Aditi Nag | Bioinformatics | Best Researcher Award

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Assist. Prof. Dr. Aditi Nag | Bioinformatics | Best Researcher Award

Assitant Professor at Dr. B. Lal Institute of Biotechnology, India

Dr. Aditi Nag is an Assistant Professor at Dr. B. Lal Institute of Biotechnology, Jaipur, India. She completed her B.Sc. (2007) in Industrial Microbiology, Botany, and Zoology with a 75.25% from the University of Rajasthan and her M.Sc. (2009) in Biotechnology with a 74.66% from the Department of Botany, University of Rajasthan. She obtained her PhD in 2017 from the Indian Institute of Technology, Kanpur, under the guidance of Dr. Jonaki Sen and Dr. Amitabha Bandyopadhyay, with a thesis focused on BMP signaling in adult tissue homeostasis.

Publication Profile

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Academic Qualifications 🎓

Assist. Prof. Dr. Aditi Nag holds a B.Sc. in Industrial Microbiology, Botany, and Zoology from University Maharani’s College, University of Rajasthan (2007) with 75.25%. She completed her M.Sc. in Biotechnology from the Department of Botany, University of Rajasthan, with 74.66% in 2009. Dr. Nag earned her PhD in 2017 from the Indian Institute of Technology, Kanpur, where she investigated BMP signaling in adult tissue homeostasis. Her thesis was supervised by Dr. Jonaki Sen and Dr. Amitabha Bandyopadhyay. Dr. Nag’s academic journey reflects her dedication to advancing scientific knowledge. 🎓🔬

Work Experience

Assist. Prof. Dr. Aditi Nag currently holds the position of Assistant Professor at Dr. B. Lal Institute of Biotechnology, a role she has been in since 2018. In this position, Dr. Nag contributes her expertise in biotechnology, focusing on teaching and research. She has been an integral part of the institution, helping to shape the academic environment and furthering scientific research in her field. Her dedication is evident through her work at the institute, and she currently receives a pay scale of ₹4.8 lakhs. 🌟📚

Professional Recognition & Awards

Assist. Prof. Dr. Aditi Nag has been recognized for her outstanding contributions to the field of biotechnology. She received the First Prize in Oral Presentation at the International Conference ISSUE-2022 at UPES, Dehradun (2023). Dr. Nag also secured the First Prize in Poster Presentation at the International Conference Biosangam-2020 (2020). Her academic excellence is further highlighted by prestigious awards such as GATE 2008 (IITK), JRF-UGC and SRF (UGC), and the Summer Research Fellowship-2008 (IAS-INSA-NASI). Additionally, she won the First Prize in Poster Presentation at the National Seminar on Biotechnology in Sustainable Agriculture and Second Prize at the Indian Science Congress (2008). 🌟🎓

Teaching Experience

Since June 2018, Assist. Prof. Dr. Aditi Nag has been a regular faculty member at Dr. B. Lal Institute of Biotechnology, teaching both PG and UG courses in Genetics, Developmental Biology, Genomics, Proteomics, Biostatistics, and Bioinformatics. She has also conducted tutorials for B.Tech students on Molecular Cell Biology and assisted professors in correcting answer sheets for courses like Compulsory Life Sciences, Biochemistry, and Molecular Cell Biology. Dr. Nag has extensive invigilation experience for department entrance exams and regular assessments. Additionally, she has trained over one M.Tech student in molecular biology techniques and lab practices. 🎓🔬

Research Focus

Assist. Prof. Dr. Aditi Nag’s research is primarily centered on environmental biotechnology, focusing on wastewater-based epidemiology (WBE) for tracking viruses like SARS-CoV-2. Her work investigates wastewater surveillance as an early warning system for pandemics and the role of microbial interactions in wastewater treatment. Dr. Nag’s studies also explore BMP signaling in tissue homeostasis, including skeletal, hair follicle, and intestinal health. Additionally, her research extends to nanotechnology, CRISPR-Cas systems, and the development of vaccines against emerging viruses. She has contributed to several publications on wastewater treatment, viral detection, and public health surveillance. 🌍🦠🧫

Publication Top Notes

  • Sewage surveillance for the presence of SARS-CoV-2 genome as a useful wastewater-based epidemiology (WBE) tracking tool in India – 177 citations, 2020 🌍🦠
  • Effect of earthworms in reduction and fate of antibiotic-resistant bacteria (ARB) and antibiotic-resistant genes (ARGs) during clinical laboratory wastewater treatment – 45 citations, 2021 🐛🧬
  • Design, performance evaluation and investigation of the dynamic mechanisms of earthworm-microorganisms interactions for wastewater treatment through vermifiltration technology – 37 citations, 2020 💧🌱
  • BMP signaling is required for adult skeletal homeostasis and mediates bone anabolic action of parathyroid hormone – 32 citations, 2016 🦴🔬
  • Monitoring of SARS-CoV-2 Variants by Wastewater-Based Surveillance as a Sustainable and Pragmatic Approach—A Case Study of Jaipur (India) – 22 citations, 2022 🧫🔎
  • Successful application of wastewater-based epidemiology in prediction and monitoring of the second wave of COVID-19 with fragmented sewerage systems – 18 citations, 2022 💧🦠
  • Imprints of Lockdown and Treatment Processes on the Wastewater Surveillance of SARS-CoV-2: A Curious Case of Fourteen Plants in Northern India – 17 citations, 2021 🌍🚰
  • RNA-Seq of untreated wastewater to assess COVID-19 and emerging and endemic viruses for public health surveillance – 15 citations, 2023 🧬🌍
  • Wastewater surveillance could serve as a pandemic early warning system for COVID-19 and beyond – 13 citations, 2023 💡🦠
  • Detection of SARS-CoV-2 RNA in fourteen wastewater treatment systems in Uttarakhand and Rajasthan States of North India – 11 citations, 2020 🌍🦠
  • Constructed Wetlands and vermifiltration two successful alternatives of wastewater reuse: A commentary on development of these alternate strategies of wastewater treatment – 3 citations, 2023 💧🌱
  • BMP signalling is critical for maintaining homeostasis of hair follicles and intestine in adult mice – 3 citations, 2017 🧬🔬
  • Population Infection Estimation from Wastewater Surveillance for SARS-CoV-2 in Nagpur, India During the Second Pandemic Wave – 2 citations, 2024 💧🦠
  • Nanoparticles: Characters, applications, and synthesis by endophytes – 2 citations, 2023 🌱🔬
  • COVID-19 Vaccines: An Account of Need and Efficacy vs Safety and Challenges – 2 citations, 2021 💉🦠

 

 

Muhammad Ishaq | Data Science | Best Paper Award

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Assist Prof Dr. Muhammad Ishaq | Data Science | Best Paper Award

Assist Prof Dr. Muhammad Ishaq, The University of Agriculture Peshawar, Pakistan

Dr. Muhammad Ishaq earned his PhD in Computer Science with Distinction from Harbin Engineering University as an HEC Scholar in 2012. With 12 years of post-PhD teaching experience, he has significantly contributed to academia by organizing conferences and launching programs like BS (Bioinformatics), BS (Artificial Intelligence), MS (Data Science), and PhD (Computer Science). Dr. Ishaq has played a pivotal role in enhancing curricula and spearheading university computerization projects. He manages the HEC’s Digital Learning and Skills Enrichment Initiative (DLSEI) and has published numerous high-quality research papers. His dedication to supervising research theses and submitting projects to funding agencies showcases his commitment to excellence. 📚✨

Publication Profile

Scopus

🖥️ Academic Background 🎓

Dr. Muhammad Ishaq earned a PhD in Computer Science with Distinction from Harbin Engineering University as an HEC Scholar in 2012.

Research Focus

Dr. Muhammad Ishaq’s research focuses on machine learning, neural networks, and optimization algorithms. He has made significant contributions to data imputation in categorical datasets, robust crowd counting, and medical data classification. His work also includes optimizing neural network weights using accelerated particle swarm optimization and improving task scheduling for computational alignment of biological sequences. Dr. Ishaq’s research in agri-informatics and wireless body area networks further highlights his diverse expertise. His publications in esteemed journals and conference papers reflect his dedication to advancing computational methods and artificial intelligence. 📊🤖💡

 

Publication Top Notes

  • Machine Learning Based Missing Data Imputation in Categorical Datasets (Ishaq, M., et al., IEEE Access, 2024) – 📄🕵️‍♂️
  • Robust Counting in Overcrowded Scenes Using Batch-Free Normalized Deep ConvNet (Zahir, S., et al., Computer Systems Science and Engineering, 2023) – 📄🕵️‍♂️2 citations
  • NUMERICAL SOLUTION of WAVELET NEURAL NETWORK LEARNING WEIGHTS USING ACCELERATED PARTICLE SWARM OPTIMIZATION ALGORITHM (Zeb, A., et al., Fractals, 2023) – 📄🕵️‍♂️1 citation
  • Optimizing connection weights of functional link neural network using APSO algorithm for medical data classification (Khan, A., et al., Journal of King Saud University – Computer and Information Sciences, 2022) – 📄🕵️‍♂️11 citations
  • A dynamic swift association scheme for wireless body area networks (Sheraz, A., et al., Transactions on Emerging Telecommunications Technologies, 2022) – 📄🕵️‍♂️
  • Comprehensive selective improvements in agri-informatics semantics (Ishaq, M., et al., Journal of Information Science, 2022) – 📄🕵️‍♂️1 citation
  • Smart Control System for User Confirmation Based on IoT (Khan, A., et al., Lecture Notes in Networks and Systems, 2022) – 📄🕵️‍♂️
  • An Improved Strategy for Task Scheduling in the Parallel Computational Alignment of Multiple Sequences (Ishaq, M., et al., Computational and Mathematical Methods in Medicine, 2022) – 📄🕵️‍♂️1 citation
  • Current Trends and Ongoing Progress in the Computational Alignment of Biological Sequences (Ishaq, M., et al., IEEE Access, 2019) – 📄🕵️‍♂️3 citations
  • Cognition in a cognitive routing system for mobile ad-hoc network through leaning automata and neural network (Afridi, M.I., et al., Applied Mechanics and Materials, 2013) – 📄🕵️‍♂️

Milad Jamali-dolatabad | Data Science Award | Best Researcher Award

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Mr. Milad Jamali-dolatabad | Data Science Award | Best Researcher Award

Mr. Milad Jamali-dolatabad, Tabriz University of Medical Sciences, Iran

Milad Jamali-Dolatabad is a biostatistics expert and researcher specializing in traffic injury prevention and data analysis. He earned his Master’s degree in Biostatistics from Tabriz University of Medical Sciences, Iran, focusing on applying advanced statistical methods to traffic data (🎓📊). His research, which includes publications on pedestrian accident outcomes and road traffic mortality, has been featured in renowned journals like BMC Public Health and Traffic Injury Prevention (📚🚶‍♂️). Proficient in R, Stata, and SPSS, Milad is involved in several projects that analyze traffic accident data and model road traffic mortality trends (💻🔍). He is fluent in Turkish and Persian, with intermediate English proficiency (🗣️🌐).

Publication profile

Google Scholar

Academic Background 📚

Milad Jamali-Dolatabad holds a Master’s degree in Biostatistics from Tabriz University of Medical Sciences, Iran, earned between 2016 and 2020. His thesis, supervised by Dr. Parvin Sarbakhsh, focused on the application of Partial Least Squares (PLS) methods to analyze traffic data, comparing their efficacy with traditional approaches. He achieved an impressive dissertation grade of 18.89 out of 20, reflecting his academic excellence (🎓).

Professional Experience 💼

Milad has been instrumental in various research projects. Notably, he contributed to the development of frameworks for synchronized data mining using driving simulators and EEG data in traffic laboratories. His expertise extends to modeling road traffic mortality dynamics and identifying hidden patterns in pedestrian characteristics using statistical methodologies.

Research Focus

Milad Jamali-Dolatabad’s research primarily focuses on traffic injury prevention and epidemiology, leveraging advanced statistical methodologies. His studies often involve analyzing predictors of fatal outcomes in pedestrian accidents and road traffic injuries in Iranian populations. Using techniques like Partial Least Squares (PLS) and categorical principal component analysis (CATPCA), he explores hidden patterns and trends in mortality data, particularly related to pedestrian safety and traffic accident dynamics (🚶‍♂️📊). His work contributes significantly to understanding factors influencing road traffic mortality and developing strategies for safer transportation systems, reflecting a commitment to improving public health through rigorous statistical analysis and evidence-based research.

 

Publication Top Notes

Alberto Brini | Statistics | Best Researcher Award

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Dr. Alberto Brini | Statistics | Best Researcher Award

Dr. AlbertoBrini, Eindhoven University of Technology, Netherlands

Dr. Alberto Brini is a skilled biostatistician with a diverse research background in health outcomes and data analysis. With a PhD in Statistics/Data Science, he has collaborated internationally, including roles at McMaster University and Radboud University. 📊 His expertise spans patient-reported outcomes, omics data analysis, and statistical modeling for healthcare applications. Dr. Brini has taught and supervised numerous projects, demonstrating his commitment to education and mentorship. His contributions to statistical methods in (onco-)hematology and food safety research showcase his dedication to improving public health. 🩺🔬

Publication profile:

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Education:

Dr. Alberto Brini’s academic journey showcases a dedication to statistical excellence and interdisciplinary learning. 📚 He earned his PhD in Statistics/Data Science from Technische Universiteit Eindhoven, specializing in high-dimensional data analysis. Under the guidance of Prof. Edwin R. van den Heuvel and Dr. Jasper Engel, his thesis focused on innovative statistical methodologies. Prior to this, he obtained an MSc in Industrial and Applied Mathematics, delving into stochastic processes and longitudinal data analysis. His educational background also includes a joint MSc in Mathematical Modelling for Engineering from Politecnico di Torino, emphasizing networks and optimization. Dr. Brini’s stellar academic record culminated from his early education at Liceo Scientifico Statale Gregorio Ricci Curbastro in Lugo, Italy. 🌟

 

Experience:

Dr. Alberto Brini is an accomplished biostatistician with a rich portfolio spanning various international research projects. 🌍 Currently, he serves as a Biostatistician at Fondazione GIMEMA Franco Mandelli Onlus in Rome, Italy, leading statistical design and analysis in (onco-)hematology. As a Volunteer Researcher at McMaster University, Canada, he contributes to the analysis of the Canadian Longitudinal Study of Ageing (CLSA) within a global consortium. Previously, he provided statistical consultancy at Maxima Medisch Centrum, Netherlands, and conducted research at Radboud University and Wageningen Food Safety Research center. Dr. Brini’s expertise extends from industrial consortia to healthcare and food safety domains, reflecting his versatile skill set. 📊🔬

Honors and Awards:

Dr. Alberto Brini’s exceptional achievements extend beyond academia, reflecting his excellence in athletics and extracurricular endeavors. 🏅 He received grants and honors for academic excellence from institutions like Politecnico di Torino and Fondazione Alemanno Fantini e Margherita Orselli. Notably, he secured “ALSP Scholarships” at Eindhoven University of Technology. His prowess in athletics earned him numerous accolades, including multiple 1st place finishes in the Club National Championships for Combined Events. Dr. Brini’s diverse accomplishments also include participation in prestigious events such as the Enterprise European Business Games and the Jean Humbert Memorial World Cup for Schools. 🌟

 

Research Focus:

Dr. Alberto Brini’s research focus spans diverse areas, with a primary emphasis on statistical analysis of high-dimensional data in biomedical and healthcare contexts. 📊 His work includes studies on patient-reported outcomes in cardiac telerehabilitation programs, determinants of information needs in coronary artery disease patients, and financial toxicity in patients with hematologic malignancies. He also contributes to optimizing medical procedures, such as the surgical shortening of lengthened iliac arteries in endurance athletes. Dr. Brini’s expertise extends to missing data imputation, lifestyle behaviors, and multimorbidity patterns, reflecting his commitment to enhancing healthcare outcomes through advanced statistical methodologies. 🩺

 

Publication Top Notes:

  1. Predictors of non-participation in a cardiac telerehabilitation programme: a prospective analysis by HMCK R W M Brouwers, A Brini, R W F H Kuijpers, J J Kraal 📊 Cited by: 14* (2021)
  2. Short-and long-term results of operative iliac artery release in endurance athletesby M van Hooff, MMJM Hegge, MHM Bender, MJA Loos, A Brini, … 🏃‍♂️ Cited by: 4 (2022)
  3. Improved One-Class Modeling of High-Dimensional Metabolomics Data via Eigenvalue-Shrinkage by ERHJE A Brini, V Avagyan, RCH de Vos, JH Vossen 💡 Cited by: 3 (2021)
  4. The t linear mixed model: model formulation, identifiability and estimation by M Regis, A Brini, N Nooraee, R Haakma, ER van den Heuvel 🔍 Cited by: 3 (2019)
  5. Short-and long-term outcomes after endarterectomy with autologous patching in endurance athletes with iliac artery endofibrosis. by M van Hooff, FFC Colenbrander, MHM Bender, MMJA Loos, A Brini, … 🏃‍♀️ Cited by: 2 (2023)
  6. Determinants of information needs in patients with coronary artery disease receiving cardiac rehabilitation: a prospective observational study
  7. Surgical shortening of lengthened iliac arteries in endurance athletes: Short-term and long-term satisfaction
  8. Financial Toxicity and Health-Related Quality of Life Profile of Patients With Hematologic Malignancies Treated in a Universal Health Care System
  9. USING NETWORK ANALYSIS METHODS TO STUDY MULTIMORBIDITY PATTERNS
  10. Association of Financial Toxicity and Health-Related Quality of Life in Long-Term Survivors of Acute Promyelocytic Leukemia Treated within a Universal Healthcare System