Mr. Utkarsh Lal | Computational Neuroscience Award | Best Researcher Award

Posted on by ScienceFather

Mr. Utkarsh Lal | Computational Neuroscience Award | Best Researcher Award

Mr. Utkarsh Lal, Manipal Institute of Technology, india

Utkarsh Lal is a versatile data scientist and engineer with a strong academic background and extensive professional experience. He holds a Bachelor of Technology in Computer Science and Engineering with a Specialization in Big Data from Manipal Institute of Technology. Currently employed as a Data Engineer at Amazon, Utkarsh previously worked as a Data Science Consultant at StatusNeo, where he collaborated with Reliance Jio to develop predictive models for e-retail platforms. His expertise spans various domains, including machine learning, data architecture, and cloud computing, as evidenced by his roles at American Express, Accenture, and Kimberly-Clark. Utkarsh is also an accomplished researcher with publications in prestigious journals and certifications in data science and cloud technologies. Additionally, he has received recognition for his contributions, including the Best Paper award at the ICEEICT conference and selection as an AI mentee for the KaggleX BIPOC scholarship program. With a diverse skill set and a passion for innovation, Utkarsh continues to make significant contributions to the field of data science and engineering.

Professional profile:

Scopus

Google Scholar

Orcid

🎓 Education:

Utkarsh Lal obtained his Bachelor of Technology in Computer Science and Engineering with a specialization in Big Data from Manipal Institute of Technology, Karnataka, completing his studies from July 2017 to July 2021. This comprehensive program equipped him with the necessary skills and knowledge to excel in the field of computer science, with a specific focus on handling and analyzing large-scale data sets.

💼 Work Experience:

Utkarsh Lal has gained extensive professional experience across various prestigious organizations. Starting as an Agile Analytics Engineer Intern at Kimberly-Clark, Bangalore, from January 2021 to July 2021, he honed his skills in analytics and data engineering. Subsequently, he transitioned to Accenture, Gurugram, as a Data Science Analyst from August 2021 to March 2022, where he further developed his expertise in data analytics. Following this, Utkarsh held the role of Analyst – Product Development at American Express, Gurugram, from March 2022 to June 2022, focusing on product enhancement and risk analysis. He then served as a Data Science Consultant at StatusNeo, Gurugram, from August 2022 to December 2023, working on predictive modeling and analytics projects. Currently, he holds the position of Data Engineer at Amazon, Gurugram, from February 2024 onwards, contributing to data-driven solutions and innovations.

🛠️ Projects:

Utkarsh Lal has spearheaded several impactful projects across diverse domains. Notable among these is the development of a Product Popularity Forecaster and Calculator for Reliance JIO, aimed at predicting and quantifying product popularity on e-retail platforms. He also led the implementation of an End-to-End Data Architecture for Churn Analysis on Google Cloud at Accenture AI, facilitating insightful analysis of customer behavior. Additionally, Utkarsh contributed to pioneering research in Facial Emotion Recognition using CNN at MIT, advancing the field of computer vision. His expertise extends to predictive modeling, as demonstrated by his work on a Loan Default Prediction Supervised Classifier and a Sentiment Classifier with Web Crawler for product reviews, both at Kimberly Clark. Furthermore, he has engaged in exploratory projects in Computational Neuroscience, showcasing his versatility and commitment to cutting-edge research and innovation.

🏅 Scholarships & Achievements:

Utkarsh Lal’s contributions have been acknowledged through prestigious accolades. His research paper on negation handling in natural language processing (NLP) earned him the Best Paper award at the ICEEICT (IEEE) conference, showcasing his expertise and innovation in the field. Additionally, Utkarsh was selected as an AI mentee for the KaggleX BIPOC scholarship program in the 2023 cohort, receiving a grant of $1,000. These achievements underscore his dedication to advancing knowledge and expertise in artificial intelligence and data science

Publication Top notes:

  1. Effective Negation Handling Approach for Sentiment Classification using synsets in the WordNet lexical database
    • Authors: U Lal, P Kamath
    • Year: 2022
  2. Temporal Feature Extraction and Machine Learning for Classification of Sleep Stages Using Telemetry Polysomnography
    • Authors: U Lal, S Mathavu Vasanthsena, A Hoblidar
    • Year: 2023
  3. Fractal dimensions and machine learning for detection of Parkinson’s disease in resting-state electroencephalography
    • Authors: U Lal, AV Chikkankod, L Longo
    • Year: 2024
  4. A Comparative Study on Feature Extraction Techniques for the Discrimination of Frontotemporal Dementia and Alzheimer’s Disease with Electroencephalography in Resting-State Adults
    • Authors: U Lal, AV Chikkankod, L Longo
    • Year: 2024
  5. Leveraging SVD Entropy and Explainable Machine Learning for Alzheimer’s and Frontotemporal Dementia Detection using EEG
    • Authors: U Lal, AV Chikkankod, L Longo
    • Year: 2023

 

 

 

 

 

Mr. Adegboyega Adebayo | Computational Epidemiological Modeling Award | Best Researcher Award

Posted on by ScienceFather

Mr. Adegboyega Adebayo | Computational Epidemiological Modeling Award | Best Researcher Award

Mr. Adegboyega Adebayo, National Open University of Nigeria,  Nigeria

Mr. Adegboyega Adebayo is a highly accomplished individual with a diverse educational background, culminating in a PhD in Health Data Analytics from the Federal University of Technology, Akure, Nigeria. With expertise in Pattern Recognition and Intelligent Systems, he earned an MPhil/PhD and an MSc in Computer Science, and a BSc in Computer Science from the same institution. Adept in research, Adebayo has led projects at the Faculty of Science, National Open University, Nigeria, and as a Graduate Research Fellow at eHealth for Everyone Foundation. He excels in teaching, currently serving as an Assistant Lecturer at National Open University, Nigeria, and has a track record of mentorship, previously tutoring at NIIT Limited, Nigeria. Noteworthy achievements include developing innovative solutions like an Autonomous Intelligent Gate-passing System and co-supervising post-graduate thesis projects, all while being recognized for academic excellence and research contributions. 🎓🔬

Professional Profile:

Google Scholar

🎓 Education:

  • PhD in Health Data Analytics, Federal University of Technology, Akure, Nigeria (2021-2024)
  • MPhil/PhD in Pattern Recognition and Intelligent Systems, Federal University of Technology, Akure, Nigeria (2019-2021)

🔍 Research Interests:

  • Health Data Analytics
  • Educational Technology
  • Deep Learning

👨‍💼 Research Experience:

  • Project Lead at Faculty of Science, National Open University, Nigeria
  • PhD Student at Federal University of Technology, Akure, Nigeria
  • Graduate Research Fellow at eHealth for Everyone Foundation

📚 Teaching & Mentorship:

  • Assistant Lecturer at National Open University, Nigeria, teaching undergraduate courses in Computer Science
  • Previously served as a Java Tutor at NIIT Limited, Nigeria, and as a Teacher during the National Youth Service Corps

🌟 Achievements:

  • Developed innovative solutions like an Autonomous Intelligent Gate-passing System
  • Co-supervised post-graduate thesis projects
  • Recognized for excellence in academic performance and research contributions

Publications Top Notes :

  1. Enhancing Epidemiological Surveillance Systems Using Dynamic Modeling: A Scoping Review
    • Published in the International Conference on Soft Computing and Pattern Recognition in 2021.
    • Cited by 2 articles.
  2. Tracking Dynamics Change Parameters of Chaotic Infectious Disease Outbreak with Bifurcated Time-Series Long Short-Term Memory Model
    • Published in Scientific African in 2024.
  3. Development of English to Yoruba Machine Translator, Using Syntax-based Model
    • Published in the University of Ibadan Journal of Science and Logics in ICT Research in 2021.