Ferdib Al Islam | Machine Learning | Excellence in Research

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Mr. Ferdib Al Islam | Machine Learning | Excellence in Research

Assistant Professor, Northern University of Business and Technology Khulna Bangladesh

Ferdib-Al-Islam is an Assistant Professor at Northern University of Business and Technology Khulna, Bangladesh. He holds a Master’s and Bachelor’s degree in Computer Science and Engineering from Khulna University of Engineering & Technology (KUET) and Bangabandhu Sheikh Mujibur Rahman Science and Technology University (BSMRSTU), respectively. His research expertise encompasses Machine Learning, Deep Learning, IoT, Data Science, and Computer Vision. Ferdib’s career includes experience as a software engineer in IoT R&D and lecturer roles, contributing significantly to academic and research pursuits.

Publication Profile

Google Scholar

🎓 Education

M.Sc. Eng. in Computer Science and Engineering from KUET (2023) – GPA: 3.50. B.Sc. Eng. in Computer Science and Engineering from BSMRSTU (2018) – GPA: 3.55. HSC in Science from Govt. PC College, Bagerhat (2012) – 5.00. SSC in Science from Bagerhat Govt. Secondary School (2010) – 5.00

💼 Experience

Ferdib has progressed from an intern to a Senior Lecturer, and now an Assistant Professor at Northern University of Business and Technology Khulna. He served as a Lecturer in Computer Science and Engineering from March 2020 to January 2024. His career also includes a Jr. Software Engineer role at W3 Engineers Ltd. in the IoT R&D sector. Ferdib brings practical industry experience into his academic roles, fostering innovation and research.

🏆 Awards & Honors

Ferdib has earned notable accolades, including the Gold Award at Semarak International Research Article Competition III 2024 for his work on Autism Spectrum Disorder detection. He also received the Best Paper Award at ICETIS 2021 for his research on Diabetes Mellitus prediction and the Honorable Mention Award at BDML 2020 for his IoT-based health monitoring tool.

🔬 Research Focus

Ferdib’s primary research interests are in Machine Learning, Deep Learning, IoT, Large Language Models, and Computer Vision. His work focuses on the application of AI techniques to healthcare, predictive modeling, and intelligent systems. His aim is to leverage machine learning for real-world applications like healthcare diagnostics, smart monitoring systems, and data-driven insights in various fields.

Conclusion

Ferdib Al-Islam is an exceptional researcher with notable accomplishments in machine learning, deep learning, and IoT. His commitment to advancing knowledge in these areas, demonstrated by his numerous awards and research contributions, marks him as a leading figure in his field. However, fostering greater interdisciplinary collaborations and increasing his global academic presence will be beneficial for his continued growth as a researcher. He is undoubtedly a deserving candidate for the Excellence in Research award, given his dedication, achievements, and potential for further contributions to the scientific community.

Publication Top Notes

  • Prediction of Cervical Cancer from Behavior Risk Using Machine Learning Techniques
    • Year: 2021
    • Authors: L Akter, Ferdib-Al-Islam, MM Islam, MS Al-Rakhami, MR Haque
    • Citation: 73
  • An IoT Enabled Health Monitoring Kit Using Non-Invasive Health Parameters
    • Year: 2021
    • Authors: A Das, SD Katha, MS Sadi, Ferdib-Al-Islam
    • Citation: 31
  • Hepatocellular Carcinoma Patient’s Survival Prediction Using Oversampling and Machine Learning Techniques
    • Year: 2021
    • Authors: Ferdib-Al-Islam, L Akter, MM Islam
    • Citation: 21
  • An Enhanced Stroke Prediction Scheme Using SMOTE and Machine Learning Techniques
    • Year: 2021
    • Authors: Ferdib-Al-Islam, M Ghosh
    • Citation: 20
  • Early Identification of Parkinson’s Disease from Hand-drawn Images using Histogram of Oriented Gradients and Machine Learning Techniques
    • Year: 2020
    • Authors: Ferdib-Al-Islam, L Akter
    • Citation: 19
  • Dementia Identification for Diagnosing Alzheimer’s Disease using XGBoost Algorithm
    • Year: 2021
    • Authors: L Akter, Ferdib-Al-Islam
    • Citation: 17
  • COV-VGX: An automated COVID-19 detection system using X-ray images and transfer learning
    • Year: 2021
    • Authors: P Saha, MS Sadi, OFMRR Aranya, S Jahan, FA Islam
    • Citation: 9
  • Detection of Hepatitis C Virus Progressed Patient’s Liver Condition Using Machine Learning
    • Year: 2022
    • Authors: Ferdib-Al-Islam, L Akter
    • Citation: 6*
  • Diabetes Mellitus Prediction and Feature Importance Score Finding Using Extreme Gradient Boosting
    • Year: 2021
    • Authors: L Akter, Ferdib-Al-Islam
    • Citation: 4
  • COV-Doctor: A Machine Learning Based Scheme for Early Identification of COVID-19 in Patients
    • Year: 2022
    • Authors: Ferdib-Al-Islam, M Ghosh
    • Citation: 3*
  • Breast Cancer Risk Prediction Using Different Clustering Techniques
    • Year: 2022
    • Authors: L Akter, M Raihan, M Raihan, M Sarker, M Ghosh, N Alvi, Ferdib-Al-Islam
    • Citation: 3
  • Crop-RecFIS: Machine Learning Classifiers for Crop Recommendation and Feature Importance Scores Calculation
    • Year: 2023
    • Authors: MS Sanim, KM Hasan, MM Alam, MAA Walid, MR Islam
    • Citation: 2
  • Prediction of Dementia Using SMOTE Based Oversampling and Stacking Classifier
    • Year: 2023
    • Authors: Ferdib-Al-Islam, MS Sanim, MR Islam, S Rahman, R Afzal, KM Hasan
    • Citation: 2*
  • An Ensemble Learning Model to Detect COVID-19 Pneumonia from Chest CT Scan
    • Year: 2022
    • Authors: PC Shill
    • Citation: 2

 

 

 

Nastaran Mehrabi Hashjin | Artificial intelligence | Best Researcher Award

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Mr. Nastaran Mehrabi Hashjin | Artificial intelligence | Best Researcher Award

Mr at Shahid beheshti university Iran

Nastaran Mehrabi Hashjin is a researcher and engineer with a background in control and electronic engineering. She specializes in AI, medical imaging, and brain-computer interfaces. With a focus on diagnosing Alzheimer’s disease and optimizing AI algorithms, she has published multiple articles in top-tier journals. Nastaran has also contributed to UAV monitoring and fault detection in power systems. A member of Iran’s National Elite Foundation, she actively engages in research on neural networks, optimization algorithms, and advanced medical data processing. She is proficient in programming, circuit design, and VLSI systems, showcasing her technical acumen.

Profile

Scopus

Orcid

Scholar

🎓 Education

Ph.D. Candidate, Control Engineering (2023-2024) Shahid Beheshti University, Tehran, Iran | Elite Foundation Member. M.Sc. in Control Engineering (2021-2024) Shahid Beheshti University, Tehran, Iran | GPA: 3.54/4.0 | Alzheimer’s diagnosis using neural networks. B.Sc. in Electronic Engineering (2016-2020) Shomal University, Amol, Iran | GPA: 3.52/4.0 | PIR sensor system design

💼 Experience

Graduate: System Identification, Non-linear Control, Modern Systems. Undergraduate: Electromagnetism, Electrical Machines, Labs Engineer, Tarashe Pardazane Jahan. Designed electronic circuits for smart doors. Intern, Mazandaran Electric Company. Energy distribution monitoring and operational map updates.

🏆 Awards and Honors

Member, Iran’s National Elite Foundation. Ph.D. admission via Elite Foundation. Certifications in neuroscience and medical imaging (TUMS). Advanced neuroscience and AI courses (Shahid Beheshti University)

🔬 Research Focus

AI-driven fault detection in power plants. Brain-computer interfaces and Alzheimer’s diagnostics. Optimization algorithms: Type-3 fuzzy logic, HO algorithm. Medical imaging: FSL, CONN, Freesurfer

🌟 Conclusion

Nastaran Mehrabi Hashjin is an exemplary candidate for the Best Researcher Award due to their innovative contributions to AI-driven fault diagnosis, optimization, and medical imaging. Their rigorous academic record, diverse expertise, and impactful publications make them a strong contender. Addressing minor gaps in global collaboration and community engagement will further enhance their standing as a leader in their field.

Publications 📚

Hyung-Pil Chang | Deep Learning | Best Researcher Award

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Mr. Hyung-Pil Chang | Deep Learning | Best Researcher Award

Mr at Korea University,  South Korea

Hyung-pil Chang is a dedicated graduate student at Korea University, pursuing a Ph.D. in Computer Science and Engineering. With a keen interest in deep learning and speech processing, he focuses on enhancing communication between humans and machines. He has contributed to several innovative projects in voice conversion and speech recognition, demonstrating a commitment to advancing technology in these fields. In addition to his academic pursuits, Chang actively engages in various sports and cultural activities, reflecting a well-rounded personality. His passion for research is complemented by his desire to develop practical solutions for real-world problems in artificial intelligence.

Profile

Scopus

Orcid

Scholar

Education 🎓

Hyung-pil Chang began his academic journey at Hansung University, where he earned a Bachelor of Science in Information System and Engineering from March 2014 to February 2020. He continued his studies at Korea University, obtaining a Master of Science in Computer Science and Engineering from 2020 to 2022. Currently, he is pursuing his Doctor of Philosophy in the same field at Korea University, enhancing his knowledge and expertise in deep learning, speech recognition, and human-computer interaction.

Experience 💼

Chang has gained valuable experience as a research assistant at Korea University’s Artificial Intelligence Laboratory since March 2020, working under the guidance of Prof. Dongsuk Yook. He has also served as a teaching assistant for undergraduate courses in Artificial Intelligence and Machine Learning, honing his teaching skills and sharing his knowledge with students. Additionally, he briefly worked in the Voice Generation Team at KT on a multi-modal project, where he contributed to advancements in voice conversion technologies, further solidifying his practical experience in the field.

Awards and Honors 🏆

Hyung-pil Chang has received recognition for his academic and research achievements, including publications in reputable journals such as MDPI Applied Sciences and IEEE Access. His contributions to voice conversion and speaker anonymization research have garnered attention in the field of speech processing. While specific awards are not listed, his active participation in conferences and collaboration on innovative projects highlight his commitment to excellence in research and development, positioning him as an emerging talent in artificial intelligence and deep learning.

Research Focus 🔬

Chang’s research centers on enhancing communication between people and machines, particularly in speech processing. He aims to improve speech recognition models using self-training techniques on large amounts of unlabeled data. His work also explores explainable AI and the development of a general-purpose domain agent capable of interacting with humans across various tasks, including vision and natural language processing. Key areas of focus include speech recognition, synthesis, voice conversion, and human-computer interaction, contributing to advancements in multi-modal language models.

📝 Conclusion

Hyung-pil Chang demonstrates strong potential as a leading researcher in deep learning and speech processing. His academic background, research contributions, and innovative spirit position him well for the Best Researcher Award. By focusing on collaboration, expanding his publication record, and engaging more with the broader community, he can enhance his impact even further. Given his current trajectory, he is well on his way to making significant contributions to his field and is a worthy candidate for recognition.

Publications Top Notes

  • Wav2wav: Wave-to-Wave Voice Conversion
    C Jeong, H Chang, IC Yoo, D Yook
    Applied Sciences, 2024, 14(10), 4251.

 

  • Zero-Shot Unseen Speaker Anonymization via Voice Conversion
    HP Chang, IC Yoo, C Jeong, D Yook
    IEEE Access, 2022, 10, 130190-130199.

 

  • CycleDiffusion: Voice Conversion Using Cycle-Consistent Diffusion Models
    D Yook, G Han, HP Chang, IC Yoo
    Applied Sciences, 2024, 14(20), 9595.

 

 

 

Rouholla Bagheri| Deep Learning | Best Researcher Award

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Assoc Prof Dr. Rouholla Bagheri | Thermodynamics | Best Researcher Award

Assoc Prof Dr. Ferdowsi University of Mashhad Iran

Dr. Rouholla Bagheri is an Assistant Professor in the Department of Management at Ferdowsi University of Mashhad, Iran. He holds a Ph.D. in Systems Management from Shahid Beheshti University, focusing on knowledge networks in the automotive sector. With a distinguished academic record, Dr. Bagheri has received numerous awards, including the 26th National Outstanding Student Award. His research interests span IoT healthcare systems, supply chain networks, and multi-objective optimization. An active member of various professional associations, he has published extensively in peer-reviewed journals, contributing significantly to the fields of information systems and management.

 

Publication profile

 

🎓 Educational Background

Ph.D. in Systems Management (2013-2018) Shahid Beheshti University, Iran Dissertation: Design a Model of Developing Knowledge Networks in the Car Engine Research Center, GPA: A+. MBA (2012) Amirkabir University, Iran, GPA: A. B.Eng. in Computer Software Engineering (2005)
Bahonar University, Iran, GPA: B

📚 Current Professional Memberships

Member, International Scientific Committee and Editorial Review Board, World Academy of Science, Engineering, and Technology. Member, Council of Knowledge Management in Iran. Member, AIS (Association for Information Systems) of Iran. Member, AKS (Association for Knowledge Management) of Iran. Head, Business Intelligence Department, Association of Management of Iran

🏆 Honors and Awards

Distinguished Assistant Professor, Ferdowsi University (2022). National Outstanding Student Award Winner (2012, 2017). National Science Foundation Award (2013). Book of the Year Award in Information Systems and Management (2010)

Publication

    1. Assessing dimensions influencing IoT implementation readiness in industries: A fuzzy DEMATEL and fuzzy AHP analysis
      Authors: MZ Nezhad, J Nazarian-Jashnabadi, J Rezazadeh, M Mehraeen, …
      Year: 2023

     

    1. BERT-deep CNN: State of the art for sentiment analysis of COVID-19 tweets
      Authors: JH Joloudari, S Hussain, MA Nematollahi, R Bagheri, F Fazl, …
      Year: 2023

     

    1. The mediator role of KM process for creative organizational learning case study: knowledge based companies
      Authors: R Bagheri, MR Hamidizadeh, P Sabbagh
      Year: 2015

     

    1. Examining the impact of product innovation and pricing capability on the international performance of exporting companies with the mediating role of competitive advantage
      Authors: J Rezazadeh, R Bagheri, S Karimi, J Nazarian-Jashnabadi, MZ Nezhad
      Year: 2023

     

    1. The relationship of knowledge management and organizational performance in Science and Technology Parks of Iran
      Authors: MA Haghighi, R Bagheri, PS Kalat
      Year: 2015

     

    1. The Evaluation of Knowledge Management Maturity Level in a Research Organization
      Authors: R Bagheri, P Eslami, S Mirfakhraee, M Yarjanli
      Year: 2013

     

    1. Factors affecting the implementation of the blue ocean strategy: A case study of Medicom production manufacturing company
      Authors: R Bagheri, SP Eslami, M Yarjanli, N Ghafoorifard
      Year: 2013

     

    1. Modelling the factors affecting the implementation of knowledge networks
      Authors: A Rezaeian, R Bagheri
      Year: 2017

     

    1. Revolutionizing supply chain sustainability: An additive manufacturing-enabled optimization model for minimizing waste and costs
      Authors: P Roozkhosh, A Pooya, O Soleimani Fard, R Bagheri
      Year: 2024

     

    1. Robust cooperative maximal covering location problem: A case study of the locating Tele-Taxi stations in Tabriz, Iran
      Authors: H Rezazadeh, S Moghtased-Azar, MS Kisomi, R Bagheri
      Year: 2018

     

    1. Examining the Relationship between organizational Climate and Entrepreneurship with regard to Staff’s Locus of Control in Industry Companies in Iran
      Authors: R Bagheri, M Yarjanli, R Mowlanapour, N Mahdinasab
      Year: 2016

     

    1. Investigating the Effect of Perceived Ethical Leadership on Knowledge Hiding: A Case Study on an Automobile Factory
      Authors: F Imani, G Eslami, R Bagheri
      Year: 2022

    Conclusion 🎓

    Rouholla Bagheri exemplifies the qualities of a strong candidate for the Best Researcher Award, with a robust educational background, a significant publication portfolio, and numerous accolades. By focusing on applied research, enhancing collaborative efforts, and increasing public engagement, he can further amplify his impact in the field of information systems and management. His dedication to advancing knowledge and fostering innovation positions him as a valuable asset to academia and beyond.

seyed matin malakouti | AI | Best Researcher Award

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seyed matin malakouti | AI | Best Researcher Award

Seyed Matin Malakouti is an accomplished Electrical Engineering professional specializing in machine learning and control systems. He holds an MS in Control System Engineering from the University of Tabriz and a BS in Electrical Engineering from Isfahan University of Technology. Malakouti has published extensively on topics including wind power prediction, temperature change modeling, and heart disease classification. His work has appeared in prominent journals such as Energy Exploration & Exploitation and Case Studies in Chemical and Environmental Engineering. He has received recognition for his research, including awards for Best Researcher and nominations for Best Paper. Malakouti’s research interests span applied machine learning, renewable energy, and biomedical signal processing. He is also an active peer reviewer for various scientific journals.

Publication profile

google scholar

🎓 Education

MS in Electrical Engineering – Control System Engineering University of Tabriz, Tabriz, Iran (2019 – 2022). BS in Electrical Engineering
Isfahan University of Technology (IUT), Isfahan, Iran (2014 – 2019)

🏢 Professional Experience

Undergraduate Teaching Assistant Dept. of Electrical Engineering, Isfahan University of Technology (IUT) (2015 – 2018) Assisted in teaching core courses such as Calculus I, II, Electrical Circuit I, II, and Electronics II.

🏆 Awards & Fellowships

Best Researcher, International Conference on Cardiology and Cardiovascular Medicine (2023). Nominated for Best Paper Award, International Research Awards on Mathematics and Optimization Methods (2023)

👨‍🏫 Teaching Experience

Spring 2018: Calculus I, Teaching Assistant. Spring 2017: Calculus II, Teaching Assistant. Fall 2016: Electrical Circuit I, Teaching Assistant. Spring 2015: Electrical Circuit II, Teaching Assistant

Research for Best Researcher Award: Seyed Matin Malakouti

🌟 Strengths for the Award

  1. Diverse Research Contributions: Seyed Matin Malakouti has an extensive list of publications covering a broad range of topics, from wind power generation and temperature change prediction to heart disease classification and asteroid detection. This indicates a high level of versatility and a strong ability to apply machine learning across different domains.
  2. Cutting-Edge Techniques: His work utilizes advanced machine learning techniques such as CNN-LSTM, ensemble methods, and Bayesian optimization. This demonstrates a commitment to leveraging state-of-the-art methods to address complex problems.
  3. High-Impact Publications: Malakouti has published in high-impact journals such as Energy Exploration & Exploitation, Biomedical Signal Processing and Control, and Case Studies in Chemical and Environmental Engineering. His work is also recognized by prestigious conferences and has received nominations for awards.
  4. Peer Review Engagement: Active involvement in peer review for numerous reputable journals reflects his expertise and recognition within the academic community.
  5. Awards and Recognition: Being named the Best Researcher at an international conference and receiving nominations for best paper awards highlights his research’s quality and impact.

🔍 Areas for Improvement

  1. Broader Impact Assessment: While his technical contributions are substantial, including a focus on how his research impacts broader societal and industrial contexts could further enhance his profile. Emphasizing real-world applications and collaborations could demonstrate the practical significance of his work.
  2. Interdisciplinary Collaboration: Engaging in interdisciplinary projects could further enrich his research profile. Collaborating with researchers from other fields, such as environmental science or healthcare, could lead to innovative solutions and increase the impact of his work.
  3. Public Engagement and Outreach: Increasing efforts in public science communication and outreach could help bridge the gap between academic research and public understanding. Engaging with non-academic audiences through popular science articles, talks, or educational programs could be beneficial.

Publication top notes

  1. Title: Predicting wind power generation using machine learning and CNN-LSTM approaches
    Citations: 46
    Year: 2022
    Journal: Wind Engineering 46(6), 1853-1869

 

  1. Title: Heart disease classification based on ECG using machine learning models
    Citations: 39
    Year: 2023
    Journal: Biomedical Signal Processing and Control 84, 104796

 

  1. Title: Utilizing time series data from 1961 to 2019 recorded around the world and machine learning to create a Global Temperature Change Prediction Model
    Citations: 37
    Year: 2023
    Journal: Case Studies in Chemical and Environmental Engineering 7, 100312

 

  1. Title: The usage of 10-fold cross-validation and grid search to enhance ML methods performance in solar farm power generation prediction
    Citations: 32
    Year: 2023
    Journal: Cleaner Engineering and Technology 15, 100664

 

  1. Title: Use machine learning algorithms to predict turbine power generation to replace renewable energy with fossil fuels
    Citations: 26
    Year: 2023
    Journal: Energy Exploration & Exploitation 41(2), 836-857

 

  1. Title: Evaluation of the application of computational model machine learning methods to simulate wind speed in predicting the production capacity of the Swiss basel wind farm
    Citations: 21
    Year: 2022
    Journal: 2022 26th International Electrical Power Distribution Conference (EPDC), 31-36

 

  1. Title: Improving the prediction of wind speed and power production of SCADA system with ensemble method and 10-fold cross-validation
    Citations: 19
    Year: 2023
    Journal: Case Studies in Chemical and Environmental Engineering 8, 100351

 

  1. Title: Estimating the output power and wind speed with ML methods: a case study in Texas
    Citations: 17
    Year: 2023
    Journal: Case Studies in Chemical and Environmental Engineering 7, 100324

 

  1. Title: Babysitting hyperparameter optimization and 10-fold-cross-validation to enhance the performance of ML methods in Predicting Wind Speed and Energy Generation
    Citations: 15
    Year: 2023
    Journal: Intelligent Systems with Applications 19, 200248

 

  1. Title: AERO2022-flying danger reduction for quadcopters by using machine learning to estimate current, voltage, and flight area
    Citations: 15
    Year: 2022
    Journal: e-Prime-Advances in Electrical Engineering, Electronics and Energy 2, 100084

 

  1. Title: Prediction of wind speed and power with LightGBM and grid search: case study based on Scada system in Turkey
    Citations: 8
    Year: 2023
    Journal: International Journal of Energy Production and Management 8.

 

🏆 Conclusion

Seyed Matin Malakouti is a strong candidate for the Research for Best Researcher Award due to his diverse and impactful research contributions, utilization of advanced machine learning techniques, and recognition within the academic community. By focusing on broader impact, interdisciplinary collaboration, and public engagement, he can further enhance his research profile and increase the overall impact of his work.

Mohammad Mohammadpour | Motion planning | Best Researcher Award

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Dr. Mohammad Mohammadpour | Motion planning| Best Researcher Award

 Dr. University of Quebec at Trois-Rivières, Canada

👩‍🔬 Ph.D. in Mechanical Engineering with over eight years of specialized experience in R&D, contributing to cutting-edge projects at two renowned institutions.

 

Profile

Scopus

 

Education 🎓

Ph.D. in Mechanical Engineering (Robotics), University of Quebec at Trois Rivières, QC, Trois Rivières, Canada; May 2019-Feb 2024Master’s degree in Aerospace Engineering (Flight Dynamic & Control), Amirkabir University of Technology, Tehran, Iran; 2014Bachelor’s degree in Mechanical Engineering, Tehran, Iran; 2011

Skills 🛠️

Programming Language: Python, C++Software: ROS, Gazebo, Rviz, MATLAB & Simulink Research: Navigation and Sensor Data Fusion Motion Planning (Guidance)Movement Sciences (Kinetic & Kinematic)Dynamic Modelling and Control Machine Learning and Deep Learning Obstacle Avoidance Applications: Autonomous Mobile Robots (simulation and experiment)Learning Frameworks: Scikit-learn, Keras, TensorFlow

Experience 🚀 Robotics Engineer

Hydrogen Research Institute, University of Quebec at Trois Rivières, Trois Rivières, QC, Canada; 2019-2024Dynamic modeling, simulating, and analyzing robots’ motion Implementing motion planning (guidance) algorithms on an Autonomous Mobile Robot and an Autonomous Forklift (simulation and experiment)Developing motion planning (guidance) algorithms using deep neural networks and the robots’ kinetic models (simulation and experiment)Designing and implementing motion controllers (simulation and experiment). Research And Development Engineer Research Center of Amirkabir University of Technology, Tehran, Iran; 2015-2019Contributed to the Attitude Determination And Control System Executed MIL, SIL, PIL, and HIL simulation and testing Conducted operation and calibration tests of sensors Participated in dynamic modelling

Publications Top Notes 📝

i. Energy-efficient motion planning of an autonomous forklift using deep neural networks and kinetic model, Authors: M. Mohammadpour et al., 2023

 

ii. Energy-efficient Local Path Planning of a Self-Guided Vehicle by Considering the Load Position, Authors: Not provided, 2022

 

iii. An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots, Authors: M. Mohammadpour et al., 2021

 

 

sofia aftab | Neural network | Best Researcher Award

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 Ms. sofia aftab | Neural network | Best Researcher Award

Ms. Norges Teknisk-Naturvitenskapelige Universitet, Norway

👩‍🔬 Highly experienced Data Scientist with expertise in research, data science, machine learning, advanced analytics, and Generative AI. Proficient in Python, SQL, SAS, Teradata, R, and QlikView. Possesses strong skills in business analysis, model building, and communication. Excels in statistical techniques, machine learning algorithms, deep learning frameworks, NLP, data engineering, and Generative AI. Experienced in agile project management and collaborative team environments.🌟

Profile

Scopus

 

 

Scholar

 

🎓📚Academics

  • MS (IT) specialization in Data Mining/Analytics from NUST
  • Ph.D (Machine Learning/Data Science) from NTNU

 

💼📊Career Skills/Knowledge

Over 12 years of experience as an enthusiastic Data Scientist Strong business analysis and data mining skills Expertise in model building and execution Proficient in segmentation and customer value management analytics Skilled in statistical techniques including regression, A/B testing, and statistical significance of ML models Experienced in machine learning algorithms such as NN, SVM, Naive Bayes, ensemble modeling, and deep learning (DNN)Knowledgeable in NLP techniques, data engineering, MLOps, and cloud deployments Experienced in Generative AI techniques including prompt engineering, Lang chain, and Semantic search Research-focused with experience in improving evaluation metrics and developing recommendation algorithms Proficient in agile project management methodologies

🏢💼Experience

Accenture-Norway (Aug 2022 – Present)Data Science Consultant/Team Lead Built and maintained data and ML pipelines Developed ML models and CI/CD workflows Collaborated with cross-functional teams Led agile projects and worked on Generative AI Telenor-Norway (Dec 2020 – Aug 2022)Data Scientist Evaluated and improved ML projects Transformed business questions into analysis Led agile projects and presented to management NTNU (Apr 2018 – 2020)Research Scientist Worked on Recommendation systems using deep learning Improved evaluation metrics for recommender systems HPE (May 2016 – 2018)Data Scientist (Consultant)Identified cross-sell and upsell opportunities Developed and maintained next best action engine Telenor (Aug 2015 – May 2016)Specialist Advance Analytics and Consumer Insight Conducted subscriber analysis and developed churn/retention framework Telenor (Aug 2013 – Aug 2015)Executive Advance Analytics and Consumer Insight Developed behavioral segmentation and churn prediction models Protégé Global (Aug 2012 – 2013)Team Lead Data Miner/Data Scientist Managed a team for data mining projects and conducted exploratory data analysis Muhammad Ali Jinnah University (MAJU) (2012 – 2013)Lecturer, Trainer National University of Science and Technology (NUST) (2011 – 2012)Research Assistant

Publications Top Notes 📝

  1. Title: Data Mining in Insurance Claims (DMICS) Two-way mining for extreme values
    • Authors: S Aftab, W Abbas, MM Bilal, T Hussain, M Shoaib, SH Mehmood
    • Conference: Eighth International Conference on Digital Information Management (ICDIM)
    • Year: 2013
    • Citations: 6

 

  1. Title: Evaluating top-n recommendations using ranked error approach: An empirical analysis
    • Authors: S Aftab, H Ramampiaro
    • Journal: IEEE Access
    • Volume: 10
    • Pages: 30832-30845
    • Year: 2022
    • Citations: 4

 

  1. Title: Improving top-N recommendations using batch approximation for weighted pair-wise loss
    • Authors: S Aftab, H Ramampiaro
    • Journal: Machine Learning with Applications
    • Volume: 15
    • Pages: 100520
    • Year: 2024

 

  1. Title: Deep Contextual Grid Triplet Network for Context-Aware Recommendation
    • Authors: S Aftab, H Ramampiaro, H Langseth, M Ruocco
    • Journal: IEEE Access
    • Year: 2023

 

  1. Title: Data Mining in Insurance Claims (DMICS)
    • Authors: S Aftab, W Abbass, MM Bilal, T Hussain, M Shoaib, SH Mehmood