Madhu Biyani | Electrochemical Biosensors | Best Researcher Award

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Assist Prof. Dr. Madhu Biyani | Electrochemical Biosensors | Best Researcher Award

Assist Prof. Dr. Madhu Biyani, Kanazawa University, Japan

Dr. Madhu Biyani is a physician and bioengineer from India, currently serving as Assistant Professor at NanoLSI, Kanazawa University, Japan. With a doctorate in bioengineering from Saitama University, her expertise lies in drug metabolism and electrochemical biosensors. She bridges clinical insight with molecular biology, contributing to research on peptide aptamers for targeted diagnostics. Her interdisciplinary work enriches biomedical innovation, especially in precision medicine. Fluent in Japanese and English, Dr. Biyani’s global academic and research journey exemplifies scientific excellence and cross-cultural collaboration. 🌏

👩‍⚕️ Profile

Scopus

🎓 Education

Dr. Biyani completed her Bachelor of Homoeopathic Medicine and Surgery (B.H.M.S.) from the University of Rajasthan in 2000. She then pursued her Ph.D. in Bioengineering at Saitama University, Japan, in 2011. Her doctoral thesis focused on enhancing protease activity using peptide aptamers for drug discovery applications. She also holds JLPT Level N3 certification, demonstrating proficiency in Japanese. Her educational path reflects a strong integration of clinical medicine and molecular engineering—forming the basis of her impactful biosensor and drug metabolism research. 🎓

đź’Ľ Experience

Dr. Biyani has over 15 years of experience in biomedical research across academia and industry. She has worked in premier Japanese projects such as REDS (JST), City Area, and Sentan, focusing on biomolecule design and diagnostics. Her tenure includes research roles in Saitama University, JAIST, and Toyama Prefectural University. She also contributed to a private biotech firm, BioDevice Technology Ltd. Since 2020, she’s held a faculty position at NanoLSI, where she leads drug metabolism and toxicology studies. Her career reflects a diverse, well-rounded scientific journey from bench to bedside. 🔬

🔬 Research Interest

Dr. Biyani’s research focuses on drug metabolism, toxicology, peptide aptamer development, and electrochemical biosensors. She is passionate about translating molecular tools into clinically actionable platforms, enabling real-time monitoring of enzymatic activity and drug responses. Her work integrates nanotechnology, molecular biology, and analytical chemistry—providing precision tools for early disease detection and safer drug therapies. She is particularly interested in using biosensors for evaluating liver enzyme functions and metabolic pathways, which can revolutionize personalized medicine. ⚗️

🏅 Awards

While Dr. Biyani has not yet received high-profile awards, she is an emerging talent with significant contributions to Japanese and international biomedical research. Her involvement in multiple Japanese Science and Technology Agency (JST) projects and her role in developing clinical biosensing platforms position her as a strong contender for research recognition. Her cross-disciplinary and multicultural profile makes her an ideal candidate for young researcher, women in science, and bioengineering innovation awards. 🌟

đź“š Publication Top Notes

“Protease Activity-Enhancing Peptide Aptamer Development”

“Application of Electrochemical Biosensors in Drug Toxicity Screening”

“Design of Aptamer-Based Platforms for Drug Metabolism Analysis”

Farzaneh Rastegari | DNA isolation and PCR amplification approaches | Best Researcher Award

Posted on by Biophotonics Research

Mrs. Farzaneh Rastegari | DNA isolation and PCR amplification approaches | Best Researcher Award

Graduate at University of Connecticut, United States

Farzaneh (Dana) Rastegari is a dedicated researcher in computational biology and bioinformatics, specializing in microbiome analysis, machine learning, and genomics. With a strong foundation in computer science and engineering, she applies computational and statistical methods to analyze microbial communities and their interactions. Her interdisciplinary expertise spans software development, wet lab techniques, and data analytics, making her a valuable contributor to biomedical research.

Profile 

Scopus

Education 🎓

Farzaneh is currently pursuing her Ph.D. in Computer Science and Engineering at the University of Connecticut (UConn), where she maintains an impressive GPA of 3.88/4.0. She previously earned her M.S. in Electrical and Computer Engineering from the University of New Haven (UNH), focusing on communication networks. Her academic journey began with a B.S. in Computer Science, specializing in robotics, from Amirkabir University of Technology (Tehran Polytechnic).

Experience đź’Ľ

As a Predoctoral Associate at The Jackson Laboratory, Farzaneh conducts extensive microbiome research involving wet lab methodologies, data processing, statistical analysis, and pipeline development. Her work at UConn includes computational genomics, Bayesian machine learning, and artificial intelligence applications in bioinformatics. Additionally, her past experience at UNH and AUT includes projects in signal processing, communication networks, and robotics, demonstrating her versatility in multiple research domains.

Research Interests 🔬

Farzaneh’s research focuses on bioinformatics, genomics, computational biology, machine learning, and artificial intelligence. Her work in microbiome research explores microbial community interactions, statistical modeling, and algorithm development for genomic data analysis. She is also passionate about evolutionary genomics, phylogenetic analysis, and predictive modeling in biomedical research.

Awards & Achievements 🏆

  • Awarded Predoctoral Fellowship at UConn’s Computer Science and Engineering department.
  • Received the Summer Doctoral Dissertation Fellowship from the Graduate School at UConn.
  • Ranked as the top student in her M.S. program at UNH, holding the highest GPA in her class.
  • Ranked among the top three students in her B.S. program at AUT.
  • Member of the Parsian Robotic team, ranked among the top 20 teams worldwide in small-size soccer robots (Robocup, Atlanta, USA).
  • Secured the 14th position in the world ranking for small-size soccer robots at Robocup, Bremen, Germany.
  • Achieved second place in ACM/ICPC line follower robots competition (Sharif University of Technology, Tehran, Iran).
  • Ranked in the 99.8 percentile among over 600,000 students in Iran’s national university entrance exam.
  • Selected for NODET (National Organization for Development of Exceptional Talents), Iran.
  • Certified in CPR, first aid, and emergency care.
  • Holds a second-dan certificate from Kukkiwon’s Taekwondo Association, South Korea.

Publications đź“š Published:

  • Metagenomics and Chemotherapy-Induced Nausea: A Roadmap for Future Research
    • Authors: Crowder, S. L., Hoogland, A. I., Welniak, T. L., LaFranchise, E. A., Carpenter, K. M., Li, D., Rotroff, D. M., Mariam, A., Pierce, C. M., Fischer, S. M., Kinney, A. Y., Rastegari, F., Weinstock, G. M., Jim, H. S. L.
    • Year: 2022
  • Predictive Modeling of Chronic Kidney Disease Progression Using Longitudinal Clinical Data and Deep Learning Techniques
    • Authors: Rastegari, F., Odeh, M., Baroughi, R. M., Bustan, A.
    • Year: 2023
  • Exploring the Relationship between Air Pollution and CNS Disease Mortality in Italy: A Forecasting Study with ARIMA and XGBoost
    • Authors: Karimi, M., Hamzehei, S., Rastegari, F., Akbarzadeh, O.
    • Year: 2023
  • A Comprehensive Simulation of Electric Vehicle Energy Consumption: Incorporating Route Planning and Machine Learning-Based Predictions
    • Authors: Baroughi, R. M., Attar, H., Rastegari, F.
    • Year: 2023
  • Comparison of Lysis and Amplification Methodologies for Optimal 16S rRNA Gene Profiling for Human and Mouse Microbiome Studies
    • Authors: Rastegari, F., Driscoll, M., Riordan, J. D., Nadeau, J. H., Johnson, J. S., Weinstock, G. M.
    • Year: 2025
  • On the Accuracy of HGTs Inference Using Phylogenetic Reconciliation
    • Authors: Rastegari, F., Masi, A., Bansal, M.
    • Year: Year of publication is not specified.

Conclusion

Farzaneh (Dana) Rastegari is an exceptional researcher with a diverse skill set in bioinformatics, microbiome research, AI, and robotics. Her strong technical expertise, multidisciplinary research contributions, and outstanding academic achievements make her a top candidate for the Best Researcher Award. While she already has a strong publication record and international recognition, further interdisciplinary collaborations, high-impact journal publications, and leadership in research grants could further solidify her position as a leading researcher in computational biology and AI-driven genomics.