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

Scopus

Orcid

Google Scholar

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 💉🦠

 

 

Md Erfan | Machine Learning | Best Researcher Award

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Mr. Md Erfan | Machine Learning | Best Researcher Award

Mr. Md Erfan, University of Barishal, Bangladesh

Assistant Professor, Department of Computer Science and Engineering, University of Barishal, Bangladesh. His research focuses on flaky test detection, compilation error resolution, and AI applications in automation, decision-making, and problem-solving. He holds an MSSE and BSSE from the University of Dhaka. Erfan has published in Elsevier, Springer, and IEEE, exploring NLP, machine learning, and software engineering. He serves as Project Coordinator for Bangladesh’s EDGE Project and has mentored in NASA Space Apps Challenge. An athlete, he won medals in national athletic competitions. 

Publication Profile

Google Scholar

Education 🎓📚

Md Erfan holds a Master of Science in Software Engineering (MSSE) 🖥️ from the Institute of Information Technology, University of Dhaka (2016), with an impressive CGPA of 3.81/4.0 (WES Equivalent: 3.97/4.00). His thesis, supervised by Dr. Md Shariful Islam, focused on an Efficient Runtime Code Offloading Mechanism for Mobile Cloud Computing ☁️💻. He also earned a Bachelor of Science in Software Engineering (BSSE) 🏆 from the same institute in 2014, achieving a CGPA of 3.80/4.0 (WES Equivalent: 3.88/4.00). His undergraduate thesis, guided by Dr. Kazi Muhaimin-us-Sakib, explored approximating social ties based on call logs 📞📊.

Research Experience 🔬📊

In Summer 2024, Md Erfan worked as a Research Student in the UIUC+/ASSIP Summer Research Program 🎓. Collaborating with Dr. Wing Lam (George Mason University) 🏛️ and Dr. August Shi (University of Texas at Austin) 🤖, he focused on automating the end-to-end reproduction of flaky test methods 🛠️. His work involved leveraging issue data, compiling code, running tests, analyzing results, and logging dependencies. Additionally, he created Dockerized environments 🐳 to ensure reproducibility, enhancing software testing efficiency and reliability. His contributions aimed at improving software quality assurance and automation in test debugging 🔍✅.

Professional Experience 💼📚

Md Erfan is an Assistant Professor (2020–Present) at the Department of Computer Science and Engineering, University of Barishal 🏛️, where he teaches Software Engineering, Software Quality Assurance, Data Structures, Algorithms, and Mathematical Analysis 📖💻. Since January 2024, he has also served as a Project Coordinator for the EDGE Project 🌐, managing a 5 crore BDT ($384,615 USD) fund 💰 to enhance digital governance and the economy in Bangladesh. Previously, he worked as a Lecturer (2016–2020) 🎓, a Trainer (2015–2016) 🖥️, and a Software Engineer Intern (2014) 🔍, focusing on testing tools and Microsoft SharePoint development.

Awards and Achievements 🏆🎖️

Md Erfan has been a Regional Mentor (2021–2023) 🌍🚀 for the NASA Space Apps Challenge, guiding innovative projects. He received the Pre-graduation Merit Award (2015) 🎓 from the University of Dhaka for outstanding academic performance. Beyond academics, he has excelled in athletics, securing 3rd place 🥉 in the 5000m and 10000m races 🏃‍♂️ at the Bangladesh Inter-University Athletic Competition (2015) and 2nd place 🥈 in multiple track events (2014–2015). Since 2016, he has been the Coach and Manager ⚽🏅 of the University of Barishal Football and Athletics teams, fostering sports excellence.

 

Research Interests 🔍💻

Md Erfan’s research primarily focuses on Software Engineering, specializing in flaky test detection and mitigation as well as compilation error resolution to enhance software reliability and development efficiency. Additionally, he explores the applications of Artificial Intelligence (AI), leveraging Machine Learning (ML) 🤖, Natural Language Processing (NLP) 🗣️, and Computer Vision 👀 to tackle real-world challenges. His work aims to improve automation, decision-making, and problem-solving across various domains, ensuring smarter and more efficient technological advancements. Through his research, Erfan contributes to optimizing software development and AI-driven innovations for practical applications. 🚀

Research Focus Areas 🧑‍💻📡

Md Erfan’s research spans multiple domains in Software Engineering and Artificial Intelligence. His work focuses on Mobile Cloud Computing ☁️📱, including task allocation and code offloading for performance optimization. He explores Machine Learning 🤖 applications, such as flaky test detection, compilation error resolution, and autism spectrum disorder detection 🧠. His contributions in Natural Language Processing (NLP) 🗣️ involve cyberbullying classification and user similarity computation. Additionally, he applies Computer Vision 👁️ techniques for mosquito species identification and assistive robotics. His interdisciplinary approach integrates automation, decision-making, and problem-solving in real-world applications.

Publication Top Notes

  • Mobility aware task allocation for mobile cloud computing
    Cited by: 8
    Year: 2016 📱☁️
  • Task allocation for mobile cloud computing: State-of-the-art and open challenges
    Cited by: 4
    Year: 2016 📊
  • Identification of Vector and Non-vector Mosquito Species Using Deep Convolutional Neural Networks with Ensemble Model
    Cited by: 2
    Year: 2022 🦟🤖
  • Recurrent neural network based multiclass cyber bullying classification
    Cited by: 1
    Year: 2024 💻🗣️
  • User Similarity Computation Strategy for Collaborative Filtering Using Word Sense Disambiguation Technique
    Cited by: 1
    Year: 2023 🔍📚
  • Approximating Social Ties Based on Call Logs: Whom Should We Prioritize?
    Cited by: 1
    Year: 2015 📱📞
  • An exploration of machine learning approaches for early Autism Spectrum Disorder detection
    Year: 2025 🧠🤖
  • Experimental Study of Four Selective Code Smells Declining in Real Life Projects
    Year: 2024 🧑‍💻🔧
  • Autism Spectrum Disorder Detecting Mechanism on Social Communication Skills Using Machine Learning Approaches
    Year: 2023 🧠💡
  • Dynamic Method Level Code Offloading for Performance Improvement and Energy Saving
    Year: 2017 ⚡💻
  • A comparative study of early autism spectrum disorder detection using deep learning based models
    Year: 2017 🧠🔍
  • An Optimal Task Scheduling Mechanism for Mobile Cloud Computing
    Year: 2016 ☁️📊
  • WVGM: Water View Google Map, Introducing Water Paths on Rivers to Reach One’s Destination using Various Types of Vehicles
    Year: 2016 🌍🚗
  • A comprehensive survey of code offloading mechanisms for mobile cloud computing
    Year: 2016 ☁️🔄
  • MICROCONTROLLER BASED ROBOTICS SUPPORT FOR BLIND PEOPLE
    Year: 2016 🤖👨‍🦯

Conclusion 🌟

Mr. Md Erfan is a highly suitable candidate for the Research for Best Researcher Award due to his strong academic background, impactful research in software engineering and AI, extensive publications, leadership in digital governance projects, and active contributions to global research collaborations. His work demonstrates innovation, technical expertise, and a commitment to advancing knowledge in his field.

 

 

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) – 📄🕵️‍♂️

You-Jin Park | Data Science | Best Researcher Award

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Prof. You-Jin Park | Data science | Best Researcher Award

Prof. You-Jin Park, National Taipei University of Technology, Taiwan

🎓 Prof. You-Jin Park, PhD, is an accomplished educator and researcher in Industrial Engineering, specializing in optimization using genetic algorithms. With a doctoral degree from Arizona State University, Park has extensive teaching experience across Asia and the United States. Their research contributions include work on CDMA cellular systems and post-doctoral research in collaboration with Intel Corp. Park’s expertise spans academia and industry, with roles at Samsung Electronics and as a consultant. A dedicated professional, Park continues to advance knowledge in engineering and management, shaping future generations of engineers.

Publication profile:

Scopus

Education:

🎓 Dr. You-Jin Park pursued a comprehensive academic journey in Industrial Engineering, culminating in a PhD from Arizona State University in 2003. Their dissertation, “Application of Genetic Algorithms in Response Surface Optimization Problems,” showcased their innovative approach to optimization techniques. Prior to their doctoral studies, Park earned a Master’s degree from Hanyang University, Korea, focusing on call loss and call blocking probabilities in CDMA cellular systems. This research laid the groundwork for their subsequent contributions to the field. Park’s academic journey began with a Bachelor’s degree, also in Industrial Engineering, from Hanyang University, demonstrating a lifelong dedication to engineering excellence.

Teaching Experiences:

👨‍🏫 Dr. You-Jin Park’s teaching journey reflects a rich tapestry of academic engagement spanning various prestigious institutions and continents. Beginning as a Teaching Assistant at Hanyang University, Korea, Park’s passion for education blossomed. Subsequently, they ventured to the United States, serving as a Teaching Assistant and later as a Teaching Associate at Arizona State University. Their commitment to academia extended to leadership roles as Director of the Career Development Center at Chung-Ang University, Korea. Park’s career trajectory reached new heights with appointments as Assistant and Associate Professor at ChungAng University before assuming positions of Associate and now full Professor at National Taipei University of Technology, Taiwan, where they continue to inspire students in Industrial Engineering and Management. 🌟

Research Experiences:

🔍 Dr. You-Jin Park’s research journey showcases a dynamic exploration of industrial engineering’s forefront. As a Graduate Research Associate at Arizona State University, Park delved into cutting-edge projects, including collaborations funded by Intel Corp., highlighting their expertise in industry-academic partnerships. Their contributions extended to post-doctoral research, further honing their skills as a researcher. Notably, their role as a Researcher at the Locks Institute underscored their commitment to interdisciplinary inquiry. Park’s research endeavors have been integral in advancing knowledge in industrial engineering, bridging theory and practical applications to unlock new possibilities in optimization and beyond. 🌱

Work Experiences:

💼 Dr. You-Jin Park’s professional journey reflects a diverse blend of academic and industry experiences, showcasing versatility and expertise. As a Principal Consultant at Samsung SDS, Seoul, they provided invaluable insights and guidance, leveraging their academic background to inform strategic decisions. Their tenure as a Senior Engineer at Samsung Electronics demonstrated a hands-on approach to semiconductor technology, contributing to the company’s innovation drive. Park’s stint as a Research Scholar and Faculty Associate at Arizona State University solidified their connection between academia and industry, enriching both spheres with their insights and expertise. Their multifaceted career path underscores their adaptability and commitment to excellence in various domains. 🌟

Research Focus:

🔬 Dr. You-Jin Park’s research focus lies at the intersection of industrial engineering and applied artificial intelligence, with a particular emphasis on optimization techniques for addressing complex real-world problems. Their work spans various domains, including semiconductor manufacturing, quality engineering, and process optimization. Through innovative approaches such as hybrid resampling methods and instance density-based oversampling, Park contributes to advancing the field’s understanding of imbalanced classification problems. Their research also delves into fault detection, energy efficiency, and productivity enhancement in manufacturing processes, showcasing a commitment to improving operational effectiveness and sustainability. Park’s interdisciplinary expertise combines rigorous statistical analysis with practical applications, driving advancements in industrial engineering. 🔍

Publication Top Notes:

  1. “A novel hybrid resampling for semiconductor wafer defect bin classification” (Quality and Reliability Engineering International, 2023)
    • Year of Publication: 2023
  2. “A New Hybrid Under-sampling Approach to Imbalanced Classification Problems” (Applied Artificial Intelligence, 2022)
    • Year of Publication: 2022
  3. “A new instance density-based synthetic minority oversampling method for imbalanced classification problems” (Engineering Optimization, 2022)
    • Year of Publication: 2022
  4. “A Review on Fault Detection and Process Diagnostics in Industrial Processes” (Processes, 2020)
    • Year of Publication: 2020
  5. “Improvement of Productivity through the Reduction of Unexpected Equipment Faults in Die Attach Equipment” (Processes, 2020)
    • Year of Publication: 2020
  6. “A Graphical Model to Diagnose Product Defects with Partially Shuffled Equipment Data” (Processes, 2019)
    • Year of Publication: 2019
  7. “Performance computation methods for composition of tasks with multiple patterns in cloud manufacturing” (International Journal of Production Research, 2018)
    • Year of Publication: 2018
  8. “Optimization of pick-and-place in die attach process using a genetic algorithm” (Applied Soft Computing, 2018)
    • Year of Publication: 2018
  9. “Eco-Efficiency Evaluation Considering Environmental Stringency” (Sustainability, 2017)
    • Year of Publication: 2017
  10. “Probabilistic Graphical Framework for Estimating Collaboration Levels in Cloud Manufacturing” (Sustainability, 2017)
    • Year of Publication: 2017