Liliana Aguilar-Marcelino | Cybersecurity | Best Innovation Award

Dr. Liliana Aguilar-Marcelino | Cybersecurity | Best Innovation Award

Senior researcher at Instituto Nacional de Investigaciones Forestales Agricolas y Pecuarias, Mexico

Dr. Liliana Aguilar-Marcelino is a senior researcher at the Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad (CENID-SAI) at INIFAP, Mexico. With a focus on microbial consortia, biocontrol, biotechnology, and natural product pharmacology, she investigates the bioactivity of fungi, bacteria, insects, mites, and nematodes. Her work includes exploring sustainable pest control strategies through biocontrol agents and metabolomic studies. Dr. Aguilar-Marcelino has contributed extensively to research on the insecticidal properties of metabolites from edible mushrooms and the development of nematocidal compounds. Her innovative research aims to advance agricultural sustainability and environmental health.

Education

Dr. Liliana Aguilar-Marcelino holds a distinguished academic background in the field of biological sciences. She completed her undergraduate studies in biology and later pursued advanced education, specializing in microbiology and biotechnology. Dr. Aguilar-Marcelino obtained her graduate degree (Master’s and/or Ph.D.) from a renowned institution, where she honed her expertise in microbial consortia, biocontrol, biotechnology, and the bioactivity of natural products. Her education has been instrumental in shaping her research focus, which spans a wide array of topics including natural product pharmacology, metabolomics, and the development of sustainable pest management solutions. With her strong academic foundation, Dr. Aguilar-Marcelino has become a leading researcher in her field, contributing significantly to the advancement of agricultural science and sustainable biocontrol technologies.

Experience

Dr. Liliana Aguilar-Marcelino has been a senior researcher at the Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad (CENID-SAI) at INIFAP, Mexico, since 2008. During her tenure, she has focused on pioneering research in microbial consortia, biocontrol, biotechnology, and metabolomics. She has led multiple studies exploring the bioactivity of fungi, bacteria, insects, mites, and nematodes, contributing to the development of sustainable solutions for pest control and agricultural health. Dr. Aguilar-Marcelino has published numerous research papers on topics such as the insecticidal effects of metabolites from edible mushrooms and the nematocidal properties of natural extracts, further establishing her expertise in the field of biocontrol and natural product pharmacology.

Research Interests

Dr. Liliana Aguilar-Marcelino’s research interests are centered on microbial consortia, biocontrol, and biotechnology, with a particular focus on the bioactivity of natural products. She specializes in metabolomics and the pharmacological potential of fungi, bacteria, insects, mites, and nematodes. Her work explores the development of natural pest control methods and sustainable agricultural practices through the study of bioactive compounds derived from edible mushrooms, fungi, and other microorganisms. Additionally, Dr. Aguilar-Marcelino investigates the potential of natural products for managing plant-parasitic nematodes and other agricultural pests, aiming to provide eco-friendly alternatives to traditional chemical controls.

 

Publication Top Noted

Title: New and future developments in microbial biotechnology and bioengineering: Trends of microbial biotechnology for sustainable agriculture and biomedicine systems: Diversity and applications

  • Authors: AA Rastegari, AN Yadav, N Yadav
  • Publisher: Elsevier
  • Cited by: 136
  • Year: 2020

Title: Micro (nano) plastics in wastewater: A critical review on toxicity risk assessment, behaviour, environmental impact, and challenges

  • Authors: S Singh, TSSK Naik, AG Anil, J Dhiman, V Kumar, DS Dhanjal, et al.
  • Journal: Chemosphere
  • Volume: 290
  • Article Number: 133169
  • Cited by: 71
  • Year: 2022

Title: Plasmodium berghei ookinetes induce nitric oxide production in Anopheles pseudopunctipennis midguts cultured in vitro

  • Authors: A Herrera-Ortíz, H Lanz-Mendoza, J Martínez-Barnetche, et al.
  • Journal: Insect Biochemistry and Molecular Biology
  • Volume: 34
  • Issue: 9
  • Pages: 893-901
  • Cited by: 65
  • Year: 2004

Title: The nematophagous fungus Duddingtonia flagrans reduces the gastrointestinal parasitic nematode larvae population in faeces of orally treated calves maintained under tropical conditions

  • Authors: P Mendoza-de-Gives, ME López-Arellano, L Aguilar-Marcelino, et al.
  • Journal: Veterinary Parasitology
  • Volume: 263
  • Pages: 66-72
  • Cited by: 52
  • Year: 2018

Title: Recent Trends in Mycological Research: Volume 1: Agricultural and Medical Perspective

  • Author: AN Yadav
  • Publisher: Springer International Publishing
  • Cited by: 49
  • Year: 2021

Title: Using molecular techniques applied to beneficial microorganisms as biotechnological tools for controlling agricultural plant pathogens and pests

  • Authors: L Aguilar-Marcelino, P Mendoza-de-Gives, LKT Al-Ani, et al.
  • Book: Molecular Aspects of Plant Beneficial Microbes in Agriculture
  • Pages: 333-349
  • Cited by: 47
  • Year: 2020

Title: Jesús Antonio Pineda-Alegría, José Ernesto Sánchez-Vázquez, Manases González-Cortazar, Alejandro Zamilpa, María Eugenia López-Arellano, Edgar Josué Cuevas-Padilla

  • Authors: P Mendoza-de-Gives, L Aguilar-Marcelino
  • Cited by: 69
  • Year: 2018

Conclusion

Dr. Liliana Aguilar-Marcelino’s innovative research in the areas of biocontrol, biotechnology, and natural product pharmacology has led to the development of several novel approaches for sustainable agricultural pest management. By focusing on natural alternatives to chemical pesticides, her work not only advances scientific understanding but also promotes environmentally friendly practices. Through her groundbreaking studies, Dr. Aguilar-Marcelino has significantly contributed to the field of sustainable agriculture, making her an outstanding candidate for the Research for Best Innovation Award.

Indu Radhakrishnan | Cryptography | Best Researcher Award

Ms. Indu Radhakrishnan | Cryptography | Best Researcher Award

Research scholar at PES University, India

Summary:

Ms. Indu Radhakrishnan is a dedicated educator and researcher currently serving as a Research Scholar pursuing M.Tech by Research in the Department of Computer Science and Engineering at PES University. With over 13 years of teaching experience, she has contributed significantly to the field of computer science education. Her research focuses on Cryptography, particularly in IoT security. Ms. Radhakrishnan has held various academic roles, including Assistant Professor at PES University and Coordinator & Assistant Professor at Surana College Peenya Campus. She holds a Master of Computer Applications from VTU – PESSE and a Bachelor of Science from Bangalore University.

Profile:

Education:

Ms. Indu Radhakrishnan holds a Master of Computer Applications (MCA) degree from VTU – PESSE, which she completed in 2010. Prior to her postgraduate studies, she earned a Bachelor of Science (BSc) degree from Bangalore University in 2007.

Professional Experience:

Ms. Indu Radhakrishnan brings over 13 years of teaching experience in computer science and engineering. Her current role as a Research Scholar at PES University involves conducting advanced research in Cryptography, focusing on IoT security. Previously, she served as an Assistant Professor at PES University, where she played a pivotal role in guiding student projects and organizing academic events. Prior to that, Ms. Radhakrishnan served as Coordinator & Assistant Professor at Surana College Peenya Campus, overseeing curriculum development and administrative responsibilities. Her expertise spans programming, networks, web designing, and she has actively contributed to workshops and faculty development programs in the field.

Research Interests:

Ms. Indu Radhakrishnan’s research interests span the domains of computer science and engineering, with a particular focus on Cryptography and IoT security. Her work delves into advanced cryptographic techniques aimed at enhancing security measures in Internet of Things (IoT) environments. She explores topics such as secure communication protocols, data encryption methods, and cryptographic key management systems to address the evolving challenges of cybersecurity in interconnected IoT ecosystems. Her research aims to contribute to the development of robust and resilient security solutions for emerging technologies and applications.

Publications:

Efficiency and Security Evaluation of Lightweight Cryptographic Algorithms for Resource-Constrained IoT Devices

  • Authors: I. Radhakrishnan, S. Jadon, P.B. Honnavalli
  • Journal: Sensors
  • Year: 2024
  • Volume and Issue: 24(12)
  • Pages: 4008

Jing Li | Deep Learning for Cybersecurity | Best Paper Award

Dr. Jing Li | Deep Learning for Cybersecurity | Best Paper Award

 Researcher at University Technology Malaysia, China

Summary:

Dr. Jing Li is a dedicated computer scientist currently pursuing a PhD in Computer Science at University Technology Malaysia. His research interests encompass networking, Internet of Things, machine learning/deep learning, cybersecurity, and big data. He has achieved academic excellence, being awarded the International Doctoral Scholarship (IDF) for the periods 2022-2023 and 2023-2024. Dr. Li holds a Master’s degree in Information Management from Zhejiang University, where he was recognized with the First Prize for his entrance essay submission and conducted research on “Hangzhou Wireless City Construction Planning.” He completed his Bachelor’s degree in Computer Science and Technology at China Jiliang University, distinguished as a four-time scholarship recipient.

Profile:

Education:

Dr. Jing Li is currently pursuing a PhD in Computer Science at University Technology Malaysia, focusing on networking, Internet of Things, machine learning/deep learning, cybersecurity, and big data. He has been awarded the prestigious International Doctoral Scholarship (IDF) for the academic years 2022-2023 and 2023-2024. Prior to this, he earned a Master’s degree in Information Management from Zhejiang University, where he received the First Prize for his entrance essay submission and completed a thesis titled “Research on Hangzhou Wireless City Construction Planning.” Dr. Li also holds a Bachelor’s degree in Computer Science and Technology from China Jiliang University, where he was a four-time scholarship winner.

Professional Experience:

Dr. Jing Li brings a wealth of professional experience in the technology sector, having held significant roles across various organizations. He started his career as a Software Engineer at UTStarcom (China) Co., Ltd., where he gained foundational experience from June 2003 to June 2006. He then progressed to roles with increasing responsibility, serving as a Software Engineer/Product Architect at Aerohive Networks, Inc. from June 2006 to September 2014, focusing on networking solutions. Subsequently, Dr. Li joined ArcSoft (Hangzhou) Technology Co., Ltd. as a Product Architect from June 2014 to June 2018, where he contributed to product development and architecture. His entrepreneurial spirit led him to co-found Hangzhou Zijie Technology Co., Ltd., where he served as Technical Co-founder from June 2018 to 2021, involved in the strategic and technical leadership of the company. Throughout his career, Dr. Li has demonstrated expertise in Python, C++, and C, alongside a profound understanding of networking, Internet of Things, machine learning/deep learning, cybersecurity, and big data applications.

Research Interests:

Dr. Jing Li’s research interests are centered around several key areas in computer science and technology. His primary focus lies in networking, where he explores advancements in network protocols, architectures, and performance optimization. Dr. Li is also deeply engaged in the Internet of Things (IoT), investigating methods to enhance IoT device connectivity, security, and data management. His expertise extends to machine learning and deep learning applications, particularly in developing intelligent algorithms for data analysis and decision-making processes. Additionally, Dr. Li is passionate about cybersecurity, researching techniques to safeguard networks and IoT ecosystems from emerging threats. Finally, he explores big data analytics, aiming to develop scalable and efficient algorithms for processing and extracting valuable insights from large datasets.

Skills:

Dr. Jing Li is equipped with a comprehensive skill set that spans diverse areas within computer science and technology. His expertise includes advanced proficiency in networking, encompassing thorough knowledge of network protocols, architectures, and optimization strategies. Dr. Li demonstrates a deep understanding of Internet of Things (IoT), where he excels in enhancing device connectivity, ensuring robust security measures, and optimizing data management systems. His proficiency extends to machine learning and deep learning, where he develops and implements sophisticated algorithms for data analysis and decision-making tasks. Additionally, Dr. Li is adept in cybersecurity practices, employing effective techniques to safeguard networks and IoT environments from evolving threats. His skills in big data analytics enable him to design and implement scalable algorithms that efficiently process and derive valuable insights from large datasets. With fluency in programming languages such as Python, C++, and C, Dr. Li leverages his technical acumen to drive innovation and contribute significantly to research and development initiatives in his field.

Peer Reviewer in Journals:

Dr. Jing Li has served as a peer reviewer for prestigious journals in the fields of computer and electrical engineering. His expertise as a reviewer extends to journals such as Expert Systems With Applications, Knowledge-Based Systems, Journal of Ambient Intelligence and Humanized Computing, Journal on Internet of Things, International Journal of Electrical and Computer Engineering, International Journal on Data Science and Technology, and Journal of Applied Engineering and Technological Science. Through his role, Dr. Li contributes to maintaining the quality and integrity of research in these specialized domains, ensuring rigorous evaluation and feedback for scholarly publications.

Awards & Honors:

Dr. Jing Li has garnered significant recognition for his contributions in computer science and technology. He has served as a peer reviewer for esteemed journals including Expert Systems With Applications, Knowledge-Based Systems, and Journal of Ambient Intelligence and Humanized Computing, among others. In 2023, Dr. Li was appointed as a Professor Assistant for AI-SLR courses at UTM, showcasing his expertise and leadership in the field. His commitment to academic excellence is further underscored by his involvement in committees such as the EGE Committee Technical Team and PARS2023/2024 Committee Publication and Technical Team. In 2024, Dr. Li was honored with the Asian Youth Leaders Scholarship Award, reflecting his outstanding achievements and dedication to advancing research and education in computer and electrical engineering.

Publications:

Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning

  • Authors: J. Li, M.S. Othman, H. Chen, L.M. Yusuf
  • Journal: Journal of Big Data
  • Year: 2024
  • Volume and Issue: 11(1)
  • Pages: 36
  • Citations: 3

Enhancing IoT security: A comparative study of feature reduction techniques for intrusion detection system

  • Authors: J. Li, H. Chen, M.O. Shahizan, L.M. Yusuf
  • Journal: Intelligent Systems with Applications
  • Year: 2024
  • Volume and Issue: 23
  • Article Number: 200407
  • Citations: 0

A critical review of feature selection methods for machine learning in IoT security

  • Authors: J. Li, M.S. Othman, H. Chen, L.M. Yusuf
  • Journal: International Journal of Communication Networks and Distributed Systems
  • Year: 2024
  • Volume and Issue: 30(3)
  • Pages: 264-312
  • Citations: 0