Dr. Faranak Hatami | Computational Chemistry | Best Researcher Award

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Dr. Faranak Hatami | Computational Chemistry | Best Researcher Award

Dr. Faranak Hatami , Computational Chemistry , PhD at University of massachuessetes Lowell, United States

Faranak Hatami (Fara) is a dedicated physicist and researcher specializing in molecular dynamics simulations, machine learning, and nuclear materials science. Currently pursuing her Ph.D. in Physics at the University of Massachusetts Lowell, she focuses on transport property analysis and multi-objective optimization for molecular systems like Tri-Butyl-Phosphate (TBP). Faranak holds two master’s degrees—one in Physics from UMASS Lowell, where she explored force fields for TBP, and another in Nuclear Engineering from Shahid Beheshti University, where she investigated radiation damage in metals. With a robust background in computational physics, AI, and advanced simulation tools, she has authored multiple publications across nuclear materials and computational chemistry. Her teaching experience spans both the U.S. and Iran, reflecting her passion for education. Beyond academia, she completed a research internship at the University of Montreal. Faranak’s work bridges fundamental physics and practical applications, contributing innovative insights to the fields of material science and chemical engineering.

Professional Profile : 

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Summary of Suitability for Award:

Faranak Hatami is a highly suitable candidate for a “Best Researcher Award”. She demonstrates exceptional multidisciplinary expertise spanning physics, molecular dynamics, machine learning, and nuclear materials science. Her Ph.D. work at UMASS Lowell innovatively combines atomic-scale simulations with AI to optimize force field parameters for Tri-Butyl-Phosphate, addressing both fundamental science and practical applications.  She has authored several impactful publications in reputable journals and preprints, covering diverse topics from radiation damage in metals to machine learning models predicting thermodynamic properties. Her research portfolio includes complex computational modeling, multi-objective optimization, and advanced materials analysis. Additionally, Faranak’s teaching record and successful research internship in Canada reflect her commitment to knowledge dissemination and international collaboration. Her ability to merge computational physics with machine learning showcases originality and forward-thinking, key attributes for top research honors. Faranak Hatami embodies the qualities of a best researcher: scientific rigor, innovative thinking, multidisciplinary skillset, and impactful publications. Her contributions significantly advance computational methods in physical sciences and engineering, making her a strong and deserving candidate for a “Best Researcher Award”.

🎓Education:

 Faranak Hatami is completing her Ph.D. in Physics at the University of Massachusetts Lowell (2021–2025), with her thesis focused on transport property analysis and optimization of force field parameters for Tri-Butyl-Phosphate (TBP), combining atomic-scale simulations with machine learning. Prior to this, she earned her M.Sc. in Physics from the same university in 2023, where she conducted a comparative study of force fields for liquid TBP using molecular dynamics. Earlier, she obtained her M.Sc. in Nuclear Engineering from Shahid Beheshti University in Iran (2016), where she examined radiation damage effects on zirconium and iron grain boundaries through simulations. Her academic journey began with a B.S. in Electrical Engineering from Kurdistan University in 2013. Throughout her studies, Faranak has integrated advanced computational methods, AI, and experimental data analysis, building a multidisciplinary foundation that connects physics, materials science, and engineering disciplines.

🏢Work Experience:

Faranak Hatami brings diverse experience across research, teaching, and technical projects. At UMASS Lowell, she serves as a Teaching Assistant in Physics while pursuing her Ph.D., guiding students through complex concepts. Previously, she lectured on Computational Methods and Statistical Methods and Physics courses at Shahid Beheshti University between 2014 and 2018. Her research career includes an internship at the University of Montreal (2019–2021), exploring hydrogen’s effects on iron grain boundaries using the kinetic activation relaxation technique (k-ART). Faranak has led significant academic projects spanning molecular dynamics simulations, multi-objective optimization, and machine learning applications in material science. She has deep expertise in computational tools such as LAMMPS, MCNP, VASP, and Python-based AI frameworks. Her work reflects a unique blend of fundamental physics research, practical problem-solving, and advanced data analysis, contributing to fields like chemical engineering, nuclear materials, and computational modeling.

🏅Awards: 

 Faranak Hatami has built an impressive research portfolio during her academic career, reflected in multiple publications and conference presentations. While specific named awards were not explicitly listed in her profile, her contributions have earned her recognition through invited presentations such as at the AIChE Annual Meeting, showcasing her expertise in molecular dynamics simulations and force field optimization. Completing dual M.Sc. degrees in Physics and Nuclear Engineering highlights her dedication and academic excellence. Her selection as a research intern at the University of Montreal, working on advanced computational studies in materials science, further underscores her capability and esteem in her field. Through her multidisciplinary approach integrating AI, molecular modeling, and nuclear materials science, she stands out as a rising scholar contributing valuable insights to computational physics and chemical engineering. As she advances her Ph.D., she is poised for further accolades in research innovation and scientific community engagement.

🔬Research Focus:

 Faranak Hatami focuses her research on the intersection of molecular dynamics simulations, machine learning, and materials science. Her Ph.D. work centers on analyzing transport properties and optimizing force field parameters for Tri-Butyl-Phosphate (TBP) using multi-objective optimization algorithms like NSGA-II/III. She applies molecular dynamics to predict critical thermodynamic and transport properties, integrating neural networks for parameter tuning. Additionally, she explores AI-based classification of microscopy and atomic-scale images, blending physics with cutting-edge data science. Faranak’s earlier research in nuclear engineering examined radiation damage in metals such as zirconium and nickel, utilizing techniques like climbing image nudged elastic band (CI-NEB) for defect analysis. She’s also investigated hydration free energies, grain boundary behaviors, and primary knock-on atom (PKA) spectra in irradiated materials. Her work bridges computational physics with practical engineering challenges, advancing predictive models and simulation methods to better understand complex molecular and material systems.

Publication Top Notes:

✅ Comparative Analysis of Machine Learning Models for Predicting Viscosity in Tri-n-Butyl Phosphate Mixtures Using Experimental Data

Citations: 6

✅ Quantification of Methane Hydration Energy Through Free Energy Perturbation Method

✅ Comparison of Different Machine Learning Approaches to Predict Viscosity of Tri-n-Butyl Phosphate Mixtures Using Experimental Data

Citations: 3

✅ Properties of Tri-Butyl-Phosphate from Polarizable Force Field MD Simulations

Citations: 1

✅ A Revision of Classical Force Fields for Tri-N-Butyl Phosphate Molecular Dynamics Simulations

✅ Interaction of primary cascades with different atomic grain boundaries in α-Zr: An atomic scale study

Citations: 34

✅ An energetic and kinetic investigation of the role of different atomic grain boundaries in healing radiation damage in nickel

Citations: 31

Dr. Peng Wang | Computational Modeling | Best Researcher Award

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Dr. Peng Wang | Computational Modeling | Best Researcher Award

Dr. Peng Wang | Computational Modeling | Lecturer at School of Mining and Coal Engineering, Inner Mongolia University of Science and Technology, China

Peng Wang is a Lecturer at the School of Mining and Coal Engineering, Inner Mongolia University of Science and Technology. His research primarily focuses on mine safety, coal spontaneous combustion mechanisms, and numerical simulation techniques. With a strong academic background, he has led innovative studies on coal gangue heap oxidation and spontaneous combustion hazard zones, contributing significantly to the field of mining safety. Over the past three years, he has published 9 academic papers as first or corresponding author, with 7 indexed in SCI/EI journals. He has successfully led two research projects, including the prestigious Inner Mongolia Autonomous Region Doctoral Research Innovation Grant. Additionally, he has played a key role as a technical lead in three industry projects. His contributions to coal safety and emergency management were recognized in 2024 when he was awarded the First Prize for Outstanding Paper at the Safety and Emergency Management Talent Development Conference.

Professional Profile :         

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Scopus 

Summary of Suitability for Award:

Peng Wang is a highly qualified candidate for the “Best Researcher Award” due to his significant contributions to coal spontaneous combustion mechanisms and mine safety. With over 15 research publications, including 7 SCI/EI-indexed papers as the first or corresponding author, he has demonstrated strong research expertise. He has successfully led two research projects, including the Inner Mongolia Autonomous Region Doctoral Research Innovation Grant, and has been a technical lead in three major projects. His interdisciplinary work, combining numerical simulation and experimental analysis, provides groundbreaking insights into fire prevention in mining. His contributions have been recognized with the First Prize for Outstanding Paper at the Safety and Emergency Management Talent Development Conference (2024). Considering Peng Wang’s research impact, publications, awards, and leadership in industry collaborations, he is a highly suitable candidate for the “Best Researcher Award” in the field of Mine Safety and Coal Combustion Prevention.

🎓Education:

Peng Wang holds a strong academic background in mining and coal engineering. He completed his doctoral studies in mine safety, focusing on the spontaneous combustion of coal gangue heaps and numerical simulations for risk mitigation. His research has been instrumental in developing new strategies for preventing coal-related hazards in dry and windy mining regions. His Ph.D. research was supported by the Inner Mongolia Autonomous Region Doctoral Research Innovation Grant, highlighting its significance in industrial safety applications. He pursued his graduate and undergraduate studies in mining engineering, equipping himself with deep technical expertise in coal combustion mechanisms and mineral-reagent interactions. His educational journey has laid a robust foundation for his research contributions in spontaneous combustion safety, mine ventilation, and fire prevention strategies. Through continuous academic pursuits, he has built a strong profile in applied mining safety and innovative coal research.

🏢Work Experience:

Peng Wang has extensive experience in the field of mining safety and coal combustion research. As a Lecturer at Inner Mongolia University of Science and Technology, he has been actively involved in both academic and industry projects. Over the years, he has led two major research projects, including one funded by the Inner Mongolia Autonomous Region. Additionally, he has contributed as a technical lead to three large-scale industry projects focused on mine safety and fire prevention. His expertise extends to numerical simulation methods, allowing him to model coal oxidation processes and spontaneous combustion risks effectively. His contributions as a member of the China Coal Society further demonstrate his active engagement in scientific communities. With a strong research output of 15 journal papers and participation in key national projects, he continues to advance the safety protocols and preventive measures in coal mining operations.

🏅Awards: 

Peng Wang has received several prestigious recognitions for his outstanding contributions to mining safety and coal spontaneous combustion research. In 2024, he was awarded the First Prize for Outstanding Paper at the Safety and Emergency Management Talent Development Conference for his significant work on coal gangue spontaneous combustion mechanisms. His research excellence was also acknowledged through the Inner Mongolia Autonomous Region Doctoral Research Innovation Grant, which supported his pioneering studies in mine fire prevention. As a major contributor to the National Natural Science Foundation of China, he has played a crucial role in advancing coal safety research at the national level. Additionally, he has served as a technical lead in three large-scale industry projects, focusing on risk mitigation in coal mining operations. His active membership in the China Coal Society further highlights his professional engagement in developing innovative strategies for fire prevention and mine safety improvements.

🔬Research Focus:

Peng Wang specializes in mine safety, with a strong emphasis on preventing coal spontaneous combustion and improving fire mitigation strategies. His research has led to groundbreaking studies on the oxidation and air seepage properties of coal gangue heaps, crucial for determining spontaneous combustion hazard zones. By integrating numerical simulation techniques, he has developed models that predict and control combustion risks in coal mines. His interdisciplinary approach combines thermodynamics, fluid mechanics, and chemistry to enhance the understanding of coal oxidation dynamics. His findings offer theoretical and practical solutions for mining operations in dry and windy regions, ensuring improved safety measures. With a strong commitment to industrial application, his work has influenced national policies on coal safety, and his collaborations with the National Natural Science Foundation of China have strengthened research advancements in the field. His studies continue to play a vital role in reducing environmental hazards and ensuring mine worker safety.

Publication Top Notes:

A study on the thermal behavior of coal gangue mountains under airflow influence based on MD and CFD simulations​

New Insights into the Depressive Mechanism of Sodium Silicate on Bastnaesite, Parisite, and Fluorite: Experimental and DFT Study

Study on the air permeability characteristics of coal gangue dump slope gangue particles​

Study on the variability of oxygen adsorption behavior in coal gangue based on pore size structure​

Analysis of failure mode and deformation evolution characteristics of slopes under the influence of highwall mining​

Experimental study and molecular simulation of spontaneous combustion of coal gangue by oxidation under different water contents​

Study on adsorption-diffusion-seepage behavior of oxygen in coal gangue under the coupling of temperature and pressure​

Study on the Law of Repeated Mining Strata Movement and Surface Subsidence in Close Distance Coal Seam​

Synergistic Adsorption and Molecular Arrangement of Mixed Surfactants at the Air/Water Interface​

DFT Calculation of BHA and SHA and Its Flotation Performance on Bastnaesite

Flotation effect and quantum chemical calculation of octyl hydroxamic acid and sodium silicate on bastnaesite and fluorite

Depression behavior and mechanism of sodium silicate on bastnaesite and parisite flotation

DFT calculation of octyl hydroxamic acid and oleic acid and their flotation performance comparison on bastnasite and fluorite

Mechanism of sodium sulfide on flotation of cyanide-depressed pyrite

Ms. Shrimanti Chakraborty | Computational Chemistry Award | Best Researcher Award

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Ms. Shrimanti Chakraborty | Computational Chemistry Award | Best Researcher Award

Ms. Shrimanti Chakraborty, Birla Institute of Technology, Mesra , India

Shrimanti Chakraborty is a dedicated aspiring research scientist in the field of Medicinal Chemistry. Currently pursuing a Master of Pharmacy in Pharmaceutical Chemistry at Birla Institute of Technology, Mesra, India, she is passionate about advancing pharmaceutical solutions that impact human health. With a solid academic foundation, she has contributed to research on green synthesis of nanoparticles and novel antimicrobial compounds. She has also gained valuable industry experience through internships and research projects, such as her work on molecular docking studies and drug discovery. As a dedicated student leader, Shrimanti holds various academic and extracurricular positions, contributing to her professional growth and development in scientific fields.

 

Professional Profile:

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Summary of Suitability for Award:

Shrimanti Chakraborty is a highly qualified and accomplished researcher with a strong track record in academic achievements, publications, and practical experience. Her research in medicinal chemistry, combined with her leadership skills and industry exposure, makes her an excellent candidate for the Best Researcher Award. Her contributions to the scientific community are poised to make a significant impact, showcasing her as an emerging leader in the field.

 

🎓Education:

Shrimanti Chakraborty completed her Bachelor of Pharmacy (BPharm) with 93.4% from Birla Institute of Technology, Mesra, in 2023. Currently, she is pursuing a Master of Pharmacy (MPharm) in Pharmaceutical Chemistry at the same institution, where she has secured an impressive 92.9%. Her academic foundation is strengthened by high achievements, including 94.75% in Higher Secondary and 94.8% in Matriculation, both from St. Joseph’s Convent, Chandannagar. Throughout her education, she has consistently displayed excellence in both theoretical knowledge and practical skills, focusing on pharmaceutical sciences, organic synthesis, and medicinal chemistry.

🏢Work Experience:

Shrimanti has gained invaluable professional experience through internships and industrial training. She worked at Dr. Reddy’s Laboratories, Hyderabad, contributing to clinical trial analysis and reporting. As part of the Khorana Program for Scholars, she interned at Purdue University, USA, under IUSSTF, gaining exposure to global pharmaceutical research. Additionally, Shrimanti participated in the Molecular Biology and Biochemistry Techniques program at IIT Kharagpur and Mendine Pharmaceuticals Pvt. Ltd. She is also involved in ongoing research projects, including her MPharm thesis on novel imidazole analogues. Her hands-on expertise includes computational modeling, molecular docking, and synthetic organic chemistry.

 

🏅Awards:

Shrimanti has earned recognition for her academic and professional achievements. She won the 1st prize along with a cash prize of INR 10,000 in the Flash Talk Competition at the International Symposium on Nucleic Acids Research by NIPER Kolkata. Her excellence in Mathematics ISC 2019 earned her rank 1, while in WIZ National Spell Bee 2014-15, she secured rank 2 and was honored with a cash prize. She also achieved rank 47 in the State Level Grand Finale of WIZ National Spell Bee. These accomplishments highlight her commitment to academic excellence, public speaking, and leadership in scientific endeavors.

 

🔬Research Focus:

Shrimanti’s research primarily focuses on Medicinal Chemistry, specifically in areas like molecular docking, drug design, and pharmacology. She has worked on green synthesis of iron/iron oxide nanoparticles, novel antimicrobial agents, and molecular dynamics. Her ongoing work includes imidazole analogues with potential antimicrobial activity, and phytoconstituents docking studies targeting Parkinson’s disease. She utilizes advanced computational techniques such as HTVS, AutoDock, Schrodinger, and Desmond for structure-based drug design. Her aim is to contribute to the development of innovative pharmaceutical solutions for treating chronic diseases and improving human health.

Publication Top Notes:

  1. Fundamental approaches of drug discovery
  2.  Comparative Molecular Docking Studies of Selected Phytoconstituents on the Dopamine D3 Receptor (PDB ID: 3PBL) as Potential Anti-Parkinson’s Agents