Mr. Rameez Hassan Pirzada | Research and development | Best Researcher Award

Mr. Rameez Hassan Pirzada | Research and development | Best Researcher Award

Ajou University, South Korea

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Early Academic Pursuits đź“š

Rameez Hassan Pirzada’s academic journey began with a Bachelor of Science in Bioinformatics from Capital University of Science and Technology in Islamabad, Pakistan, where he developed a keen interest in the molecular and computational aspects of biological sciences. His early research focused on the development of genome annotation software, a fundamental tool in bioinformatics that would later serve as a springboard for his future research endeavors.

Building on his passion for medical biology, Rameez went on to pursue a Master of Science in Medical Biology and Genetics from Yakın Doğu Üniversitesi in Mersin, Turkey. His thesis on telomere length dynamics in patients with recurrent pregnancy loss was a significant milestone in his academic career, leading to a publication in the International Journal of Biological Macromolecules. This early work honed his skills in molecular biology and bioinformatics, laying a strong foundation for his future academic and professional pursuits.

Professional Endeavors 🧑‍🔬

Since March 2019, Rameez has been serving as a Research Fellow at Ajou University in Suwon, South Korea, where he is involved in cutting-edge research in computational biology. He has developed advanced QSAR models to identify IL1R1 and IL-1β inhibitors, which are currently being tested in vitro and in preclinical studies. His innovative use of transfer learning in drug discovery has opened up new pathways for targeting critical molecular interactions in inflammatory and viral diseases. His work on designing VEGF peptide agonists using LSTM-based deep learning algorithms has achieved promising in vitro results, with animal testing planned and potential for patent filing.

Rameez’s dedication to finding novel solutions for pressing health issues is also reflected in his antiviral drug repurposing research, which identified FDA-approved drugs with potential to inhibit SARS-CoV-2 replication. This groundbreaking work was published in Cells, further solidifying his standing as an emerging leader in the field of computational drug discovery.

Contributions and Research Focus 🔬

Rameez’s research has made significant contributions to various therapeutic areas, including viral infections, inflammation, and cancer. His focus on structure-activity relationships (SAR) for COVID-19 therapeutics targeting GSK3 was a pivotal moment in his career, published in Frontiers in Endocrinology. His research on protein-protein interactions and molecular dynamics simulations has paved the way for the development of effective therapeutic agents by understanding the underlying mechanisms of diseases.

In addition to his work on drug discovery, Rameez’s deep expertise in molecular dynamics simulations and machine learning has led to the development of sophisticated computational models that predict the efficacy of novel drug candidates. By combining AI with traditional pharmacological methods, Rameez is at the forefront of a new wave of precision medicine and targeted therapies.

Accolades and Recognition 🏆

Rameez Hassan Pirzada’s academic and professional achievements have garnered significant recognition. His publications in high-impact journals such as the International Journal of Biological Macromolecules, Frontiers in Endocrinology, and Cells showcase the quality and impact of his work in the global scientific community. His research on IL1R1 and IL-1β inhibitors is currently under revision with the International Journal of Biological Macromolecules, further emphasizing the credibility and potential of his contributions.

Beyond his research, Rameez’s role as a lecturer in Bioinformatics at the University of Lahore, Pakistan, speaks to his ability to communicate complex scientific concepts to students, contributing to the development of future professionals in bioinformatics and computational biology.

Impact and Influence 🌍

Rameez’s work has had a profound impact on the scientific community, particularly in the field of computational drug discovery. His research on SARS-CoV-2 has not only contributed to the global response to the pandemic but also highlighted the potential of repurposing existing drugs to combat emerging infectious diseases. Furthermore, his development of AI-driven drug discovery models has the potential to accelerate the development of new therapies for a range of diseases, from cancer to autoimmune disorders.

Through his work, Rameez has also made significant contributions to systems biology, using computational tools to uncover the intricate cellular processes that drive disease. His deep understanding of protein interactions and his ability to model these interactions computationally has positioned him as a leading figure in drug design and molecular pharmacology.

Legacy and Future Contributions 🌱

As Rameez continues to push the boundaries of computational biology, his future contributions are poised to reshape the landscape of drug discovery. His dedication to innovation, coupled with his passion for mentorship, ensures that his legacy will extend beyond his own research. By training the next generation of bioinformatics professionals and continuing to develop novel therapeutic strategies, Rameez is paving the way for a new era of precision medicine.

Looking ahead, Rameez is committed to advancing his research in AI-driven drug discovery, particularly in the fields of inflammation, cancer, and infectious diseases. His ability to integrate machine learning with molecular biology offers exciting possibilities for developing targeted therapies that will revolutionize how we approach drug development and disease treatment.

Rameez Hassan Pirzada’s journey is one of relentless curiosity, groundbreaking contributions, and a commitment to transforming healthcare through the power of computational biology. With his expertise and forward-thinking approach, he is well on his way to making an indelible mark on the scientific community and improving global health outcomes for generations to come.

đź“ťNotable Publications

Wnt signaling in the regulation of immune cell and cancer therapeutics

Authors: M. Haseeb, R.H. Pirzada, Q.U. Ain, S. Choi

Journal: Cells

Year: 2019

The roles of the NLRP3 inflammasome in neurodegenerative and metabolic diseases and in relevant advanced therapeutic interventions

Authors: R.H. Pirzada, N. Javaid, S. Choi

Journal: Genes

Year: 2020

Remdesivir and ledipasvir among the FDA-approved antiviral drugs have potential to inhibit SARS-CoV-2 replication

Authors: R.H. Pirzada, M. Haseeb, M. Batool, M.S. Kim, S. Choi

Journal: Cells

Year: 2021

Role of TRF2 and TPP1 regulation in idiopathic recurrent pregnancy loss

Authors: R.H. Pirzada, O. Orun, C. Erzik, H. Cagsin, N. Serakinci

Journal: International Journal of Biological Macromolecules

Year: 2019

Modeling structure–activity relationships with machine learning to identify GSK3-targeted small molecules as potential COVID-19 therapeutics

Authors: R.H. Pirzada, B. Ahmad, N. Qayyum, S. Choi

Journal: Frontiers in Endocrinology

Year: 2023

 

Prof Dr. Genggeng Liu | Innovative Leadership | Best Researcher Award |} 2825

Prof Dr. Genggeng Liu | Innovative Leadership | Best Researcher Award

Prof Dr. Genggeng Liu, Fuzhou University, China

đź”— Professional Profiles

🎓 Academic Qualifications

  • Ph.D. in Mathematics and Computer Science, Fuzhou University, China
    Sep. 2009 – Mar. 2015
  • B.S. in Mathematics and Computer Science, Fuzhou University, China
    Sep. 2005 – Jul. 2009

👨‍🏫 Academic Positions

  • Full Professor, College of Computer and Data Science, Fuzhou University
    Sep. 2023 – present
  • Associate Professor, College of Computer and Data Science, Fuzhou University
    May. 2021 – Sep. 2023
  • Associate Professor, College of Mathematics and Computer Science, Fuzhou University
    Jul. 2018 – May. 2021
  • Lecturer, College of Mathematics and Computer Science, Fuzhou University
    Jul. 2015 – Jul. 2018

🏅 Honors & Recognitions

  • Fujian Outstanding Young Scholars
  • Fujian High Level Talents (C-Level)

đź“š Selected Publications

  • Fault-Tolerance-Oriented Physical Design for Fully Programmable Valve Array Biochips
    G. G. Liu, Y. H. Zhu, W. Z. Guo, and X. Huang
    Proceedings of ACM/IEEE Design Automation Conference (DAC), 2023, pp. 1-6.
  • Control-Logic Synthesis of Fully Programmable Valve Array Using Reinforcement Learning
    X. Huang, H. Y. Cai, W. Z. Guo, G. G. Liu, T.-Y. Ho, K. Chakrabarty, and U. Schlichtmann
    IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 43, no. 1, pp. 277-290, 2024.
  • Design Automation for Continuous-Flow Microfluidic Biochips: A Comprehensive Review
    G. G. Liu, H. B. Huang, Z. S. Chen, H. X. Lin, H. Liu, X. Huang, and W. Z. Guo
    Integration-the VLSI Journal (INTEGRATION), vol. 82, pp. 48-66, 2022.
  • Adaptive Control-Logic Routing Flow for Fully Programmable Valve Array Using Deep Reinforcement Learning
    H. Y. Cai, G. G. Liu*, W. Z. Guo, Z. P. Li, T.-Y. Ho, and X. Huang
    Asia and South Pacific Design Automation Conference (ASP-DAC), 2024, pp. 564-569.
  • Towards Automated Testing of Multiplexers in Fully Programmable Valve Array Biochips
    G. G. Liu, Y. Q. Zeng, Y. H. Zhu, H. Y. Cai, W. Z. Guo, Z. P. Li, T.-Y. Ho, and X. Huang

Dr. Genggeng Liu is a prominent figure in the field of computer and data science, particularly known for his contributions to the design and automation of microfluidic biochips. His work has significantly advanced fault-tolerant design and control-logic synthesis, employing cutting-edge techniques such as reinforcement learning. Dr. Liu’s research has been recognized through prestigious publications and numerous awards, underscoring his impact on the academic and scientific community.

Publication Top Noted

Paper Title : Multilayer obstacle-avoiding X-architecture Steiner minimal tree construction based on particle swarm optimization

    • Authors: Genggeng Liu, Xing Huang, Wenzhong Guo, Yuzhen Niu, Guolong Chen
    • Journal: IEEE Transactions on Cybernetics
    • Year: 2015
    • Citations : 97

Paper Title : A PSO-based timing-driven Octilinear Steiner tree algorithm for VLSI routing considering bend reduction

    • Authors:Genggeng Liu, Wenzhong Guo, Yuzhen Niu, Guolong Chen, Xing Huang
    • Journal: Soft Computing 
    • Year: 2015
    • Citations:  87

Paper Title : A unified algorithm based on HTS and self-adapting PSO for the construction of octagonal and rectilinear SMT

    • Authors: Genggeng Liu, Zhisheng Chen, Zhen Zhuang, Wenzhong Guo, Guolong Chen
    • Journal: Soft Computing
    • Year: 2020
    • Citations:  85

Paper Title :Obstacle-avoiding algorithm in X-architecture based on discrete particle swarm optimization for VLSI design

    • Authors: He, X.-H., Shi, Y.-Y., Zhou, X.-L., …, Zhang, Z.-K., Huang, Q.-C.
    • Journal: ACM Transactions on Design Automation of Electronic Systems (TODAES)
    • Year: 2015
    • Citations: 70

Paper Title : A hybrid multi-objective PSO algorithm with local search strategy for VLSI partitioning

    • Authors: Wenzhong Guo, Genggeng Liu, Guolong Chen, Shaojun Peng
    • Journal: Frontiers of Computer Science
    • Year: 2014
    • Citations: 58