Bilal Ahmad MIr | Microbial Cell Biology | Best Researcher Award

Mr.Bilal Ahmad MIr | Microbial Cell Biology | Best Researcher Award

Mr.Bilal Ahmad MIr | Jeonbuk National University | South Korea

Bilal Ahmad Mir is a dedicated Ph.D. scholar at the NSCL Lab, Jeonbuk National University, South Korea, with a strong focus on artificial intelligence, machine learning, and computational sciences. Born on May 7, 1993, Bilal has a diverse academic and research background encompassing data science, deep learning, computational biology, and chemistry. He combines technical acumen with innovative thinking to solve real-world scientific problems. Fluent in English, Urdu, and Kashmiri, Bilal’s research is published in leading international journals. He is well-versed in programming languages such as Python, R, MATLAB, and Java, and excels in cloud computing technologies. His scholarly contributions span predictive modeling, neural networks, and intelligent systems. His enthusiasm for technological advancements and interdisciplinary research positions him as a strong candidate for prestigious research awards, reflecting both his scientific rigor and passion for discovery.

Publication Profile:

Google Scholar

✅ Strengths for the Award:

  1. Interdisciplinary Expertise:
    Bilal’s work spans artificial intelligence, deep learning, computational biology, and chemistry, reflecting strong interdisciplinary depth. He has applied advanced ML models like CNNs, LSTMs, and GRUs across bioinformatics and synthetic chemistry, showing his adaptability and scientific creativity.

  2. Research Publications:
    He has published in high-impact journals such as Journal of Molecular Biology, Computational Biology and Chemistry, and Sustainability. These works demonstrate novelty and real-world relevance, e.g., sustainable solar energy prediction and enhancer identification in genomics.

  3. Technical Proficiency:
    Bilal is proficient in multiple programming languages (Python, R, MATLAB, Java, etc.) and research tools, which enhances his capability to design, implement, and optimize advanced computational models.

  4. Academic Progression:
    His academic journey from a B.Sc. through MCA to a Ph.D. in South Korea demonstrates commitment to continuous learning and global academic engagement.

  5. Early Research Experience:
    His MCA project on real-time facial recognition using Raspberry Pi and GSM modules showed practical innovation, integrating software and hardware for applied AI.

⚠️ Areas for Improvement:

  1. Citation and Impact Metrics:
    While Bilal has strong publications, more details on citations, h-index, or conference presentations would strengthen his profile for global competitive awards.

  2. Leadership in Projects:
    Future applications should highlight any mentoring, project leadership, or grant involvement, which are important indicators of research independence.

  3. Community Contribution:
    Participation in open-source contributions, academic societies, or organizing workshops/seminars would further showcase his community engagement and outreach efforts.

  4. Formal Language Polishing:
    Refinement in presenting his resume/CV with consistent formatting and professional tone would improve the impression in award submissions.

🎓 Education:

Bilal Ahmad Mir began his academic journey with a B.Sc. in Mathematics, Electronics, and IT from Sri Pratap College, Srinagar, graduating with 60% in 2016. He then pursued an MCA (Master of Computer Applications) at the Islamic University of Science and Technology, Awantipora, where he excelled in courses like algorithms, AI, ML, data structures, and cloud computing, graduating with a CGPA of 7.76/10 in 2019. He is currently enrolled as a Ph.D. scholar at Jeonbuk National University, South Korea, in the Department of Electronics and Information Engineering. His doctoral work at the NSCL Lab integrates deep learning, computational chemistry, and molecular biology, contributing to high-impact publications. His solid academic foundation and continued pursuit of knowledge equip him with the interdisciplinary expertise necessary to tackle complex computational and AI challenges in life sciences and beyond.

🧪 Experience:

Bilal’s academic and research journey spans across domains of intelligent systems, AI, and computational biology. During his MCA, he completed a dissertation on a real-time “Intelligent Face Recognition System” using Raspberry Pi and Eigenface recognition, integrating image processing with GSM modules. As a Ph.D. researcher at NSCL Lab in South Korea, he has been involved in multiple projects focusing on neural networks, such as CNNs, LSTMs, and GRUs, for bioinformatics and organic chemistry applications. His hands-on experience in deep learning, data preprocessing, and predictive modeling has resulted in several peer-reviewed journal publications. He is proficient in Python, MATLAB, R, and Java and is experienced with research tools used for analyzing genetic and chemical data. Bilal’s versatility across both hardware (e.g., Raspberry Pi) and software research platforms positions him as a highly capable and adaptable scientist in the interdisciplinary field of AI-powered scientific research.

🏆 Awards and Honors:

Bilal Ahmad Mir has received multiple accolades that highlight his academic potential and creative engagement in both academic and extracurricular domains. He secured the 1st rank in a national-level quiz competition organized during the Digital India Week in 2015, reflecting his strong grasp of technical knowledge and current affairs. During his post-graduate studies, he was honored with the title of “Mr. Fresher” for the MCA batch of 2016 at the Islamic University of Science and Technology, recognizing his leadership and interpersonal qualities. His growing contribution to impactful scientific research has earned him recognition among academic peers. With peer-reviewed publications in top-tier journals and ongoing contributions to AI-driven biological and chemical modeling, Bilal is on a trajectory of continued academic success. These honors reflect both his intellect and his dedication to continuous learning and innovation, making him a strong contender for prestigious awards such as the Best Researcher Award.

🔬 Research Focus:

Bilal Ahmad Mir’s research focus lies at the confluence of artificial intelligence, deep learning, and life sciences. He applies cutting-edge machine learning techniques—particularly CNNs, LSTMs, and GRUs—to computational biology and chemistry, aiming to solve intricate molecular problems. His key research areas include enhancer identification, RNA modification prediction, and retrosynthetic pathway modeling. Through deep learning architectures and stacked ensemble models, he enhances the accuracy of biological predictions and synthesis pathway generation. His recent work also explores sustainable energy research, applying AI to predict recombination losses in perovskite solar cells. Bilal’s interdisciplinary work is distinguished by its practical application to genomics, cheminformatics, and renewable energy, blending technical rigor with scientific curiosity. His aim is to use AI not only for theoretical insights but also for impactful innovations in healthcare, sustainable energy, and synthetic biology. This makes him a versatile and forward-thinking researcher in the modern AI landscape.

📚 Publication Titles Top Notes:

  1. 🧬 Improving enhancer identification with a multi-classifier stacked ensemble model – Journal of Molecular Biology, 2023

  2. 🔄 Sb-net: Synergizing CNN and LSTM networks for uncovering retrosynthetic pathways in organic synthesis – Computational Biology and Chemistry, 2024

  3. 🔋 Toward Sustainable Solar Energy: Predicting Recombination Losses in Perovskite Solar Cells with Deep Learning – Sustainability, 2025

  4. 🧪 GRU-Based Prediction of RNA 5-Hydroxymethylcytosine Modifications – 정보 및 제어 논문집

🧾 Conclusion:

Bilal Ahmad Mir is a highly promising and emerging researcher in the AI-bioinformatics interface. His dedication to interdisciplinary research, proven publication record, and hands-on approach to complex problems make him a strong candidate for the Best Researcher Award. With ongoing contributions, especially in deep learning for biology and sustainable energy, and with slight enhancements in scientific communication and visibility, he is on a trajectory toward impactful global research leadership.

Lijuan Deng | Molecular Mechanisms Signaling | Molecular Cell Biology Award

Mrs. Lijuan Deng | Molecular Mechanisms Signaling | Molecular Cell Biology Award

Mrs. Lijuan Deng , Zhongshan Institute for Drug Discovery , China

Lijuan Deng is a passionate graduate student researcher at the Zhongshan Institute for Drug Discovery in China, specializing in the molecular mechanisms underlying metabolic diseases. Her scientific curiosity centers on gene regulation, signaling pathways, and metabolic dysregulation in disease progression, particularly metabolic-associated fatty liver disease (MASLD). Her translational approach blends experimental models and bioinformatics to bridge basic science and therapeutic innovation. Lijuan has already co-authored a publication in The FASEB Journal, identifying CDKN1A as a key regulator in MASLD. She is also the inventor of a patent-pending technique for nascent RNA labeling in extracellular vesicles. Through collaborations with clinical researchers and a solid foundation in molecular biology techniques, she is positioning herself as a rising talent in cell biology. Her work promises to advance understanding and treatment of metabolic diseases.

Publication Profile:

Orcid

✅ Strengths for the Award:

  1. Innovative Research: Lijuan Deng has significantly contributed to the understanding of MASLD (Metabolic-Associated Steatotic Liver Disease) by identifying CDKN1A as a key regulatory gene through integrated transcriptomic analysis and experimental validation.

  2. Translational Focus: Her research bridges molecular biology and clinical application, enhancing its impact in drug discovery and disease diagnostics.

  3. Publication Record: She is the first author of a peer-reviewed article published in The FASEB Journal (SCI-indexed), showcasing her ability to conduct and communicate high-quality research.

  4. Patent Innovation: She holds a pending patent for a novel method involving nascent RNA labeling in extracellular vesicles, showing her drive toward technological advancement and biomedical innovation.

  5. Collaborative Approach: Active collaboration with the Department of Endocrinology at Shenzhen Second People’s Hospital reflects strong interdisciplinary and clinical integration.

🧩 Areas for Improvement:

  1. Expanded Publication Portfolio: Increasing the number of peer-reviewed articles will strengthen her academic visibility and impact.

  2. Professional Networking: Engagement in international cell biology societies or conferences and obtaining professional memberships can support broader recognition and growth.

  3. Editorial/Leadership Roles: Participation in editorial boards, review panels, or student leadership roles can enrich her professional development profile.

🎓 Education:

Lijuan Deng is currently pursuing her graduate studies in molecular biology at the Zhongshan Institute for Drug Discovery, where she focuses on translational biomedical research. Her academic foundation includes advanced coursework in biochemistry, molecular genetics, and cellular signaling. Through structured academic training, she has acquired proficiency in modern laboratory methods, including RNA sequencing, qPCR, western blotting, and exosome analysis. Her education emphasizes critical thinking and scientific rigor, enabling her to design experiments, analyze data, and interpret biological outcomes. She regularly participates in academic seminars, journal clubs, and collaborative workshops to refine her scientific acumen. Her thesis research is centered around identifying novel molecular targets in MASLD, a field gaining global relevance. Lijuan’s education is not only shaping her technical capabilities but also nurturing her ambition to contribute to impactful, real-world medical solutions through cell biology research.

💼 Experience:

Lijuan Deng has gained extensive laboratory experience as a graduate student researcher at the Zhongshan Institute for Drug Discovery. Her hands-on work includes both cellular and animal models, with a strong focus on metabolic disease mechanisms. She played a key role in identifying CDKN1A as a potential MASLD progression factor, combining transcriptomic data analysis with molecular validation. Additionally, she has worked on exosome-based biomarker discovery and developed a patent-pending method for nascent RNA labeling. She collaborates with the Department of Endocrinology at Shenzhen Second People’s Hospital, providing a clinical dimension to her work. Though early in her career, her contributions to translational research are already making an impact. She is skilled in molecular biology, gene expression profiling, and therapeutic target screening. Her research experience has been shaped by interdisciplinary collaboration, scientific publications, and the ambition to innovate within the field of molecular cell biology.

🧬 Research Focus:

Lijuan Deng’s research is primarily focused on the molecular underpinnings of metabolic-associated fatty liver disease (MASLD), a key manifestation of metabolic syndrome. She investigates how dysregulated genes, signaling networks, and lipid metabolism contribute to disease initiation and progression. A major highlight of her work is identifying CDKN1A as a potential risk factor in MASLD using integrated bioinformatics and experimental techniques. Additionally, she explores the utility of extracellular vesicles as carriers of diagnostic biomarkers and therapeutic molecules. Her patent-pending work involves a novel method for labeling nascent RNA within exosomes, opening possibilities for tracking dynamic RNA communication in disease contexts. Her research strategy merges molecular biology with disease modeling, aiming to bridge laboratory discoveries with potential therapeutic strategies. Through strong collaborations and a translational research outlook, Lijuan is dedicated to uncovering actionable insights that can inform drug development for complex metabolic disorders.

📚 Publications Top Notes:

  • 🧾 “Identification of CDKN1A as a potential key risk factor in MASLD progression.”The FASEB Journal, 2025. DOI: 10.1096/fj.202402942R

🧾 Conclusion:

Lijuan Deng stands out as an emerging researcher with strong foundations in molecular cell biology and a clear orientation toward translational science. Her innovative work in MASLD, combined with an SCI publication and a pending patent, make her a highly suitable and promising candidate for the Molecular Cell Biology Award. While she is in the early stages of her career, her achievements thus far indicate substantial potential for future contributions to the field.