Aditi Nag | Bioinformatics | Best Researcher Award

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 πŸŽ“

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. πŸŽ“πŸ”¬

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 β‚Ή4.8 lakhs. πŸŒŸπŸ“š

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). πŸŒŸπŸŽ“

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. πŸŽ“πŸ”¬

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 πŸ›πŸ§¬
  • Design, performance evaluation and investigation of the dynamic mechanisms of earthworm-microorganisms interactions for wastewater treatment through vermifiltration technology – 37 citations, 2020 πŸ’§πŸŒ±
  • BMP signaling is required for adult skeletal homeostasis and mediates bone anabolic action of parathyroid hormone – 32 citations, 2016 πŸ¦΄πŸ”¬
  • Monitoring of SARS-CoV-2 Variants by Wastewater-Based Surveillance as a Sustainable and Pragmatic Approachβ€”A Case Study of Jaipur (India) – 22 citations, 2022 πŸ§«πŸ”Ž
  • Successful application of wastewater-based epidemiology in prediction and monitoring of the second wave of COVID-19 with fragmented sewerage systems – 18 citations, 2022 πŸ’§πŸ¦ 
  • 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 πŸ’‘πŸ¦ 
  • 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 πŸ’§πŸŒ±
  • BMP signalling is critical for maintaining homeostasis of hair follicles and intestine in adult mice – 3 citations, 2017 πŸ§¬πŸ”¬
  • Population Infection Estimation from Wastewater Surveillance for SARS-CoV-2 in Nagpur, India During the Second Pandemic Wave – 2 citations, 2024 πŸ’§πŸ¦ 
  • Nanoparticles: Characters, applications, and synthesis by endophytes – 2 citations, 2023 πŸŒ±πŸ”¬
  • COVID-19 Vaccines: An Account of Need and Efficacy vs Safety and Challenges – 2 citations, 2021 πŸ’‰πŸ¦ 

 

 

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

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 (πŸŽ“πŸ“Š). 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 (πŸ“šπŸšΆβ€β™‚οΈ). Proficient in R, Stata, and SPSS, Milad is involved in several projects that analyze traffic accident data and model road traffic mortality trends (πŸ’»πŸ”). He is fluent in Turkish and Persian, with intermediate English proficiency (πŸ—£οΈπŸŒ).

Publication profile

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Academic Background πŸ“š

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 (πŸŽ“).

Professional Experience πŸ’Ό

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 (πŸšΆβ€β™‚οΈπŸ“Š). 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