, Kanpur, and ICAR-National Academy of Agricultural Research Management, Hyderabad. In teaching, spanning twelve years, he imparts knowledge to M.Sc. and Ph.D. students, covering a range of courses from Introduction to Bioinformatics to Computational Genomics 📚. Dr. Iquebal’s research interests at the forefront of Computational Biology and Agricultural Bioinformatics involve Genomics, Genome Assembly, and RNA-seq Data Analysis. His innovative spirit extends to the application of Machine Learning techniques and the development of web-based tools, reflecting his dedication to advancing research accessibility in genomics and computational biology 🧬.

🎓 Education :

Dr. Mir Asif Iquebal is an accomplished academician with a Ph.D. in Agricultural Statistics earned in 2008 from ICAR-Indian Agricultural Research Institute, New Delhi, India 🎓. His doctoral thesis, “A Study on Some Nonlinear Time-series Models in Agriculture,” reflects his expertise in advanced statistical methods. Prior, he secured the first rank in M.Sc. Agricultural Statistics in 2004 from the same institute, with a thesis on “Estimation of Heritability of Threshold Characters Using Auxiliary Traits.” Dr. Iquebal’s educational journey showcases his commitment to excellence in the field of agricultural statistics 🌾

🌐 Professional Profiles :

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🔄 Experiences :

With over sixteen years of extensive experience, Dr. Mir Asif Iquebal is currently serving as a Senior Scientist at the Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute (IASRI), New Delhi 🌾. He has been contributing significantly since joining on April 11, 2011, engaging in impactful research in Computational Biology and Statistical modeling. His responsibilities encompass research, teaching, and training in the fields of Agricultural Bioinformatics, Computational Biology, and Agricultural Statistics. Prior to his current role, Dr. Iquebal worked at ICAR-Indian Institute of Pulses Research, Kanpur, and commenced his career as a Scientist at ICAR-National Academy of Agricultural Research Management, Hyderabad, in January 2008 🚀. His diverse experience underscores his expertise and commitment to advancing agricultural research and bioinformatics.

🔍 Teaching :

Dr. Mir Asif Iquebal brings a wealth of teaching experience, spanning twelve years from 2011 to the present, imparting knowledge to M. Sc. and Ph. D. students at the PG School, ICAR-Indian Agricultural Research Institute, New Delhi 🎓. His diverse range of courses reflects his expertise, including foundational subjects such as Introduction to Bioinformatics and Statistical Methods for Applied Sciences, as well as specialized topics like Computational Genomics and Machine Learning Techniques in Bioinformatics. Dr. Iquebal’s commitment to education is evident in the breadth of subjects he covers, contributing significantly to the academic growth of students in the field of agricultural bioinformatics and computational biology 🌱.

🌐 Research Interests  :

Dr. Mir Asif Iquebal’s research interests lie at the intersection of cutting-edge fields, focusing on Computational Biology and Agricultural Bioinformatics 🧬. His expertise encompasses Genomics, Genome Assembly, and RNA-seq Data Analysis, where he employs advanced techniques to unravel the complexities of biological data. Driven by innovation, he delves into the application of Machine Learning techniques for insightful data interpretation. Additionally, he contributes to the development of web-based tools and genomic resources, reflecting his commitment to advancing research accessibility and technological solutions in genomics 🌐.

📚 Publication Impact and Citations :

Scopus Metrics:

  • 📝 Publications: 142 documents indexed in Scopus.
  • 📊 Citations: A total of 954 citations for his publications, reflecting the widespread impact and recognition of Dr. Mir Asif Iquebal’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 1657 📖
    • h-index: 21  📊
    • i10-index: 57 🔍
  • Since 2018:
    • Citations: 1304 📖
    • h-index: 17 📊
    • i10-index: 43 🔍

👨‍🏫 A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. 🌐🔬

Publications Top Notes  :

1.  RNAseq analysis reveals drought-responsive molecular pathways with candidate genes and putative molecular markers in root tissue of wheat

Journal: Scientific Reports, 9(1), 13917

Published Year: 2019

Cited By: 65

2.  Origin, diversity and genome sequence of mango (Mangifera indica L.)

Journal: Not Available

Published Year: 2016

Cited By: 65

3.  Uncovering genomic regions associated with 36 agro-morphological traits in Indian spring wheat using GWAS

Journal: Frontiers in Plant Science, 10, 527

Published Year: 2019

Cited By: 59

4.  Genetic variability for chickpea (Cicer arietinum L.) under late-sown season

Journal: Legume Research – An International Journal, 35(1), 1-7

Published Year: 2012

Cited By: 55

5.  Transcriptomic signature of drought response in pearl millet (Pennisetum glaucum (L.) and development of web-genomic resources

Journal: Scientific Reports, 8(1), 3382

Published Year: 2018

Cited By: 51