ARUNACHALASIVAMANI PONNUSAMY | Technology | Young Scientist Award

Mr. ARUNACHALASIVAMANI PONNUSAMY | Technology |Best Researcher Award

šŸ‘Øā€šŸ«Profile Summary

Arunachalasivamani Ponnusamy is a highly motivated researcher pursuing a Doctorate in Food Science and Technology at Prince of Songkla University, Thailand. With a background in Fisheries Science and a master’s degree in Fish Processing Technology, he specializes in diverse research areas, including carbon dots synthesis, edible-active biofilms, and health management of food products. Ponnusamy has published impactful papers, showcasing his expertise in multifunctional films and nanofibrous electrospun blisters. His lab-oriented skills encompass biochemical techniques, lipid oxidation analysis, and microbiological techniques. Awarded prestigious fellowships, he possesses proficiency in MS Office, Origin Pro, and has bilingual proficiency in Tamil and English. Trusted character references commend his work.

šŸŒ Professional Profiles

šŸŽ“ Education:

Secondary Schooling: Sri Vidya Mandir Matric Higher Secondary School, Tamil Nadu, India (2012-2013), Higher Secondary Schooling: Sri Vidya Mandir Matric Higher Secondary School, Tamil Nadu, India (2014-2015), Bachelor of Fisheries Science (B.F.Sc): Dr. MGR Fisheries College and Research Institute, Tamil Nadu, India (2015-2019), Master of Fisheries Science (M.F.Sc) in Fish Processing Technology: Kerala University of Fisheries and Ocean Studies, Kerala, India (2019-2021)

šŸ”¬ Current Research Works:

Carbon dots from agro-wastes and seafood wastes: Morphology, properties, toxicity, and antimicrobial properties. Chitosan-gelatin nanofiber-based multifunctional films integrated with carbon dots and anthocyanins from Clitoria ternatea for active and intelligent food packaging applications. Formation of functional nanofibrous electrospun blister containing EGCG for packaging of shrimp oil capsules.

šŸ” Research Interests:

Bio-engineering (R&D), Waste utilization and management, Health management (Enrichment or value addition of food products), Extraction of bioactive compounds from underutilized resources (seaweeds)

šŸŽ“ Area of Expertise:

Carbon dots synthesis, kinetics, and characteristics. Edible, active, and intelligent packaging techniques. Emulsion – Pickering Emulsion Nanoparticles synthesis and characterization. Shelf-life evaluation of food products

šŸ”¬ Lab-Oriented Skills:

  • Biochemical techniques
  • Lipid oxidation analysis
  • Microbiological techniques
  • Equipment handling

šŸ… Fellowship:

Awarded Reinventing University program for pursuing a Doctorate in Food Science and Technology at Prince of Songkla University, Hat Yai (2022-2025). Awarded National Talent Scholarship (NTS) for pursuing Post-graduation (M.F.Sc) degree (2019-2021).

 

šŸ“šTop Noted Publication

  1. “Storage stability of Asian seabass oil-in-water Pickering emulsion packed in pouches made from electrospun and solvent casted bilayer films from poly lactic acid/chitosan-gelatin blend containing epigallocatechin gallate.” – International Journal of Biological Macromolecules (2024). Link to Paper

 

  1. “Chitosan silver nanoparticle inspired seaweed (Gracilaria crassa) biodegradable films for seafood packaging.” – Algal Research, 78, 103429 (2024). Link to Paper

 

  1. “Bilayer Polylactic Acid and Chitosan/Gelatin Film Containing Epigallocatechin Gallate Prepared through Solvent Casting and Electrospinning: Properties, Bioactivities, and Release Kinetics.” – Journal of Polymers and the Environment (2023). Link to Paper

 

  1. “Ultrasound treated fish myofibrillar protein: Physicochemical properties and its stabilizing effect on shrimp oil-in-water emulsion.” – Ultrasonics Sonochemistry, 98, 106513 (2023). Link to Paper

Hajar Hakkoum | Machine learning | Best Scholar Award

Dr. Hajar Hakkoum | Machine learning |Best Scholar Award

šŸ‘Øā€šŸ«Profile Summary

In my current role as a Postdoctoral Researcher at INRAE in Versailles, France, I specialize in plant cell cycle dynamics through image analysis and compressed fluorescence acquisition. As a Software Engineer at IS Technologies, Courbevoie, France, I contributed to robust server-side components, integrated AI APIs, and enhanced search engine recommendation systems. My Ph.D. in Machine Learning Interpretability from ENSIAS, UM5*, Rabat, involved groundbreaking research in medical AI, including mentoring fellow researchers and contributing to peer-reviewed journals. Proficient in Python, data mining, and deep learning, I possess strengths in scientific writing and presentation skills. Fluent in Arabic, English, French, Spanish, and German, I hold a C1 IELTS certification and received the Best Poster Award at the 15th International Conference on Health Informatics in 2022. Beyond my professional endeavors, I nurture a keen interest in languages, reading, and running. My educational background includes a Software Engineering Degree (Web & Mobile) from ENSIAS, UM5*, Rabat, and completion of Engineering Preparatory Classes at CPGE Salmane Al Faressi in SalƩ, Morocco.

šŸŒ Professional Profiles

šŸ“š Education:

Software Engineering Degree (Web & Mobile): ENSIAS, UM5*, Rabat, MAR (2016-2019). Engineering Preparatory Classes: CPGE Salmane Al Faressi, SalƩ, MAR (2014-2016)

šŸ” Professional Experience:

Postdoctoral Researcher INRAE, Versailles, FR (March 2024 ā€“ Present) Conducting image analysis of plant cell cycle dynamics. Implementing compressed fluorescence acquisition techniques.. Software Engineer IS Technologies, Courbevoie, FR (October 2022 ā€“ February 2024) Developing robust server-side components using ASP.NET and PostgreSQL. Analyzing and integrating AI APIs for text translation, camera filters, and ChatGPT. Enhancing search engine recommendation systems and assessing employee/user satisfaction using Python. PhD in Machine Learning Interpretability in Medicine ENSIAS, UM5, Rabat, MAR (January 2020 ā€“ April 2023) Conducting a systematic literature review on interpretability techniques in medicine. Quantitatively evaluating the interpretability of ML black-box models in medicine. Assessing the impact of categorical feature encoding on ML interpretability techniques in medicine. Guiding two new PhD students in research projects on ML interpretability in Biodiversity and Cybersecurity. Publishing research papers in reputable peer-reviewed journals and conferences emphasizing the significance of interpretability in medical AI. Contributing to the peer-review process within the medical AI domain as a reviewer for the Scientific African journal (Q2 with IF: 2.9). PhD Internship (ERASMUS) Facultad de InformĆ”tica, Murcia, SP (January – June 2022) Investigating the impact of categorical data on interpretability techniques. Participating in interdisciplinary discussions to bridge the gap between ML and domain experts’ needs. Projects and Internships: Final Degree Project – Research Initiation: Interpretability of ANNs for breast cancer diagnosis (Python). Third Year Project – Handwritten Digits and French Numbers Image Recognition using CNNs and collected images (Python). Second Year Internship – ChatBot development for Banks Q/A (.NET). First Year Internship – Checks Amounts Validation for Banks (C#, Azure APIs).

šŸ† Certificates:

IELTS: C1 (8.5 Reading & Listening, 7.5 Speaking, and 6.5 Writing). Best Poster Award: 15th International Conference on Health Informatics (2022)

šŸŽÆ Interests:

Languages: “A different language is a different vision of life.” Reading: “A reader lives a thousand lives before he dies.” Running: “Exercise is a tribute to the heart.”

 

šŸ“šTop Noted Publication

  1. “Interpretability in the medical field: A systematic mapping and review study” (2022, Applied Soft Computing):
    • This paper likely serves as a comprehensive review and mapping study on the topic of interpretability in the medical field, possibly summarizing existing research and identifying trends or gaps in the literature.

 

  1. “Assessing and comparing interpretability techniques for artificial neural networks breast cancer classification” (2021, Computer Methods in Biomechanics and Biomedical Engineering):
    • The focus here is on assessing and comparing interpretability techniques specifically applied to artificial neural networks for breast cancer classification. The paper likely delves into the methods used to make these complex models interpretable.

 

  1. “Ensemble blood glucose prediction in diabetes mellitus: A review” (2022, Computers in Biology and Medicine):
    • This study appears to be a review on ensemble methods for predicting blood glucose levels in the context of diabetes mellitus, exploring the various techniques employed in aggregating predictions for improved accuracy.

 

  1. “Artificial neural networks interpretation using LIME for breast cancer diagnosis” (2020, Trends and Innovations in Information Systems and Technologies):
    • This paper seems to focus on the interpretability of artificial neural networks for breast cancer diagnosis, specifically using the Local Interpretable Model-agnostic Explanations (LIME) technique.

 

  1. “A Systematic Map of Interpretability in Medicine” (2022, HEALTHINF):
    • This paper likely provides a systematic map, possibly a visual representation, of interpretability in medicine. It could outline the landscape of interpretability techniques, their applications, and potential challenges in the medical field.

 

  1. “Global and local interpretability techniques of supervised machine learning black box models for numerical medical data” (2024, Engineering Applications of Artificial Intelligence):
    • This study seems to explore both global and local interpretability techniques applied to supervised machine learning models for numerical medical data. The emphasis is likely on making black-box models more understandable and transparent.

 

  1. “Evaluating Interpretability of Multilayer Perceptron and Support Vector Machines for Breast Cancer Classification” (2022 IEEE/ACS 19th International Conference on Computer Systems andā€¦):
    • This paper likely evaluates the interpretability of two different machine learning models, Multilayer Perceptron and Support Vector Machines, in the context of breast cancer classification.

 

ARUNACHALASIVAMANI PONNUSAMY | Technology | Best Researcher Award

Mr. ARUNACHALASIVAMANI PONNUSAMY | Technology |Best Researcher Award

šŸ‘Øā€šŸ«Profile Summary

Arunachalasivamani Ponnusamy is a highly motivated researcher pursuing a Doctorate in Food Science and Technology at Prince of Songkla University, Thailand. With a background in Fisheries Science and a master’s degree in Fish Processing Technology, he specializes in diverse research areas, including carbon dots synthesis, edible-active biofilms, and health management of food products. Ponnusamy has published impactful papers, showcasing his expertise in multifunctional films and nanofibrous electrospun blisters. His lab-oriented skills encompass biochemical techniques, lipid oxidation analysis, and microbiological techniques. Awarded prestigious fellowships, he possesses proficiency in MS Office, Origin Pro, and has bilingual proficiency in Tamil and English. Trusted character references commend his work.

šŸŒ Professional Profiles

šŸŽ“ Education:

Secondary Schooling: Sri Vidya Mandir Matric Higher Secondary School, Tamil Nadu, India (2012-2013), Higher Secondary Schooling: Sri Vidya Mandir Matric Higher Secondary School, Tamil Nadu, India (2014-2015), Bachelor of Fisheries Science (B.F.Sc): Dr. MGR Fisheries College and Research Institute, Tamil Nadu, India (2015-2019), Master of Fisheries Science (M.F.Sc) in Fish Processing Technology: Kerala University of Fisheries and Ocean Studies, Kerala, India (2019-2021)

šŸ”¬ Current Research Works:

Carbon dots from agro-wastes and seafood wastes: Morphology, properties, toxicity, and antimicrobial properties. Chitosan-gelatin nanofiber-based multifunctional films integrated with carbon dots and anthocyanins from Clitoria ternatea for active and intelligent food packaging applications. Formation of functional nanofibrous electrospun blister containing EGCG for packaging of shrimp oil capsules.

šŸ” Research Interests:

Bio-engineering (R&D), Waste utilization and management, Health management (Enrichment or value addition of food products), Extraction of bioactive compounds from underutilized resources (seaweeds)

šŸŽ“ Area of Expertise:

Carbon dots synthesis, kinetics, and characteristics. Edible, active, and intelligent packaging techniques. Emulsion – Pickering Emulsion Nanoparticles synthesis and characterization. Shelf-life evaluation of food products

šŸ”¬ Lab-Oriented Skills:

  • Biochemical techniques
  • Lipid oxidation analysis
  • Microbiological techniques
  • Equipment handling

šŸ… Fellowship:

Awarded Reinventing University program for pursuing a Doctorate in Food Science and Technology at Prince of Songkla University, Hat Yai (2022-2025). Awarded National Talent Scholarship (NTS) for pursuing Post-graduation (M.F.Sc) degree (2019-2021).

 

šŸ“šTop Noted Publication

  1. “Storage stability of Asian seabass oil-in-water Pickering emulsion packed in pouches made from electrospun and solvent casted bilayer films from poly lactic acid/chitosan-gelatin blend containing epigallocatechin gallate.” – International Journal of Biological Macromolecules (2024). Link to Paper

 

  1. “Chitosan silver nanoparticle inspired seaweed (Gracilaria crassa) biodegradable films for seafood packaging.” – Algal Research, 78, 103429 (2024). Link to Paper

 

  1. “Bilayer Polylactic Acid and Chitosan/Gelatin Film Containing Epigallocatechin Gallate Prepared through Solvent Casting and Electrospinning: Properties, Bioactivities, and Release Kinetics.” – Journal of Polymers and the Environment (2023). Link to Paper

 

  1. “Ultrasound treated fish myofibrillar protein: Physicochemical properties and its stabilizing effect on shrimp oil-in-water emulsion.” – Ultrasonics Sonochemistry, 98, 106513 (2023). Link to Paper

Jundong feng | technology | Women Researcher Award

Assoc Prof Dr . Jundong feng | technology | Women Researcher Award

šŸ‘Øā€šŸ«Profile Summary

Jundong feng, a distinguished academic, holds a doctoral degree in medicine from Chongqing Medical University, commencing a remarkable academic journey. As an associate professor at Nanjing University of Aeronautics and Astronautics, their expertise extends globally, notably contributing to radioactive nuclide disposal research. Pioneering innovative solutions, such as the development of the radiation-resistant strain Y-7, showcases their commitment to impactful biomedical science. Recognized for transformative work in strontium ion removal, publications in esteemed journals and support from prestigious foundations underscore their international acclaim. Driven by a passion for research and development, their groundbreaking contributions shape the future of bioaccumulation studies.

šŸŒ Professional Profiles

 

šŸŽ“ Academic Journey šŸš€

Embarking on a profound academic expedition, I earned my doctoral degree in medicine from Chongqing Medical University. Presently, I contribute as an associate professor at the esteemed School of Materials Science and Technology, Nanjing University of Aeronautics and Astronautics. My scholarly pursuits expanded during a transformative postdoctoral tenure at the Postdoctoral Workstation of the Eastern Theater Command General Hospital from December 2006 to December 2009.

šŸŒ International Research Impact šŸŒ

Focusing on the pressing issue of radioactive nuclide disposal, my research endeavors have left an indelible mark globally. Pioneering principles of biomedical science, our research group achieved a remarkable feat by transforming baker’s yeast into a living radiation-resistant strain (Y-7). This innovative strain not only exhibits outstanding strontium ion removal capability but is also environmentally friendly and non-pathogenic. Through meticulous exploration, we unraveled the intricate pathways involving the Rsn1p protein and L-type calcium ion channels for strontium ion entry into the cells.

šŸ”¬ Innovative Solutions and Recognition šŸ†

Utilizing Y-7 as a carrier, we introduced magnetic yeast adsorbents, revolutionizing the approach to strontium ion removal. The groundbreaking work has been disseminated through multiple publications in top-tier journals in the field, earning recognition and accolades. Notably, the research has received support from prestigious entities like the National Natural Science Foundation of China and the Jiangsu Natural Science Foundation.

šŸ‘Øā€šŸ”¬ Contribution to Research & Development šŸŒ±

Diving deeper into the mechanisms of strontium ion bioaccumulation, CRISPR/Cas9 gene editing technology was employed to engineer Saccharomyces cerevisiae Y-7. The successful construction of a RSN1 gene knockout strain (Y-7-rsn1Ī”) illuminated the pivotal role of RSN1 in regulating strontium ion adsorption. This work represents a pioneering contribution, supported by a robust foundation of collaborative activities and a cumulative impact factor reflecting the last three impactful years.

šŸ“šTop Noted Publication

  1. “Effect of RSN1 gene knockout on the adsorption of strontium ions by irradiated Saccharomyces cerevisiae” (2024) – Published in the Journal of Environmental Radioactivity.

 

  1. “Removal of Sr(II) in Aqueous Solutions Using Magnetic Crayfish Shell Biochar” (2023) – Published in Separations.

 

  1. “Tribo-induced antibacterial and electrochemical performances of CrMoSiCN/Ag coatings in seawater” (2022) – Published in Surface and Coatings Technology

 

  1. “The Performance of Topic Evolution Based on a Feature Maximization Measurement for the Linguistics Domain” (2022) – Published in Axioms.

 

  1. “Effect of Cs(I) and Cr(III) on the adsorption of strontium ion by living irradiated Saccharomyces cerevisiae” (2022) – Published in the Journal of Radioanalytical and Nuclear Chemistry.

 

  1. “Ferroptosis, a new form of cell death defined after radiation exposure” (2022) – Published in the International Journal of Radiation Biology.

 

  1. “Effects of neutron irradiation on ophthalmic fundus structure, visual function and the mechanisms underlying these effects in rats” (2021) – Published in Acta Astronautica.

 

  1. “Long-term corrosion resistance and friction-induced antibacterial enhancement of CrMoSiCN coating on Ti6Al4V alloy” (2021) – Published in Corrosion Science.

 

  1. “Ionizing radiation induces ferroptosis in splenic lymphocytes of mice” (2021) – Published in the International Journal of Radiation Research.

 

  1. “Hematopoietic protection and mechanisms of ferrostatin-1 on hematopoietic acute radiation syndrome of mice” (2021) – Published in the International Journal of Radiation Biology.

 

Muhammad Mudassar Hassan | Graph Theory | Best Researcher Award

Mr . Muhammad Mudassar Hassan | Big Data | Best Researcher Award

šŸ‘Øā€šŸ«Profile Summary

Muhammad Mudassar Hassan is a dedicated Mathematics Lecturer with a strong background in education. Currently serving at Concordia College Sadar Campus in Lahore, Pakistan šŸ‡µšŸ‡°, he imparts knowledge and fosters a deep understanding of mathematics. With an M.Phil in Mathematics from Riphah International University, his research focuses on Graph Theory šŸ“Š, particularly a comparative and computational study of Zagreb Connection Indices of Chemical Graphs. Muhammad has also contributed to international journals as a reviewer šŸ“. His proficiency in digital tools, including Microsoft Word and LaTex, complements his commitment to modern teaching methods šŸ’». Muhammad Mudassar Hassan is not just an educator but a passionate researcher advancing the realms of mathematics šŸ§®.

šŸŒ Professional Profiles

 

šŸ“š Professional Journey in Education

Mathematics Lecturer – Concordia College Sadar Campus Lahore, Pakistan (04/09/2023 ā€“ Present) Currently contributing my expertise as a Mathematics Lecturer, shaping the mathematical acumen of students at Concordia College Sadar Campus Lahore. My responsibilities involve creating an engaging learning environment and fostering a strong foundation in mathematical principles.

Mathematics Lecturer – The Arqam Schools and College, Sanora Colony, Samanabad, Faisalabad (01/09/2021 ā€“ 30/09/2022) Played a pivotal role as a Mathematics Lecturer at The Arqam Schools and College, focusing on delivering quality education and facilitating a comprehensive understanding of mathematical concepts.

Mathematics Lecturer – Officer Science College Jhang (01/01/2019 ā€“ 27/08/2021) Contributed as a Mathematics Lecturer at Officer Science College Jhang, actively participating in the academic development of students and fostering a passion for mathematics.

Mathematics Teacher – Al-Qamar Boys High School Jhang (05/04/2017 ā€“ 01/12/2018) As a Mathematics Teacher, I imparted knowledge at Al-Qamar Boys High School, contributing to the educational growth of students.

Mathematics Lecturer – Study Links Academy Jhang (01/03/2019 ā€“ 10/08/2021) Engaged as a Mathematics Lecturer at Study Links Academy Jhang, where I played a crucial role in educating students and preparing them for academic success.

šŸ‘Øā€šŸ« Reviewer and Continuous Learning Advocate

As part of my commitment to academic excellence, I am currently serving as a reviewer for several international journals, contributing to the peer-review process and ensuring the quality of scholarly publications.

šŸŽ“ Academic Achievements

M.Phil Mathematics – Riphah International University (19/05/2021 ā€“ 29/05/2023) Undertook rigorous research in Graph Theory, earning a commendable CGPA of 3.72/4. My thesis, titled “Comparative and Computational Study of Zagreb Connection Indices of Chemical Graphs,” reflects my dedication to advancing mathematical knowledge.

M.Sc Mathematics – University of Sargodha (19/07/2015 ā€“ 07/07/2017) Successfully completed my Master’s in Mathematics with a notable CGPA of 3.23/4, demonstrating a strong academic foundation.

B.Sc. (Maths A, Math B, and Physics) – University of Punjab (10/12/2012 ā€“ 31/12/2014) Embarked on the academic journey, specializing in Mathematics and Physics, and laying the groundwork for my future endeavors.

 

šŸ“šTop Noted Publication

  • “Computation of Connection-Based Zagreb Indices in Chain Graphs and Triangular Sheets” (2024) – Published in the Journal of Coordination Chemistry. DOI: 10.1080/00958972.2024.2305819

 

 

 

 

Bilel Ammouri | Big Data | Best Researcher Award

Assoc Prof Dr . Bilel Ammouri | Big Data | Best Researcher Award

šŸ‘Øā€šŸ«Profile Summary

Bilel Ammouri is a seasoned Data Scientist, Data Analyst, and Actuary, holding a Ph.D. in Economic Quantitative Methods from the University of Tunis. With a background in Statistics and Information Analysis, he has excelled in academia as an Assistant Professor at the University of Carthage. Bilel’s extensive professional journey includes roles as a Senior Data Scientist at Axefinance and a Mission Leader Quantitative Analyst at Ernst & Young. His expertise spans Machine Learning, Quantitative Analysis, and Data Mining, with proficiency in Python, R, and SAS. Bilel is recognized for developing robust statistical models and credit risk analytics. Passionate about continuous learning, he actively contributes to the field through diverse projects and ongoing research.

šŸŒ Professional Profiles

 

šŸŽ“ Educational Journey

Embarking on a journey of continuous learning, I pursued a Ph.D. in Economic Quantitative Methods at the University of Tunis from 2014 to 2019. My commitment to knowledge didn’t stop there; I obtained a degree in Engineering with a focus on Statistics and Information Analysis from the University of Carthage in 2012 and a Master’s in Industrial Economics from the University of Tunis between 2003 and 2008.

šŸ’¼ Professional Expedition

Assistant Professor at the University of Carthage (Since December 2022) In my current role, I serve as an Assistant Professor in Quantitative Methods. Leading the quality committee, my responsibilities extend to modules covering diverse topics like Biometrics, Deep Learning, Algorithms and Programming, E-commerce, and Business Plan.

Mission Leader Quantitative Analyst at Ernst & Young (October 2022 – March 2023) At Ernst & Young, I assumed the role of Mission Leader Quantitative Analyst in Actuarial services. My mission involved comparing scenarios with external consensus, auditing normative principles related to valuation and accounting of ECL, and developing a default probability model for the factoring sector under IFRS9.

Senior Data Scientist at Axefinance (May 2019 – September 2022) My tenure at Axefinance as a Senior Data Scientist was marked by the development of statistical and machine learning models, including credit risk models, fraud detection systems, and various data mining initiatives. I played a key role in assessing model stability, performance, and conducting regular reviews. Additionally, I contributed to the development of a financial document recognition model and a framework for scorecard calculation.

Statistical Expert at ARAB MAGHREB UNION, Rabat, Morocco (April 2016 – November 2016) During my time at ARAB MAGHREB UNION, I served as a statistical expert, contributing to the design of a macroeconomic indicators database for Arab Maghreb countries. I was responsible for preparing periodic reports based on these indicators.

šŸš€ Technical Proficiencies

My technical arsenal includes over 5 years of hands-on experience in Machine Learning, Quantitative Analysis, Data Mining, and extensive use of tools like Python, R, MATLAB, SAS, Power BI, Tableau, and SQL.

šŸŒŸ Personal Touch

A creative and diligent individual, I possess a strong ability to adapt to various work environments and cultures. Known for my optimism, I excel in team collaboration and effective people management.

šŸ” Continuous Development and Specialized Training

To stay at the forefront of technological advancements, I consistently invest in my skill set. Recent endeavors include training in Artificial Intelligence and Deep Learning for Medical Applications and a Masterclass in Machine Learning for Credit Risk Analytics conducted in Python & SAS.

šŸŒ Global Exposure

My educational and professional pursuits have not only been confined to Tunisia but have expanded globally, including experiences in Frankfurt, Germany, and diverse projects impacting economic performance in Tunisia.

 

šŸ“šTop Noted Publication

  • “The Dynamics of Ecological Convergence to an Economic Model of Degrowth through Coherence Wavelet Analysis” (2023) – Published in Sustainable Futures. DOI: 10.1016/j.sftr.2023.1001271

 

  • “Does time-frequency scale analysis predict inflation? Evidence from Tunisia” (2021) – Published in the International Journal of Computational Economics and Econometrics. DOI: 10.1504/IJCEE.2021.114551

 

  • “The growth-CO2 emissions relationship and its effect on sustainable development: Evidence from coherence wavelet analysis” (2019) – Published in the Journal of Energy and Development.

 

  • “Forecasting inflation in Tunisia during instability: Using dynamic factors model a two-step based procedure based on kalman filter” (2019) – Published in the International Journal of Computational Economics and Econometrics. DOI: 10.1504/IJCEE.2019.097794

 

  • “Causality links among renewable energy consumption, CO2 emissions, and economic growth in Africa: evidence from a panel ARDL-PMG approach” (2017) – Published in Environmental Science and Pollution Research. DOI: 10.1007/s11356-017-8850-7

 

  • “The Dynamic Effects of Time, Health, and Well-Being on Pollution: A Post-Johannesburg Earth Summit Assessment” (2017) – Published in the Journal of Energy and Development.

 

  • “Dynamic effects of mergers and acquisitions on the performance of commercial European banks” (2016) – Published in the Journal of Knowledge Economy. DOI: 10.1007/s13132-016-0389-1

 

Srinivasan Jayakumar | Organic | Best Researcher Award

Ā Dr . Srinivasan Jayakumar | Organic | Best Researcher Award

šŸ‘Øā€šŸ«Profile Summary

Dynamic, versatile, and self-motivated Research Scientist with eight years of expertise in Synthetic Organic and Medicinal Chemistry. A pragmatic strategist adept at crafting research strategies aligned with organizational priorities. Proven ability to manage complex research schedules, delivering results on demanding projects.šŸ§Ŗ

Passionate about hands-on organic synthesis, possessing extensive knowledge in modern organic chemistry, crystallization techniques, metal-catalyzed reactions, and multi-step synthesis. Proficient in purification using flash column chromatography, Combi Flash, Gilson, Isolera, and spectroscopic characterization of novel compounds. Specialized in Drug discovery, Lead optimization, and Synthesis Characterization of Anti-viral Drugs, focusing on viral infections, macular degeneration, and neuropathic painšŸŒ

šŸŒ Professional Profiles

 

šŸŽ“ Education

Ph.D. in Organic Chemistry, National Tsing Hua University, Taiwan (2011-2020), Title: Synthesis of Quinolinoquinolines by a New Domino Reaction and Hinged Aromatic Compounds against Enterovirus 71, Masters in Chemistry, Gurunanak College, University of Madras, India (2003-2005) Bachelors in Chemistry, Gurunanak College, University of Madras, India (2000-2003)

šŸ”¬Ā Professional and Research Experience

Rensselaer Polytechnic Institute, Troy, NY (Jan 2022 ā€“ Present) Postdoctoral Research Associate (Department of Chemistry and Chemical Biology) Title: Synthesis of GlyT2 inhibitors to treat Neuropathic pain Albany College of Pharmacy and Health Sciences, Albany, NY (July 2020 ā€“ Dec 2021) Postdoctoral Research Associate (Department of Basic and Clinical Sciences, Department of Pharmaceutical Sciences) Title: Age-Related Macular Degeneration Syngene International Limited, India (June 2006 ā€“ Jan 2011) Research Associate II Job responsibilities include research and development of new synthetic pathways, Suzuki coupling, Grignard reaction, and monitoring reaction progress using analytical techniques.

šŸ“šĀ Editorial Board and Committee (2023-Present)

Editorial board member at the International Journal of Pharmacy and Chemistry, Editorial board member at Online Journal of Chemistry. Editorial board member at the International Journal of Science and Management Studies Editorial board member at Archives of Pharmacy & Pharmacology Research Community associate membership at ACS. Serving as a member of the Selection Committee for Graduate Scholarships and Awards at the University of Ottawa.

šŸ”Journal Reviewer and Peer- Reviewing

Demonstrated expertise in the organic and medicinal field through service as a reviewer for Eleven reputable organic chemistry journals. Reviewer at Pharmacy & Pharmacology International Journal.

šŸŒŸ Research Highlight

Participated in extramurally funded small molecule drug discovery research focusing on indications like dry AMD, neuropathic pain, and viral infections. Key projects include the design and development of novel transthyretin (TTR) tetramer kinetic stabilizers and inhibitors of glycine transporter 2 (GlyT2).

šŸ”¬Skillset

Synthesis, purification, and characterization of structurally diverse organic compounds, Broad knowledge of Synthetic Organic and Medicinal chemistry. Experience with using Chem Draw, Chem Sketch, ISIS draw, Beilstein, Reaxys, and SciFinder. Proven experience in synthetic organic chemistry, process optimization, and technology transfer. Purification using reverse-phase preparative HPLC and method development. Expertise in scale-up, product development, mass spectrometry, lead optimization, and peer

 

šŸ“šTop Noted Publication

  • “The efficacy of the analgesic GlyT2 inhibitor, ORG25543, is determined by two connected allosteric sites.”
    • Authors: Cantwell Chater, Ryan; Quinn, Ada; Wilson, Katie; Frangos, Zachary; Sutton, Patrick; Jayakumar, Srinivasan; Cioffi, Christopher; O’Mara, Megan; Vandenberg, Robert
    • Published: J. Neurochem. 2023, 00, 1ā€“20
    • DOI: 10.1111/jnc.16028

 

  • “Novel Phenylene Lipids That Are Positive Allosteric Modulators of Glycine Receptors and Inhibitors of Glycine Transporter 2”
    • Authors: Casey I. Gallagher, Zachary J. Frangos, Diba Sheipouri, Susan Shimmon, Meryem-Nur Duman, Srinivasan Jayakumar, Christopher L. Cioffi, Tristan Rawling, Robert J. Vandenberg
    • Published: ACS Chem. Neurosci. 2023, 14, 15, 2634ā€“2647
    • DOI: 10.1021/acschemneuro.3c00167

 

  • “Bis(Benzofuranā€“1,3-N,N-heterocycle)s as Symmetric and Synthetic Drug Leads against Yellow Fever Virus.”
    • Authors: Nitesh K. Gupta, Srinivasan Jayakumar, Wen-Chieh Huang, Pieter Leyssen, Johan Neyts, Sergey O. Bachurin, Jih Ru Hwu, Shwu-Chen Tsay
    • Published: Int. J. Mol. Sci. 2022, 23, 12675.
    • DOI: 10.3390/ijms232012675

 

  • “Identification of Transthyretin Tetramer Kinetic Stabilizers That Are Capable of Inhibiting the Retinol-Dependent Retinol Binding Protein 4-Transthyretin Interaction: Potential Novel Therapeutics for Macular Degeneration, Transthyretin Amyloidosis, and Their Common Age-Related Comorbidities.”
    • Authors: Christopher L. Cioffi, Arun Raja, Parthasarathy Muthuraman, Aravindan Jayaraman, Srinivasan Jayakumar, Andras Varadi, Boglarka Racz, Konstantin Petrukhin
    • Published: J. Med. Chem. 2021, 64, 13, 9010āˆ’9041.
    • DOI: 10.1021/acs.jmedchem.1c00099

 

  • “Enterovirus Inhibition by Hinged Aromatic Compounds with Polynuclei.”
    • Authors: Jih Ru Hwu, Avijit Panja, Srinivasan Jayakumar, Shwu-Chen Tsay, Kui-Thong Tan, WenChieh Huang, Yu-Chen Hu, Pieter Leyssen, Johan Neyts
    • Published: Molecules 2020, 25, 3821.
    • DOI: 10.3390/molecules25173821

 

  • “Synthesis and Human Anticancer Cell Line Studies on Coumarin- āˆ’carboline Hybrids as Possible Antimitotic Agents.”
    • Authors: S. Samundeeswari, Manohar V. Kulkarni, Shrinivas D. Joshi, Sheshagiri R. Dixit, Srinivasan Jayakumar, R. M. Ezhilarasi
    • Published: ChemistrySelect 2016, 1, 5019ļ€­5024.
    • DOI: 10.1002/slct.201601020

 

 

Jatin Chaudhary | Image processing | Young Scientist Award

Ā Mr . Jatin Chaudhary | Image processing | Young Scientist Award

šŸ‘Øā€šŸ«Profile Summary

Ā Research trainee at the University of Pennsylvania’s Image Computing and Science Lab, focusing on medical imaging and software development. Ā Worked on aortic valve ultrasound data analysis, segmentation, and contributed to open-source software. Ā Research trainee at the University of Turku in Data Science & Machine Learning, utilizing Python and MATLAB for optimization problems in solar cells. Undergraduate researcher at SV National Institute of Technology, India, exploring advanced optics. Ā Achievements include independent research funding, travel funding, and recognition for research excellence. Ā Experienced mentor and private tuition teacher. Presented papers globally and awarded for innovation. Passionate about cutting-edge research at the intersection of technology and healthcarešŸŒŸ

šŸŒ Professional Profiles

 

šŸŽ“ Education

University of Turku, Department of Future Technologies, Turku, Finland, Doctoral Researcher (Data Science & Machine Learning) Supervisor: Prof. Jukka Heikkonen July 2021 ā€“ Present. Major Responsibilities: Mathematical Analysis of Algorithms, Dataset Preprocessing, Implementation of Algorithms, drafting Research Articles, etc. Working on Algorithm Designing of Image processing techniques for Satellite Images from Sentinel 1 and Sentinel 2 satellites. Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat, India Bachelors of Technology (B.Tech) in Electronics and Communication Engineering 2017-2021 Cumulative GPA: 7.13/10

šŸ‘Øā€šŸ’¼ Professional Experience

Penn Image Computing and Science Laboratory, University of Pennsylvania (Remote, Part-time), Research Trainee (Medical Imaging and Software Development) Supervisor: Prof. Alison Pouch February 2021-Present Major Responsibilities: Data Analysis and Segmentation of Aortic Valve Ultrasound data using ITK Snap, VTK, MATLAB, C3D. Algorithm Designing of Image Segmentation of 4D image using C3D. Contribution to an open-source software. University of Turku, Department of Future Technologies, Turku, Finland Research Trainee (Data Science & Machine Learning)Supervisor: Prof. Jukka Heikkonen August 2018-May 2019 (Remote, Part-time) / June 2019-July 2019 (In-Person, Full Time) / August 2019-June 2021 (Remote, Part-time) Utilized Python (TensorFlow, Keras, scikit-learn, pandas) and LaTeX. MATLAB implementation of Artificial Neural Network techniques for the optimization problem of Single Junction Solar Cells. SV National Institute of Technology, Applied Physics Department, Surat, India Undergraduate Researcher (Advance Optics Research Laboratory) Supervisor: Prof. Vipul Kheraj September 2017-July 2018 Worked on the deflection of particle nature of light ray by a strong external electric and magnetic field.

šŸ’”Skills

Medical Imaging Analysis: ITK, VTK, C3D, Programming Languages: C++, Python, Machine Learning: Python libraries (Tensorflow, Keras, scikit-learn, numpy, pandas), Data Science Algorithms: Support Vector Machine, Convolutional Neural Network, Artificial Neural Network, Long Short Term Memory (LSTM), K Nearest Neighbour (KNN)

šŸš€Ā Projects

Bachelors’ Thesis (Advisor: Prof. Suman Deb) NIT, Surat Emotion Detection of Sound using Deep Learning for Emergency Usage (August 2020-May 2021) Working on Emotion Detection of sound data to deploy it to law enforcement agencies’ surveillance systems. Algorithms: SVM, CNN, LSTM, Inception model on Keras and Tensorflow.

šŸ“„Ā Paper and Poster Presentation

Oral presentation of paper entitled ā€œOptimization of Silicon Tandem Solar Cells Using Artificial Neural Networksā€ at the 39th SGAI International Conference on Artificial Intelligence, Cambridge University, England. Poster presentation of the paper entitled ā€œPerformance Analysis of Back Surface Field (BSF) Effects in Multijunction Photovoltaic Cellā€ at the 47th IEEE Photovoltaic Specialists Conference (PVSC), Canada (Virtual Meeting). Oral presentation of the paper entitled ā€œHuman Presence Detection with Thermal Sensor using Multilayer Perceptron Algorithmā€ at the 2021 IEEE 7th World Forum on Internet of Things (WF-IoT), New Orleans, Louisiana, USA (Virtual Meeting). Research Talk on ā€œNumerical Investigations on the Type-II Band Alignment and Quantum Efficiency of Multijunction Solar Cell using Andersonā€™s Ruleā€ at the Indian Institute of Technology (IIT), Roorkee, India.

šŸ‘Øā€šŸ« Teaching Experience

2022 (Mar-Sept): Supervisor Supervised two undergraduate students for their theses based on object detection at the harbor in Finland. 2020-2021: Private Tuition Teacher (Part-time) Tutored high school students in Elementary Physics, Mechanics and Relativity, Electricity and Magnetism, Calculus, Energy Science, and Technology. 2018-2020: Mentor Mentored younger undergraduate students on Computer Programming (Weekly). Provided guidance on C/Python Programming Language.

šŸ†Achievements

Secured independent funding from the University of Turku for two years of research. Funding Amount: 57,000 EUR. Secured travel funding from the Smarter Project (an EU project) for a research travel of up to six months. Funding Amount: 18,000 EUR (approx). Awarded the Research Excellence Award by the First Bionicsol Young India Innovator Contest in 2020. Awarded a scholarship for undergraduate studies by the Embassy of India, Kathmandu, under the Compex Scholarship Scheme.

 

šŸ“šTop Noted Publication

  • Liu M., Chaudhary J., Pouch A.
    • Title: Virtual Reality for Image-Based Quantitative Assessment of the Aortic Root.
    • Status: Ongoing

 

  • Chaudhary, J., Bhattacharya, S., Heikkonen, J., & Kanth, R.
    • Title: Optimization of Photovoltaic Cells using Artificial Intelligence Techniques: Systematic Literature Review
    • Status: To be submitted to Artificial Intelligence, Elsevier

 

  • Chaudhary, J., Pant, D. R., Pokharel, S., Skƶn, J. P., Heikkonen, J., & Kanth, R.
    • Title: Image Quality Assessment by Integration of Low-level & High-Level Features: Threshold Similarity Index.
    • Conference: 2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)
    • Published: June 2022, pp. 135-141, IEEE

 

  • Chaudhary, J., Bhattacharya, S., Heikkonen, J., & Kanth, R.
    • Title: Prediction of Electron Band Gap of A2XY6 Perovskite Compounds using Machine Learning.
    • Conference: 2022 IEEE 49th Photovoltaics Specialists Conference (PVSC)
    • Published: June 2022, pp. 1173-1176, IEEE

 

  • Chaudhary, J.K., Liu, J., Skƶn, J.-P., Chen, Y.W., Kanth, R.K., Heikkonen, J.
    • Title: Optimization of Silicon Tandem Solar Cells Using Artificial Neural Networks.
    • Published: Lecture Notes in Computer Science, 2019, pp. 392ā€“403. DOI: 10.1007/978-3-030-34885-4_30

 

  • J. Chaudhary, R. Kanth, J. Skƶn, and J. Heikkonen
    • Title: Performance Analysis of Back Surface Field (BSF) Effects in Multijunction Photovoltaic Cell.
    • Conference: 47th IEEE Photovoltaic Specialists Conference (PVSC), 2020, pp. 1207-1211, DOI: 10.1109/PVSC45281.2020.9301018

 

  • J. K. Chaudhary, R. Kanth, J. Skƶn and J. Heikkonen
    • Title: Analysis and Enhancement of Quantum Efficiency for Multi-Junction Solar Cell.
    • Conference: 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC), 2019, pp. 0210-0214, doi: 10.1109/PVSC40753.2019.8980684

 

  • Kanth, R., Korpi, T., Toppinen, A., MyllymƤki, K., Chaudhary, J., Heikkonen, J.
    • Title: Educational Approach to the Internet of Things (IoT) Concepts and Applications.
    • Published: DOI: 10.5121/csit.2019.91320

 

  • L. Puurunen, J. Chaudhary, R. Kanth and J. Heikkonen
    • Title: Human Presence Detection with Thermal Sensor using Multilayer Perceptron Algorithm.
    • Conference: 2021 IEEE 7th World Forum on Internet of Things (WF-IoT), 2021, pp. 669-673, doi: 10.1109/WF-IoT51360.2021.9595529.