Avan Kumar | Chemical Engineering | Best Researcher Award

Dr. Avan Kumar | Chemical Engineering | Best Researcher Award

Arizona State University, United States

👨‍🎓Profiles

🎓 Early Academic Pursuits

Dr. Avan Kumar’s academic journey began with a Bachelor of Technology in Polymer Science and Chemical Technology from Delhi Technological University (DTU) (2013–2017). Building on this strong foundation, he pursued a Master of Technology in Chemical Engineering at the prestigious Indian Institute of Technology (IIT) BHU, Varanasi (2017–2019), where his research focused on enhancing solar module efficiency using luminescent dyes. His commitment to advancing sustainable technologies culminated in a Ph.D. in Chemical Engineering at IIT Delhi (2019–2023), specializing in the application of deep learning and natural language processing (NLP) for sustainable process development. This rigorous academic path laid the groundwork for his later innovations in AI-driven sustainability solutions.

🧑‍💼 Professional Endeavors

Dr. Kumar is currently serving as a Post-Doctoral Researcher at the School of Sustainability, Arizona State University (ASU), USA, under the mentorship of Prof. Bhavik R. Bakshi. Since December 2023, he has been actively engaged in designing customized large language models (LLMs) that extract structured databases from unstructured texts, aiming to create comprehensive life cycle inventories (LCIs) and circular reaction networks, particularly for chemical and plastic industries. His professional endeavors seamlessly blend chemical engineering with advanced AI technologies, showcasing his interdisciplinary expertise.

🧠 Contributions and Research Focus

Throughout his academic and research career, Dr. Kumar’s work has revolved around Generative AI, Large Language Models, Explainable AI, Natural Language Processing, and Sustainable Process Development. His doctoral research featured the development of a deep learning-integrated photo-catalyst classification model, data-driven optimization frameworks using Gaussian Process Regression and Multi-Objective Bayesian Optimization, and the creation of domain-specific LLMs such as “Extend-SciBERT,” “H2-BERT,” “Recycle-BERT,” and “CCU-LlaMA.” His innovative use of AI tools for chemical sustainability reflects his forward-thinking vision of the industry.

🌍 Impact and Influence

Dr. Kumar’s pioneering research has significant implications for green energy transition, plastic circular economy promotion, and carbon capture advancements. His customized language models have streamlined research processes across sectors like hydrogen production and plastic recycling, thus supporting industries to adapt more sustainable practices. By bridging AI and chemical engineering, he influences both academia and industry towards achieving climate goals and sustainability targets.

📚 Academic Citations

While still at an early stage of his postdoctoral career, Dr. Kumar’s contributions, particularly in AI-driven sustainability research, have begun attracting scholarly attention. His interdisciplinary approach promises a growing impact, with citations expected to increase as his LLM models and sustainable frameworks gain wider academic and industrial adoption.

🛠️ Technical Skills

Dr. Kumar possesses strong technical skills in Deep Learning, Natural Language Processing (NLP), Explainable Machine Learning (SHAP, GPR), Multi-Objective Optimization (MOBO), Large Language Model Fine-Tuning, and Life Cycle Inventory (LCI) Development. His interdisciplinary expertise also extends to Sustainable Process Design, Solar Energy Systems, and Circular Reaction Pathway Mapping, demonstrating a rare blend of computational and engineering acumen.

👨‍🏫 Teaching Experience

During his Ph.D. tenure at IIT Delhi, Dr. Kumar contributed actively to the academic community through mentorship roles and lab supervision. His engagement with students in interdisciplinary projects related to AI in chemical processes fostered a collaborative and innovative learning environment. His teaching philosophy focuses on integrating modern computational tools into chemical engineering curricula to prepare future-ready engineers.

🌟 Legacy and Future Contributions Highlight

Dr. Kumar’s legacy will be defined by his trailblazing integration of AI into chemical engineering to support sustainable development. His ongoing work at ASU promises to revolutionize the way industries build life cycle inventories and circular process models. In the future, he envisions advancing explainable, domain-specific AI systems that not only enhance industrial efficiency but also promote ecological responsibility. His contributions are poised to play a critical role in shaping next-generation sustainable technologies and AI innovations for environmental stewardship.

📖Notable Publications

An NLP-Based Framework for Extracting the Catalysts Involved in Hydrogen Production from Scientific Literature
Authors: Avan Kumar, Hariprasad Kodamana
Journal: Computer Aided Chemical Engineering (Book Chapter)
Year: 2023

A Convolutional Neural Network-Based Gradient Boosting Framework for Prediction of the Band Gap of Photo-Active Catalysts
Authors: Avan Kumar, Sreedevi Upadhyayula, Hariprasad Kodamana
Journal: Digital Chemical Engineering
Year: 2023

Recycle-BERT: Extracting Knowledge about Plastic Waste Recycling by Natural Language Processing
Authors: Avan Kumar, Bhavik R. Bakshi, Manojkumar Ramteke, Hariprasad Kodamana
Journal: ACS Sustainable Chemistry & Engineering
Year: 2023

Multiobjective Bayesian Optimization Framework for the Synthesis of Methanol from Syngas Using Interpretable Gaussian Process Models
Authors: Avan Kumar, K.K. Pant, Sreedevi Upadhyayula, Hariprasad Kodamana
Journal: ACS Omega
Year: 2023

A Text Mining Framework for Screening Catalysts and Critical Process Parameters from Scientific Literature – A Study on Hydrogen Production from Alcohol
Authors: Avan Kumar, Swathi Ganesh, Divyanshi Gupta, Hariprasad Kodamana
Journal: Chemical Engineering Research and Design
Year: 2022

 

Pengfei Li | Theoretical Chemistry | Best Researcher Award -1929

Prof. Pengfei Li | Theoretical Chemistry | Best Researcher Award

Shanghai Institute of Technical Physics, Chinese Academy of Sciences, China

👨‍🎓Profiles

🎓 Early Academic Pursuits

Prof. Pengfei Li’s journey in scientific research has been deeply rooted in environmental physics and remote sensing. His passion for atmospheric studies and hyperspectral technologies developed during his formative academic years, where he excelled in blending physical science with environmental applications. His academic path ultimately led him to become a key researcher at the prestigious State Key Laboratory of Infrared Physics under the Shanghai Institute of Technical Physics, part of the Chinese Academy of Sciences.

🧑‍💼 Professional Endeavors

Currently, as a Research Fellow, Prof. Li is a leading figure in satellite-based atmospheric monitoring. His role includes spearheading research on weak gas emissions detection, a crucial area for tackling global issues like climate change and environmental pollution. His leadership in the lab is marked by interdisciplinary integration, where hyperspectral satellite technology, data assimilation, atmospheric modeling, and artificial intelligence (AI) converge to address modern environmental challenges.

🔬 Contributions and Research Focus

Prof. Li’s research is at the intersection of hyperspectral remote sensing and AI-driven environmental monitoring. His team is developing next-generation techniques for satellite-based detection of weak gas emissions, aimed at pushing the detection limits in extreme environments. This work also involves defining payload specifications for future hyperspectral satellites. The outcomes of his research hold significant relevance for addressing atmospheric pollution, climate change, and homeland security threats, providing critical insights into satellite system design and operational strategies.

🌍 Impact and Influence

With over 50 SCI-indexed publications, including 20+ first-author or corresponding-author papers in leading journals such as PNAS and One Earth, Prof. Li has made a global impact. His research has informed both the academic community and policymakers, particularly in the realms of climate change mitigation, environmental monitoring, and satellite payload engineering. His work is frequently showcased at international conferences like the United Nations Climate Change Conference, AMS Annual Meeting, and the Goldschmidt Conference, where he has delivered numerous invited talks.

🏆 Honors and Leadership Roles

Prof. Li was selected for the prestigious Chinese Academy of Sciences “Hundred Talents Program” (Category B), recognizing his innovative research and leadership potential. Beyond research, he plays a pivotal role as a review expert for China’s National Key R&D Program and serves on scientific committees, including as the Deputy Secretary-General of the Hyperspectral Remote Sensing Technology and Application Professional Committee under the China Association for Remote Sensing Applications.

📚 Academic Citations

Prof. Li’s publications are highly cited within the fields of environmental monitoring, satellite remote sensing, and atmospheric sciences, reflecting the value and influence of his contributions on an international scale. His research continues to shape the discourse around climate resilience, pollution tracking, and advanced remote sensing methods.

🛠️ Technical Skills

His technical expertise includes:  Hyperspectral satellite data processing, Atmospheric modeling and data assimilation, AI and machine learning for environmental monitoring, Payload design and specification for next-generation satellites, Quantitative remote sensing and geospatial analysis.

👨‍🏫 Teaching & Mentoring

In addition to research, Prof. Li is actively involved in mentoring graduate students and early-career scientists, fostering a culture of innovation and collaboration in hyperspectral remote sensing. His guidance has produced a growing cadre of young scientists contributing to China’s leadership in satellite-based environmental science.

🚀 Vision and Future Contributions

Prof. Li’s future goals include expanding the applications of hyperspectral technologies to global-scale monitoring of greenhouse gases and pollutants, developing real-time AI-driven detection frameworks, and enhancing China’s position in next-gen satellite missions. His work is set to continue making a transformative impact on how we monitor and respond to environmental and security-related atmospheric events.

📖Notable Publications

The effectiveness of solar radiation management using fine sea spray across multiple climatic regions
Authors: Z Song, S Yu, P Li, N Yao, L Chen, Y Sun, B Jiang, D Rosenfeld
Journal: Atmospheric Chemistry and Physics
Year: 2025

Photostationary state assumption seriously underestimates NOx emissions near large point sources at 10 to 60 m pixel resolution
Authors: L Chen, Z Song, N Yao, H Xi, J Li, P Gao, Y Chen, H Su, Y Sun, B Jiang, …
Journal: Proceedings of the National Academy of Sciences
Year: 2025

Multi-task deep learning for quantifying methane emissions from 2-D plume imagery with Low Signal-to-Noise Ratio
Authors: Q Xu, X Gu, P Li, X Gu
Journal: International Journal of Remote Sensing
Year: 2024

Less anthropogenic aerosol indirect effects are a potential cause for Northeast Pacific warm blob events
Authors: N Yao, Z Song, L Chen, Y Sun, B Jiang, P Li, J Chen, S Yu
Journal: Proceedings of the National Academy of Sciences
Year: 2024

Different contributions of meteorological conditions and emission reductions to the ozone pollution during Shanghai’s COVID-19 lockdowns in winter and spring
Authors: X Dou, M Li, Y Jiang, Z Song, P Li, S Yu
Journal: Atmospheric Pollution Research
Year: 2024