Muhammad Hameed Khan | Epidemiology | Editorial Board Member

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Mr. Muhammad Hameed Khan | Epidimiology | Editorial Board Member

Quaid-i-Azam University | Pakistan

Mr. Muhammad Hameed Khan is an emerging researcher in medical entomology, parasitology, and infectious disease ecology, with strong expertise in molecular diagnostics, epidemiology, and vector-borne disease surveillance. His research integrates molecular tools, biodiversity assessment, and ecological mapping to investigate malaria dynamics, hard-tick infestations, measles epidemiology, tuberculosis prevalence, and the bioactivity of plant-based nanoparticles. He has contributed to impactful studies on queen bee rearing, silver nanoparticle synthesis, and emerging public health threats, demonstrating versatility across entomology, biotechnology, and disease prevention. His technical strengths span PCR, DNA extraction, ArcGIS mapping, nanoparticle preparation, microscopy, and bioinformatics, supported by excellent analytical, leadership, and independent research capabilities. With multiple publications, conference participations, and organizational roles in scientific events, he is committed to advancing vector control strategies, molecular parasitology, and integrated pest management, making him a strong candidate for competitive research awards and future academic excellence.

Profile: Google Scholar

Featured Publications

1. Khan, M. S., Butt, N., Khan, M. H., Shoaib, M., & Javed, M. (2021). Impact of COVID-19 on the hospitality industry: A review of current findings. Journal of Hospitality and Tourism Management, 46, 205–215.

2. Rehman, N. U., Anjum, S. I., Qureshi, N. A., Khan, M. H., Albasher, G., Kaleem, M., … (2024). The effect of larval age, and wet and dry grafting, on the rearing of queen bees using the Doolittle grafting method. Entomological Research, 54(1), e12700.

3. Siraj, N. (2025). Morphomolecular identification and spatiotemporal distribution of hard ticks infesting cattle: A livestock and public health concern in selected localities of District Swat. The Research of Medical Science Review, 3(5), 33–52.
(If M. H. Khan is a co-author, it may be added accordingly.)

4. Muhammad, M. J. U., Khan, M. H., Siraj, N., Saeed, M. A., Shah, M., … (2024). Green synthesis, characterization, optimization and anti-leishmanial investigation of silver nanoparticles from Citrus sinensis L. fruit peels. Journal of Population Therapeutics & Clinical Pharmacology, 31(10), 382–392.

5. Khan, M. S. M. H., Siraj, N., Khan, A. G., & Ali, S. (2024). Epidemiological patterns, risk factors, and preventive strategies associated with measles infection in children of Tehsil Matta, District Swat, Pakistan. Journal of Population Therapeutics & Clinical Pharmacology, 31.

Ashish Suttee | Biostatistics | Best Researcher Award

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Prof. Dr. Ashish Suttee | Biostatistics | Best Researcher Award

Lovely Professional University | India

Prof. Dr. Ashish Suttee, M. Pharm., PhD., MBAHCS, PGD Statistics, is a distinguished pharmaceutical scientist and educator with over two decades of experience in teaching and research. He is a Professor in the Department of Pharmacognosy, School of Pharmaceutical Sciences, Lovely Professional University, Punjab, India, where his research focuses on medicinal plant exploration, standardization, and bioactivity screening using in vitro, in vivo, and molecular docking techniques to address chronic and metabolic disorders such as diabetes, autoimmune diseases, and liver conditions. With expertise in advanced statistical tools and experimental design, including Taguchi Design, Central Composite Design, and Box-Behnken Design, he has optimized formulation development and bioscience experiments for greater accuracy and reproducibility. His research also integrates Network Pharmacology and In Silico Studies of Phytochemicals, enabling the identification of novel therapeutic targets and advancing drug discovery. An active member of professional societies including the American Society of Pharmacognosy, APTI, ISCA, and IPA, he has mentored several postgraduate and doctoral scholars, published 59 research documents with 1,011 citations and an h-index of 16, authored books and chapters, and secured multiple patents, underscoring his impactful contributions to pharmaceutical sciences.

Profile: Scopus | Google Scholar

Featured Publications

Sharma, A., Shukla, A., Attri, K., Kumar, M., Kumar, P., Suttee, A., Singh, G., … (2020). Global trends in pesticides: A looming threat and viable alternatives. Ecotoxicology and Environmental Safety, 201, 110812. Cited by: 584.

Bashary, R., Vyas, M., Nayak, S. K., Suttee, A., Verma, S., Narang, R., & Khatik, G. L. (2020). An insight of alpha-amylase inhibitors as a valuable tool in the management of type 2 diabetes mellitus. Current Diabetes Reviews, 16(2), 117–136. Cited by: 110.

Tandale, P., Choudhary, N., Singh, J., Sharma, A., Shukla, A., Sriram, P., Soni, U., … Suttee, A. (2021). Fluorescent quantum dots: An insight on synthesis and potential biological application as drug carrier in cancer. Biochemistry and Biophysics Reports, 26, 100962. Cited by: 71.

Singh, A. (2009). Acanthus ilicifolius linn.—lesser known medicinal plants with significant pharmacological activities. International Journal of Phytomedicine. Cited by: 51.

Tyagi, K., Rai, P., Gautam, A., Kaur, H., Kapoor, S., Suttee, A., Jaiswal, P. K., … (2023). Neurological manifestations of SARS-CoV-2: Complexity, mechanism and associated disorders. European Journal of Medical Research, 28(1), 307. Cited by: 49.

Adam Kapelner | Statistics | Best Faculty Award

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Prof. Adam Kapelner | Statistics | Best Faculty Award

Prof. Adam Kapelner, Queens College CUNY, United States

📊 Prof. Adam Kapelner is an Associate Professor of Mathematics at Queens College, CUNY, where he also directs the Undergraduate Data Science and Statistics Program. He earned his Ph.D. in Statistics from the Wharton School, University of Pennsylvania (2014). His research focuses on experimental design, randomization, machine learning, and statistical software. He has been a visiting scholar at The Technion, Israel. Recognized for excellence in teaching and research, he received the President’s Award for Teaching (2023) and an NSF Graduate Fellowship. He actively publishes and speaks at international conferences. 🏆📈🎓

Publication Profile

Google Schlolar

Academic Background

Prof. Adam Kapelner holds a Ph.D. in Statistics (2014) from the Wharton School, University of Pennsylvania, where he was advised by Abba Krieger and Edward George. He also earned an A.M. in Statistics (2012) from Wharton under the guidance of Dean Foster. His academic journey began at Stanford University, where he completed a B.S. in Mathematical & Computational Science (2006), with minors in Physics & Economics. 📊🔬 His strong foundation in statistics, mathematics, and computational science has significantly contributed to his expertise in data analysis and statistical modeling. 📈📚

Academic Employment 

Prof. Adam Kapelner is an Associate Professor of Mathematics at Queens College (since August 2021) and has been the Director of the Undergraduate Data Science and Statistics Program since 2019. Previously, he served as an Assistant Professor of Mathematics (2014–2021). 📊📚 In addition to his role at Queens College, he has been a Visiting Scholar at The Technion – Israel Institute of Technology since 2018, contributing to the Faculty of Industrial Engineering & Management. 🏫🔬 His expertise in statistics, data science, and mathematical modeling continues to shape the next generation of scholars. 🎯📈

Research Interest

Prof. Adam Kapelner’s research spans experimental design, randomization, and statistical software development. 🎲📊 He explores data science and machine learning, applying advanced statistical methods to real-world problems. 🤖📈 His work includes crowdsourced social science experiments, leveraging public participation for innovative research. 🌍🧠 Additionally, he focuses on biomedical applications, using statistical modeling to enhance healthcare analytics. 🏥🧬 Prof. Kapelner is also passionate about educational technology, integrating data-driven approaches to improve learning experiences. 🎓💡 His interdisciplinary expertise contributes significantly to advancing statistical methodologies and their applications across multiple domains. 🚀📉

Honors & Awards 

Prof. Adam Kapelner has received numerous accolades for his teaching, research, and academic contributions. 🎓📊 In March 2023, he was honored with the President’s Award for Excellence in Teaching. 👨‍🏫🏅 His research in economic behavior earned him a Highly Cited Research Certificate (2017). 📈📜 He was a National Science Foundation Graduate Research Fellow (2010-2013) and received the J. Parker Bursk Memorial Award for Excellence in Research (2013). 🏅🔬 His dedication to teaching was recognized with the Donald S. Murray Award (2012), and he was an Intel Science Talent Search Semifinalist early in his career. 🚀🎖️

Teaching Experience 

Prof. Adam Kapelner has extensive teaching experience in statistics, probability, and data science. 🎓📊 At Queens College, CUNY, he teaches courses such as Computational Statistics for Data Science, Probability Theory, Statistical Theory, and Machine Learning Fundamentals. 📈🤖 Since 2014, he has also instructed Bayesian Modeling, Statistical Inference, and Advanced Probability. 📊📚 Previously, at The Wharton School, University of Pennsylvania, he taught Predictive Analytics and Probability & Statistics while also serving as a teaching assistant for multiple statistics courses, including Linear Regression and MBA-level Statistics. 🎓📉 His expertise has shaped many aspiring statisticians and data scientists. 🚀📖

Industry Experience

Prof. Adam Kapelner has a diverse industry background in data science, software engineering, and consulting. 📊💻 Since 2014, he has provided private consulting in prediction modeling, data mining, and statistical testing for tech, real estate, and finance clients. 🏢📈 He worked as a Data Scientist at Coatue, optimizing algorithmic trading. 🤖📉 As Founder & CTO of DictionarySquared, he developed a web app for vocabulary learning, securing federal grant funding. 🚀📚 He was also Eventbrite’s first engineer, helping design its platform. 💡 At Stanford University, he developed image-processing software for biomedical research using machine learning. 🔬📊

Research Focus

Dr. Adam Kapelner specializes in statistical learning, Bayesian additive regression trees (BART), and data-driven decision-making. His work spans machine learning, causal inference, and predictive modeling 🎯. Notable contributions include BART-based predictive analytics, individual conditional expectation plots, and efficient experimental designs 📈. His interdisciplinary research extends to social media-based well-being predictions, crowdsourcing motivation, and personalized medicine 💡. He has also explored biostatistics, oncology-related immune analysis, and ketogenic therapies for cancer 🧬. His impactful research blends theoretical innovation with practical applications, advancing both statistics and computational methods 🔍.

Publication Top Notes

1️⃣ Peeking inside the black box: Visualizing statistical learning with plots of individual conditional expectation – Journal of Computational and Graphical Statistics, 2015, Cited by: 1718 📊📈

2️⃣ Breaking Monotony with Meaning: Motivation in Crowdsourcing Markets – Journal of Economic Behavior & Organization, 2013, Cited by: 584 💡👥

3️⃣ bartMachine: Machine Learning with Bayesian Additive Regression Trees – Journal of Statistical Software, 2016, Cited by: 451 🤖📉

4️⃣ Predicting individual well-being through the language of social media – Biocomputing 2016 Proceedings, 2016, Cited by: 244 📱🧠

5️⃣ Variable selection for BART: an application to gene regulation – Journal of Statistical Software, 2014, Cited by: 205 🧬📊

6️⃣ Preventing Satisficing in Online Surveys – Proceedings of CrowdConf, 2010, Cited by: 143 📝📑

7️⃣ Prediction with missing data via Bayesian additive regression trees – Canadian Journal of Statistics, 2015, Cited by: 105 📉📈

8️⃣ Spatial organization of dendritic cells within tumor draining lymph nodes impacts clinical outcome in breast cancer patients – Journal of Translational Medicine, 2013, Cited by: 60 🧪🎗

9️⃣ Quantitative, architectural analysis of immune cell subsets in tumor-draining lymph nodes from breast cancer patients and healthy lymph nodes – PLOS ONE, 2010, Cited by: 60 🔬🦠

🔟 Nearly random designs with greatly improved balance – Biometrika, 2019, Cited by: 46 📊📏

1️⃣1️⃣ Matching on-the-fly: Sequential allocation with higher power and efficiency – Biometrics, 2014, Cited by: 40 🏹🎯

Peng Zhang | Biological Science | Best Researcher Award

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Dr. Peng Zhang | Biological Science | Best Researcher Award

Assistant Professor, Tianjin University of Technology, China

Dr. Peng Zhang is an Assistant Professor at the Life and Health Intelligent Research Institute, Tianjin University of Technology. With a strong focus on understanding gut microbiota and its impact on health, Dr. Zhang combines expertise in natural product research with advanced omics technologies. His work explores innovative ways to improve bioavailability and efficacy of therapeutic agents. 🌟

Publication Profile

Strengths for the Award:

  1. Innovative Research Focus: Peng Zhang’s work on natural products, drug delivery systems, and the role of gut microbiota in health demonstrates a high level of innovation and relevance in the field of life and health sciences.
  2. Significant Publications: Zhang has a strong publication record in reputable journals, including Journal of Functional Foods, Journal of Agricultural and Food Chemistry, and The ISME Journal. His research on gut microbiota and its impact on health conditions showcases his expertise and contributions to the field.
  3. Active Projects: Leading national projects funded by the National Natural Science Foundation of China, Zhang’s research includes high-impact topics like antibiotic resistance and its effects on gut microbiota. This aligns with current global health challenges.
  4. Diverse Experience: Zhang’s experience spans from studying the effects of natural products on obesity to the development of nanotechnology-based drug delivery systems, indicating a broad and applied approach to research.

Areas for Improvement:

  1. Broader Impact and Outreach: While Zhang’s research is impactful, expanding efforts to disseminate findings to a wider audience, including the general public and policymakers, could enhance the societal impact of his work.
  2. Collaborations and Networking: Increasing collaborations with international researchers and institutions could further strengthen his research’s global relevance and visibility.
  3. Grant and Project Diversification: Although Zhang has led and participated in significant projects, diversifying funding sources and project scopes might provide additional opportunities for groundbreaking research.

Education

Dr. Zhang earned his PhD from Nankai University, Tianjin, China, in 2021, where he developed models to study the role of gut microbiota in health crises caused by antibiotics. Prior to this, he completed his graduate studies at Hainan University, Haikou, China, focusing on the effects of dietary compounds on obesity. 🎓

Experience

2022 – Present: Assistant Professor, Life and Health Intelligent Research Institute, Tianjin University of Technology, Tianjin, China. Research includes purifying natural products and developing nanotechnology-based drug delivery systems. 🔬2017 – 2021: PhD student, Nankai University, Tianjin, China. Developed models to study antibiotic exposure and drug-resistant bacteria. 🧪2015 – 2017: Graduate student, Hainan University, Haikou, China. Examined effects of Luo Han Guo on obesity. 🌿

Research Focus

Dr. Zhang’s research primarily investigates the role of natural products in alleviating inflammatory diseases and improving gut health. His projects include:

Purifying Natural Products: Studying polysaccharides and polyphenols from medicinal foods to understand their impact on inflammatory diseases and gut microbiota. 🌱Drug Delivery Systems: Developing nanotechnology-based encapsulation systems to enhance the bioavailability of active compounds. 🚀

Awards and Honours

Dr. Zhang’s contributions to the field are recognized through various awards and honors. Notable mentions include his significant contributions to understanding the interactions between gut microbiota and therapeutic agents. 🏅

Publications Top Note

Biological Science, Biological Research, Life Sciences

  1. Polysaccharides isolated from Hibiscus sabdariffa L. mitigate intestinal radiation injury, Journal of Functional Foods, 2024.
  2. Polysaccharide Isolated from Agaricus blazei Murill Alleviates Intestinal Ischemia/Reperfusion Injury, Journal of Agricultural and Food Chemistry, 2024.
  3. The Gut Microbiota Contributes to Systemic Responses and Liver Injury in Gut-Derived Sepsis, Microorganisms, 2023.
  4. Porphyromonas gingivalis exacerbates alcoholic liver disease, Journal of Clinical Periodontology, 2023.
  5. Gut microbiota exaggerates triclosan-induced liver injury, Journal of Hazardous Materials, 2022.

 

Conclusion:

Peng Zhang is a highly qualified candidate for the Research for Best Researcher Award. His innovative research, strong publication record, and leadership in significant projects underscore his contributions to the field. Addressing areas for improvement, such as expanding outreach and fostering international collaborations, could further enhance his impact and recognition in the global research community.