Mohit Kataria | Machine Learning | Best Researcher Award

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Mr. Mohit Kataria | Machine Learning | Best Researcher Award

Professor at IIT-Delhi

📌  Mohit Kataria is a 4th-year Ph.D. scholar at the School of Artificial Intelligence, IIT Delhi, India, specializing in Graph Machine Learning. His research focuses on scalability of graph algorithms, including graph coarsening, structure learning, federated learning, and large-scale applications. He has published in top venues like NeurIPS, MICAAI, and CBME. Mohit holds a Master’s in Computer Applications (80.1%) and has expertise in Python, PyTorch, TensorFlow, CUDA, and C/C++. His skill set spans deep learning (GNNs, CNNs, RNNs), machine learning (SVM, XGBoost), and mathematical optimization.

Publication Profile

Google Scholar

Academic Background 🎓🔬

📌 Mohit Kataria is a Ph.D. scholar in Graph Machine Learning at the MISN Lab, IIT Delhi, maintaining an 8.0 CGPA since August 2021. He holds a Master’s in Computer Applications (80.1%) from May 2020. His technical expertise spans Python, PyTorch, TensorFlow, CUDA, MPI, C/C++, Java, MySQL, and Erlang. 🖥️ He specializes in Machine Learning (SVM, Random Forest, XGBoost, Decision Trees) and Deep Learning (ANNs, GNNs, CNNs, RNNs, LSTM, VAE, GANs). 📊 His strong foundation in Linear Algebra, Probability, and Optimization fuels his research in scalable graph algorithms and AI applications. 🚀

💼 Professional Experience of Mohit Kataria

📌 Mohit Kataria has been actively involved in AI/ML training at IIT Delhi (2021-Present), where he has helped train 260+ industry experts in a six-month AI/ML program, covering fundamentals to advanced ML models. 🎓 He also conducted 5-day ML training programs for CAG and CRIS, Government of India. As a WebMaster (2022-Present), he manages the Yardi-ScAI and MISN group websites. 🌐 Previously, as a Member of Technical Staff at Octro.Inc (2020-2021), he led a team of four and contributed to the backend architecture of multiplayer games like Poker3D and Soccer Battles. 🎮🚀

🔬 Research Focus of Mohit Kataria

📌 Mohit Kataria specializes in Graph Machine Learning, focusing on graph coarsening, structure learning, and scalable AI applications. His work enhances GNN performance on heterophilic datasets 🧠, improves large-scale single-cell data analysis 🧬, and optimizes histopathological image processing 🔍. His research, published in NeurIPS, MICAAI, and CBME, develops efficient graph-based frameworks for biomedical and computational applications. 🏥 His expertise spans AI-driven healthcare, graph-based AI models, and machine learning scalability, making significant contributions to bioinformatics, medical imaging, and large-scale data processing. 🚀

Publication Top Notes 

 

 

 

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 💉🦠

 

 

Erika Loučanová | Digital Transformation | Best Researcher Award

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Assoc. Prof. Dr. Erika Loučanová | Digital Transformation | Best Researcher Award

Assoc. Prof., Technical Unversity in Zvolen, Slovakia

Assoc. Prof. Dr. Erika Loučanová is a researcher and educator specializing in innovation management and eco-innovation 🌱. She serves as an Associate Professor at the Technical University of Zvolen and has over two decades of experience in academia 📚. Holding a PhD in Sectoral and Cross-Sectional Economics, her work focuses on sustainable business strategies and industrial innovation. She has authored 320+ publications 📝 and contributed to major scientific projects.

Publication Profile

Orcid

🎓 Education & Academic Qualifications

Assoc. Prof. Dr. Erika Loučanová has a strong academic background in economics and business management 📚. In 2021, she attained the title of Associate Professor at the University of Žilina, specializing in Sectoral and Cross-Sectional Economics 📊. She earned her PhD (2007) from the Technical University of Zvolen, focusing on innovation in the woodworking industry 🏗️. Earlier, she completed her Engineering degree (2004) in Wood Engineering – Business Management 🏢. Her academic journey began at the Business Academy Žiar nad Hronom (1999), where she graduated with a strong foundation in business studies 💼.

 

🏆 Skills & Certifications

Assoc. Prof. Dr. Erika Loučanová possesses strong organizational, analytical, and communication skills 🗂️, honed through scientific projects, research management, and conference organization 🎤. She is proficient in digital tools 💻, including Microsoft Office, STATISTICA, and Adobe Acrobat Reader. Her work ethic is defined by reliability, flexibility, and leadership 🤝. She holds multiple certifications 📜, including Managing Innovation (2024, UNIDO, Austria), Business and Law (2022, Palacký University), and Tax Law (2023, Palacký University). Additionally, she has expertise in public health protection 🏥 and has undergone training in cluster management and bookkeeping 📊. Fluent in English, she actively engages in scientific collaboration 🌍.

Research Focus

Erika Loučanová’s research primarily focuses on eco-innovation, sustainable development, and business models for digital transformation and smart services. 🌱💡 Her work explores strategic environmental consumer segmentation, AI in innovation processes, and financial sustainability in pension systems. 📊🏡 She has contributed significantly to ecological innovation in Slovakia, including perceptions of wood-based structures and eco-services innovations in the furniture industry. 🏗️🌳 Additionally, she examines innovation in banking, management education, and public smart services for sustainability. 🏦🎓 Her research integrates economic, environmental, and technological perspectives, making substantial contributions to green business strategies and digital innovation. 🌍📈

Publication Top Notes

  • “Digital Transformation in Higher Education Institutions as a Driver of Social Oriented Innovations” (2022) – Cited by 3

  • “Innovation as a Tool for Sustainable Development in Small and Medium Size Enterprises in Slovakia” (2023) – Cited by 6

  • “The Perception of Respondents of Intelligent Packaging in Slovakia as Ecological Innovations” (2019) – Cited by 5

  • “Supporting Ecological Innovation as a Factor for Economic Development” (2019)

  • “Perception of packaging functions and the interest in intelligent and active packaging in terms of age” (2018)

  • Hodnotenie stavu udržateľnosti krajín EÚ (2022)  🌍♻️

  • Obchodné praktiky aplikované voči spotrebiteľom a ich právam na slovenskom trhu z pohľadu etiky (2022)  ⚖️🛒

  • Perception of Supplied Furniture and Its Innovation by Slovak Customers (2022)  🏠✨

  • The Relationship of Innovation and the Performance of Business Logistics in the EU (2022)  🚚📈

  • Crowdfunding as a Way of the Monetary and Financial Ecologies (2021)  💰🌱

  • Ecological Innovations in Services – Servitization of Furniture (2021) 🌳🛋️

  • Perception of Zero Waste in the Context of Environmental Innovation in Slovakia (2021) 🌿🚯

  • Positive Effects of the Forest on the Human Organism in the Context of Ecological Innovations and Modern Medicine (2021) 🌲❤️

  • Practices of Innovative Marketing Communication Tools in Furniture Sector (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) – 📄🕵️‍♂️