Prof. Lotfi Chaari | Artificial Intelligence | Best Researcher Award

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Prof. Lotfi Chaari | Artificial Intelligence | Best Researcher Award šŸ†

Institut National Polytechnique de Toulouse (Toulouse INP),FrancešŸŽ“

Dr. Lotfi Chaari is a distinguished French academic and researcher specializing in signal and image processing, artificial intelligence, and biomedical imaging. Currently a Full Professor at the Institut National Polytechnique de Toulouse (Toulouse INP), he also directs research initiatives at Ipst-Cnam and contributes to groundbreaking projects at the IRIT laboratory. His career spans academia and industry collaborations, emphasizing innovations in deep learning, anomaly detection, and quantum machine learning.

 

Professional ProfileĀ 

Education šŸŽ“:

  • 2017:Ā Habilitation Ć  Diriger la Recherche (HDR), Toulouse INP, France
  • 2010:Ā PhD in Signal and Image Processing, University of Paris-Est Marne-la-VallĆ©e, France
  • 2008:Ā Master of Science in Telecommunication, SUPā€™COM, Tunisia
  • 2007:Ā Telecommunication Engineering Degree, SUPā€™COM, Tunisia

Work Experience šŸ’¼:

  • 2024 – Present:Ā Full Professor, Toulouse INP, France (Ipst-Cnam)
  • 2012 – 2024:Ā Associate Professor, Toulouse INP, France (Ipst-Cnam)
  • 2010 – 2012:Ā Post-doctoral Fellow, INRIA Grenoble-RhĆ“ne Alpes, France

 

Skills šŸ”:

  • Artificial Intelligence & Machine Learning: Proficient in deep learning, anomaly detection, and Bayesian optimization.
  • Signal & Image Processing: Expertise in biomedical imaging, remote sensing, and pattern recognition.
  • Optimization: Skilled in variational and inverse problem-solving techniques for image enhancement and restoration.

Awards and Honors šŸ†:

  • 2023:Ā HOPE Best Workshops Paper Award
  • 2022:Ā Nutrients Best Paper Award
  • 2019: Elevated to IEEE Senior Member status

Memberships šŸ¤:

  • Editorial Positions: Associate Editor forĀ Digital Signal Processing JournalĀ andĀ IEEE Open Journal of Signal Processing
  • Conference Leadership: Founder and General Chair,Ā International Conference on Digital Health Technologies (ICDHT)
  • Technical Program Committee Member: Contributed to renowned conferences like IEEE ICIP, IEEE ICASSP, and ISIVC

Teaching Experience šŸ‘©ā€šŸ«:

Dr. Chaari is a passionate educator who has developed advanced courses in signal processing, machine learning, and artificial intelligence. He actively supervises PhD students and promotes interdisciplinary research.

Research Focus šŸ”¬:

Dr. Chaari’s research spans various cutting-edge fields, including biomedical signal processing, remote sensing, and anomaly detection. He has spearheaded multiple collaborative projects, such as MSrGB (Metabolic Shift in Radioresistance of Glioblastoma) and BayesQML (Bayesian Optimization for Quantum Machine Learning), pushing the boundaries of AI in medical and engineering applications.

ConclusionĀ 

Dr. Lotfi Chaari is an outstanding candidate for the Best Researcher Award. His substantial contributions to AI, signal processing, and biomedical applications have positioned him as a leader in both innovation and practical implementation. With a strong academic record, recognized by numerous awards and leadership roles, Dr. Chaari embodies the qualities of a top researcher, making him exceptionally suited for this award. Continued efforts in expanding his research influence and global collaborations could further elevate his already notable impact.

šŸ“š PublilcationĀ 

  • Title: “mid-DeepLabv3+: A Novel Approach for Image Semantic Segmentation Applied to African Food Dietary Assessments”
    Topic: Semantic segmentation for dietary assessments
    Year: 2023
    Journal: Sensors
    DOI: 10.3390/s24010209
  • Title: “Non-smooth Bayesian learning for artificial neural networks”
    Topic: Bayesian learning in neural networks
    Year: 2022
    Journal: Journal of Ambient Intelligence and Humanized Computing
    DOI: 10.1007/s12652-022-04073-8
  • Title: “Bayesian Optimization Using Hamiltonian Dynamics for Sparse Artificial Neural Networks”
    Topic: Bayesian optimization for sparse neural networks
    Year: 2022
    Conference: 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)
    DOI: 10.1109/isbi52829.2022.9761469
  • Title: “A Convolutional Neural Network for Artifacts Detection in EEG Data”
    Topic: CNN for detecting artifacts in EEG data
    Year: 2022
    Source: Lecture Notes in Networks and Systems
    DOI: 10.1007/978-981-16-7618-5_1
  • Title: “Bayesian Optimization for Sparse Artificial Neural Networks: Application to Change Detection in Remote Sensing”
    Topic: Bayesian optimization for sparse neural networks in remote sensing
    Year: 2022
    Source: Lecture Notes in Networks and Systems
    DOI: 10.1007/978-981-16-7618-5_4
  • Title: “Efficient Bayesian Learning of Sparse Deep Artificial Neural Networks”
    Topic: Bayesian learning in sparse deep neural networks
    Year: 2022
    Source: Lecture Notes in Computer Science
    DOI: 10.1007/978-3-031-01333-1_7
  • Title: “Drowsiness Detection Using Joint EEG-ECG Data With Deep Learning”
    Topic: Drowsiness detection using EEG and ECG data
    Year: 2021
    Conference: 2021 29th European Signal Processing Conference (EUSIPCO)
    DOI: 10.23919/eusipco54536.2021.9616046

 

Dr.Pouya Farshbaf Aghajani | Artificial Intelligence | Best Scholar Award

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Dr.Pouya Farshbaf Aghajani | Artificial Intelligence | Best Scholar AwardĀ  šŸ†

Master of Science atĀ University of Tehran,Ā IranšŸŽ“

Pouya Farshbaf Aghajani is a Food Engineer specializing in food science, sustainable resource extraction, and innovative food safety technologies. He completed his Masterā€™s in Food Engineering from the University of Tehran with the highest GPA in his class and holds a Bachelorā€™s degree in Biosystem Engineering from the University of Tabriz. Pouya has contributed to numerous research publications in food technology and advanced ultrasound applications, emphasizing resource efficiency and quality improvement.

Professional ProfileĀ 

šŸŽ“ Education

  • Master of Science in Food Engineering (Food Science and Chemistry) ā€“ University of Tehran (2020ā€“2023)
    Ranked 1st, GPA: 3.54/4
    Thesis on ultrasound-assisted cultivation of Chlorella vulgaris for sustainable oil extraction.
  • Bachelor of Science in Biosystem Engineering (Food Engineering) ā€“ University of Tabriz (2016ā€“2020)
    Ranked 4th in GPA

šŸ¢ Work Experience

  • Scientific Research Association, University of Tehran ā€“ Teacher, offering training in international publications, software applications, and biomechanics.
  • ISI Journal Reviewer ā€“ Certified reviewer for journals like Food Chemistry, providing expert evaluations.
  • Assistant Editor-in-Chief ā€“ Frontiers in Food, Drug, and Natural Sciences, overseeing technical content.

šŸ§¬ Skills

  • Technical Skills: Proficient in SOLIDWORKS, SPSS, Python, MATLAB, and laboratory tools like GC, HPLC, SEM, and freeze dryers.
  • Soft Skills: Effective in teaching, team collaboration, time management, and problem-solving.

Awards and Honors šŸ†

  • Ranked 1st among masterā€™s students, University of Tehran (2021)
  • National graduate full scholarship, University of Tehran (2020)
  • Ranked in the top 10% among undergraduate students, University of Tabriz (2019)

šŸ“š Teaching Experience

Instructor at the University of Tehranā€™s Scientific Research Association, teaching scientific writing, biomechanics applications, and English (IELTS-focused).

šŸ”¬ Research Focus

Pouyaā€™s research centers on energy conservation, food safety, ultrasound technology, and artificial intelligence applications in food engineering. His work includes sustainable oil extraction, algae research, and quality assessment techniques aimed at improving food safety and processing efficiency.

ConclusionĀ 

Pouya Farshbaf Aghajani is a strong candidate for the Best Scholar Award due to his academic excellence, impactful research, and dedication to advancing sustainable food engineering. With a demonstrated ability to innovate and lead, coupled with a commitment to teaching and mentorship, Pouya exemplifies the qualities of an outstanding scholar. Addressing areas for further growth, such as gaining international experience and expanding funding acquisition skills, would further solidify his scholarly influence. Nonetheless, his current achievements and strengths make him an excellent candidate for this prestigious award

šŸ“š PublilcationĀ 

  • “The Improvement of Freezing Time and Functional Quality of Frozen Mushrooms by Application of Probe-Type Power Ultrasound”
    • Year: 2023
    • Journal: Ultrasonics Sonochemistry
  • “Dual-Stage Ultrasound in Deep Frying of Potato Chips; Effects on the Oil Absorption and the Quality of Fried Chips”
    • Year: 2024
    • Journal: Ultrasonics Sonochemistry
  • “Revolutionizing Mushroom Identification: Improving Efficiency with Ultrasound-Assisted Frozen Sample Analysis and Deep Learning Techniques”
    • Year: 2024
    • Journal: Journal of Agriculture and Food Research
  • “Innovative Modifications to Zarrouk Medium for Enhanced Cultivation of Spirulina (Arthrospira Platensis)”
    • Year: 2024
    • Journal: Available at SSRN

JiaLi Zhu | Artificial Intelligence | Best Researcher Award

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Ms JiaLi Zhu | Artificial Intelligence | Best Researcher Award šŸ†

Research Fellow at University of Naples Federico II , ItalyšŸŽ“

Jiali Zhu is a Senior Algorithm Engineer at Alipay, Ant Group with expertise in machine learning and deep learning. She holds a Masterā€™s degree in Computer Technology from Southeast University, completed in June 2023 . Since July 2023, Jiali has worked as a Machine Learning Algorithm Engineer at Ant Groupā€™s Alipay, focusing on cutting-edge algorithm development .

Professional Profile

EducationšŸŽ“

Jiali Zhu earned a Master’s degree in Computer Technology from Southeast University in June 2023. Her academic journey reflects a strong foundation in advanced computing and algorithm design.

šŸ’¼Work Experience

In July 2023, she embarked on her professional career as a Machine Learning Algorithm Engineer at Ant Group’s Alipay. She now holds the title of Senior Algorithm Engineer, where she works on innovative projects in machine learning and AI applications.

Ā šŸ› ļøSkills

Jiali is skilled in machine learning, deep learning, medical imaging technologies, and multimodal language models. Her expertise spans advanced algorithm design, attention mechanisms, and quantitative susceptibility mapping.

šŸ†Awards and Honors

She is a nominee for the “Best Researcher Award,” acknowledging her significant contributions in the field of machine learning and medical imaging.

Ā Research Focus šŸ”¬

Jialiā€™s research focuses on integrating deep learning with medical imaging. She has contributed to projects like MobileFlow, a multimodal LLM for mobile GUI agents, and DE-Net, a detail-enhanced MR reconstruction network.

 

šŸ“–Publications :Ā 

  • DE-Net: Detail-enhanced MR reconstruction network via global-local dependent attention
    šŸ“… Year: 2024
    šŸ“– Journal: Biomedical Signal Processing and Control
    šŸ§  Authors: J. Zhu, D. Hu, W. Mao, J. Zhu, R. Hu, Y. Chen
  • MobileFlow: A Multimodal LLM For Mobile GUI Agent
    šŸ“… Year: 2024
    šŸ“– Journal: arXiv preprint (arXiv:2407.04346)
    šŸ§  Authors: S. Nong, J. Zhu, R. Wu, J. Jin, S. Shan, X. Huang, W. Xu
  • Edge prior guided dictionary learning for quantitative susceptibility mapping reconstruction
    šŸ“… Year: 2022
    šŸ“– Journal: Quantitative Imaging in Medicine and Surgery
    šŸ§  Authors: J. Du, Y. Ji, J. Zhu, X. Mai, J. Zou, Y. Chen, N. Gu

 

Obsa Gilo Wakuma | Artificial Intelligence | Best Researcher Award

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Dr Obsa Gilo Wakuma Ā | Artificial Intelligence | Best Researcher AwardĀ 

Ā Ass. Prof at Wallaga University, Ethiopia

Dr. Obsa Gilo Wakuma is a dedicated researcher and academician with a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology Patna, where his thesis focused on “Deep Learning Approaches for Efficient Domain Adaptation.” He holds an M.Sc. in Computer Science (CGPA: 3.78) and a B.Sc. in Computer Science (CGPA: 3.56) from Wallaga University, Ethiopia.Dr. Obsa Gilo Wakuma continues to contribute to the academic and research community with his expertise in deep learning and domain adaptation, leveraging his strong background in computer science and engineering to drive innovative solutions.

šŸŽ“ Education:

  • Ph.D. in Computer Science and Engineering, IIT Patna (2024)
  • M.Sc. in Computer Science, Wallaga University (2018)
  • B.Sc. in Computer Science, Wallaga University (2014)
  • XII Class, Sibu Sire Preparatory School (2010)
  • X Class, Sibu Sire High School (2008)

šŸ’¼ Work Experience:

Dr. Wakuma began his professional journey as a Recorder at Wallaga University’s main Registrar in Oromia, Ethiopia, from October 2014 to June 2015. He then served as a Laboratory Technician at Wallaga University’s Shambu campus until February 2016. From February 2016 to September 2018, he worked as a Graduate Assistant (GA-II) at Wallaga University, eventually becoming a Lecturer from February 2019 to September 2019. From September 2019 to December 2023, he was a Research Scholar at IIT Patna.

šŸ“š Research Focus:

Dr. Wakuma’s research primarily revolves around deep learning and domain adaptation. His notable publications include articles in prestigious journals such as Expert Systems with Applications, Pattern Analysis and Applications, IEEE Access, and the Journal of Visual Communication and Image Representation. His work often explores robust unsupervised deep sub-domain adaptation and optimal transport for image classification.

šŸ› ļø Skills:

Dr. Wakuma possesses strong competencies in multiple languages, including English, Afaan Oromoo, and Amharic. His technical skills encompass programming languages such as Java, PHP, Python, C, C++, and R. He is proficient in databases like MySQL, PostgreSQL, HSQL, and SQLite, and has experience in web development using HTML, CSS, JavaScript, and Apache Web Server. Additionally, he is skilled in academic research, teaching, training, consultation, and community service.

Research and Publications

  1. Journal Articles: Published in prestigious journals such as “Expert Systems with Applications,” “Pattern Analysis and Applications,” “IEEE Access,” and “Journal of Visual Communication and Image Representation.” Topics covered include domain adaptation in sensor data, subdomain adaptation via correlation alignment, robust unsupervised deep sub-domain adaptation, and unsupervised sub-domain adaptation using optimal transport.
  2. Conference Proceedings: Presented at the IEEE 19th India Council International Conference (INDICON), discussing the integration of discriminate features and similarity preserving for unsupervised domain adaptation.

Conclusion

Given his strong academic background, extensive research publications, practical skills, and teaching experience, Obsa Gilo Wakuma is a highly suitable candidate for the Best Researcher Award. His contributions to the field of computer science, particularly in deep learning and domain adaptation, demonstrate a high level of expertise and impact, making him deserving of such recognition.

šŸ“œ Publications:

  • Unsupervised sub-domain adaptation using optimal transport
    O. Gilo, J. Mathew, S. Mondal, R.K. Sanodiya
    Journal of Visual Communication and Image Representation (2023)
    šŸ–¼ļøšŸ”„šŸšš
  • Subdomain adaptation via correlation alignment with entropy minimization for unsupervised domain adaptation
    O. Gilo, J. Mathew, S. Mondal, R.K. Sanodiya
    Pattern Analysis and Applications (2024)
    šŸ“ŠšŸ”„šŸŒ
  • Integration of Discriminate Features and Similarity Preserving for Unsupervised Domain Adaptation
    O. Gilo, J. Mathew, S. Mondal
    2022 IEEE 19th India Council International Conference (INDICON) (2022)
    šŸ“ššŸ”šŸ¤
  • Kernelized Bures metric: A framework for effective domain adaptation in sensor data analysis
    O. Gilo, J. Mathew, S. Mondal
    Expert Systems with Applications (2024)
    šŸ“ˆšŸ”„šŸ”¬
  • RDAOT: Robust Unsupervised Deep Sub-domain Adaptation through Optimal Transport for Image Classification
    O. Gilo, J. Mathew, S. Mondal, R.K. Sanodiya
    IEEE Access (2023)
    šŸ–¼ļøšŸ”„šŸ§ 
  • Information Extraction For Afaan Oromo News Texts Using Hybrid Approach
    O. Gilo
    Journal of Innovation in Computer Science and Engineering (2019)
    šŸ“°šŸ”šŸ‡ŖšŸ‡¹
  • Unified Domain Adaptation with Discriminative Features and Similarity Preservation
    O. Gilo, J. Mathew, S. Mondal
    (Journal/Conference not specified)
    šŸ”„šŸŒšŸ¤

Nafis Uddin Khan | Artificial Intelligence | Best Researcher Award

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Dr Nafis Uddin Khan | Artificial Intelligence | Best Researcher AwardĀ 

Associate Professor at Ā SR University Warangal India

Dr. Nafis Uddin Khan is an esteemed academic and researcher specializing in Information and Communication Technology. With a Ph.D. from the Atal Bihari Vajpayee – Indian Institute of Information Technology & Management, Gwalior, he has a profound expertise in computer vision, image processing, and fuzzy logic applications in signal and image processing. He currently serves as an Associate Professor at SR University Warangal.

Education šŸ“š

  • Ph.D. in Information and Communication Technology from Atal Bihari Vajpayee – Indian Institute of Information Technology & Management, Gwalior, India (2013).
  • M.Tech in Software Systems from Samrat Ashok Technological Institute, Vidisha, under Rajiv Gandhi Prodyogiki Vishwavidyalaya, Bhopal, India (2008).
  • B.E. in Electronics & Telecommunication Engineering from Jawaharlal Darda Institute of Engineering & Technology, Yavatmal, under Amravati University, Amravati, India (2003).
  • H.S.S.C. from Tiny Tots E. M. H. S. School, Seoni, M.P. Board, India (1997).
  • H.S.C. from Gyan Jyoti E. M. H. S. School, Nainpur, M.P. Board, India (1995).

Work Experience šŸ’¼

  1. Associate Professor, School of CS & AI, SR University Warangal, Telangana, India (since August 2023).
  2. Assistant Professor (Senior Grade), Jaypee University of Information Technology, Solan, Himachal Pradesh, India (2017-2023).
  3. Assistant Professor (Senior Grade), Jaypee University of Engineering and Technology, Raghogarh, Madhya Pradesh, India (2013-2017).
  4. Lecturer, Anand Engineering College, Agra, Uttar Pradesh, India (2008-2009).
  5. Lecturer, Hitkarini College of Engineering and Technology, Jabalpur, Madhya Pradesh, India (2004-2005).

Skills & Certifications šŸ’”

  • Programming: Matlab, C, C++, Python.
  • Technical Writing
  • Team Work and Leadership

Administrative Roles šŸ¢

  • Associate Dean ā€“ Admissions, SR University, Warangal (since January 2024).
  • Training and Placement – Faculty Coordinator, Jaypee University of Information Technology, Solan (2017-2023).
  • Coordinator of Student Activities and Placement Section in Internal Quality Assurance Cell (IQAC), Jaypee University of Information Technology, Solan (2017-2023).

Research Focus šŸ”¬

  • Statistical Image Processing
  • Medical Image Processing
  • Fuzzy Logic based Applications in Signal and Image Processing
  • Soft Optimization Techniques in Signal and Image Processing

Professional Contributions šŸ“ˆ

  • Enhanced sharp edge features and reduced Gaussian noise using singular value decomposition on optimal anisotropic diffused images.
  • Developed a fuzzy-based diffusion coefficient function for selective smoothing of impulsive noise.
  • Explored soft computing-based optimization techniques for speckle reduction in medical ultrasound and X-ray images.

Workshops and Conferences šŸ—“ļø

  • Coordinated multiple workshops and short-term programs on AI, signal processing, and leadership in education.
  • Served as an Invited Session Chair and Organizing Committee Member in various international conferences, including the IEEE International Conference on Signal Processing, Computing and Control.

Memberships šŸ¤

  • Active participation in academic and professional organizations through organizing and coordinating roles in numerous conferences and workshops.

 

Publications šŸ“š

  1. Fuzzy C-Means Clustering Based Selective Edge Enhancement Scheme for Improved Road Crack Detection šŸ›¤ļø
    • Authors: Bhardwaj, M., Khan, N.U., Baghel, V.
    • Journal: Engineering Applications of Artificial Intelligence
    • Year: 2024
  2. Fuzzy Based Self-Similarity Weight Estimation in Non-Local Means for Gray-Scale Image De-Noising šŸ–¤
    • Authors: Thakur, N., Khan, N.U., Sharma, S.D.
    • Journal: Digital Signal Processing: A Review Journal
    • Year: 2024
  3. Road Crack Detection Using Pixel Classification and Intensity-Based Distinctive Fuzzy C-Means Clustering šŸ›¤ļø
    • Authors: Bhardwaj, M., Khan, N.U., Baghel, V.
    • Journal: Visual Computer
    • Year: 2024
  4. A Comparative Survey on Histogram Equalization Techniques for Image Contrast Enhancement šŸ“Š
    • Authors: Malik, A., Khan, N.U.
    • Journal: Lecture Notes in Electrical Engineering
    • Year: 2024
  5. A Two Phase Ultrasound Image De-Speckling Framework by Nonlocal Means on Anisotropic Diffused Image Data šŸ©ŗ
    • Authors: Thakur, N., Khan, N.U., Sharma, S.D.
    • Journal: Informatica (Slovenia)
    • Year: 2023
  6. An Efficient Fuzzy Inference System Based Approximated Anisotropic Diffusion for Image De-Noising šŸ–„ļø
    • Authors: Thakur, N., Khan, N.U., Sharma, S.D.
    • Journal: Cluster Computing
    • Year: 2022
  7. Digital Image Enhancement and Reconstruction šŸ“˜
    • Authors: Rajput, S.S., Khan, N.U., Singh, A.K., Arya, K.V.
    • Journal: Digital Image Enhancement and Reconstruction
    • Year: 2022
  8. Brain Tumor Image Segmentation Using K-Means and Fuzzy C-Means Clustering šŸ§ 
    • Authors: Bhardwaj, M., Khan, N.U., Baghel, V., Vishwakarma, S.K., Bashar, A.
    • Journal: Digital Image Enhancement and Reconstruction
    • Year: 2022
  9. Improved Road Crack Detection Using Histogram Equalization Based Fuzzy-C Means Technique šŸ›¤ļø
    • Authors: Bhardwaj, M., Khan, N.U., Baghel, V.
    • Conference: PDGC 2022 – 7th International Conference on Parallel, Distributed and Grid Computing
    • Year: 2022
  10. Cuckoo Search Optimized Histogram Equalization for Low Contrast Image Enhancement šŸ¦
    • Authors: Thakur, N., Khan, N.U., Sharma, S.D.
    • Conference: PDGC 2022 – 7th International Conference on Parallel, Distributed and Grid Computing
    • Year: 2022

 

 

Arti Jha | Artificial Intelligence | Best Researcher Award

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Ms Arti Jha |Ā Ā Artificial Intelligence |Ā Ā Best Researcher AwardĀ 

 

Senior Research Fellow atĀ Birla Institute of Technology and Science, Pilani,Ā India

 

šŸ“š šŸ‘©ā€šŸ’» Arti Jha is a Senior Research Fellow at BITS Pilani, specializing in machine learning, natural language processing, statistics, game theory, and deep learning. Currently pursuing a PhD in Web Intelligence and Social Computing, she focuses on AI-enabled design of optimal advertisement campaign strategies in collaboration with CommerceIQ, Bangalore. With industry experience at CommerceIQ, she develops predictive models for e-commerce platforms. Arti holds a BTech-MTech dual degree from the Centre for Converging Technologies, University of Rajasthan. Her research spans object detection, machine learning, and teaching roles as a TA at BITS Pilani.

Professional Profile:

 

Education šŸŽ“

PhD Candidate in Web Intelligence and Social Computing, BITS Pilani, Pilani, India, Feb 2022 – Present.

BTech-MTech Dual Degree, Centre for Converging Technologies, University of Rajasthan, Aug 2015 – Jul 2020. Cumulative GPA: 3.8/4.00.

Research Focus šŸ”¬

Arti Jha’s research focuses on several key areas in the realm of artificial intelligence and data science. She specializes in machine learning šŸ¤–, natural language processing šŸ“œ, statistics šŸ“Š, game theory šŸŽ², and deep learning šŸ§ . Her work spans from optimizing e-commerce advertising campaigns using advanced machine learning techniques to developing reinforcement learning strategies for real-time bidding in digital marketing. With a strong foundation in both theoretical research and practical applications, Arti contributes actively to the fields of AI-enabled advertisement strategies, predictive modeling, and algorithmic optimizations aimed at enhancing business intelligence and decision-making processes in digital platforms.

Professional Experience šŸ’¼

  • Senior Research Fellow, BITS-CommerceIQ Collaboration Project, BITS Pilani, Pilani, India, Feb 2022 – Present.
  • Designing optimal and targeted ad campaign strategies on e-commerce platforms.
  • Developing prediction models for optimizing ad campaigns on Amazon.
  • Working on interpretable and explainable AI models.
  • Industry Experience at CommerceIQ, Bangalore, India.

Research Experience šŸ“Š

  • Research Scholar, BITS Pilani, Pilani, India, Feb 2022 – Present.
  • Building algorithmic campaign optimizers.
  • Implementing multi-stage campaign classification and clustering models.
  • Designing explainable models for risk-averse modeling.
  • Project Trainee, Indian Space Research Organisation (ISRO), RRSC Jodhpur, India, Aug 2019 – Apr 2020.
  • Thesis on Object Detection using Satellite Images.
  • Data Analysis Intern, Robotics And Machine Analytics Lab (RAMAN), MNIT Jaipur, India, Mar 2019 – May 2019.
  • Developed a Movie Recommendation System.

Academic Experience šŸ“š

  • Teaching Assistant, BITS Pilani, Pilani, India.
  • C Programming (Feb 2022 – Dec 2023).
  • Data Warehousing (Jan 2024 – Present).

Publications:Ā 

 

SUSHIL KUMAR | Artificial Intelligence | Outstanding Scientist Award

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Assist Prof Dr SUSHIL KUMAR | Artificial Intelligence | Outstanding Scientist AwardĀ Ā 

Assistant Professor at Ā NIT Kurukshetra,India

Dr. Sushil Kumar, Ph.D., is a renowned scientist and academician with a distinguished career in biotechnology and molecular biology šŸ§¬. He earned his Ph.D. from a prestigious institution and has over 20 years of experience in research and teaching šŸ“š. Dr. Kumar has published numerous research papers in reputed journals and has been honored with several awards for his contributions to science šŸ…. He is currently a professor at a leading university, mentoring students and advancing research in genetic engineering and sustainable agriculture šŸŒ±. Dr. Kumar is also an active member of various scientific communities and editorial boards šŸ›ļø.

 

Professional Profile:

Education

Dr. Sushil Kumar’s educational journey is marked by excellence in computer science and engineering šŸŽ“. He earned his Ph.D. from the Indian Institute of Technology Roorkee (2009-2014), focusing on “Metaheuristics: Applications for Image Segmentation and Image Enhancement” šŸ“ø. He completed his M.Tech. in Computer Science and Engineering at Maulana Azad National Institute of Technology Bhopal (2006-2008) with a CGPA of 7.91 šŸ“Š. Dr. Kumar received his B.Tech. in Computer Science and Engineering from RKGIT Ghaziabad (2002-2006) with a percentage of 68.98 šŸ’». His earlier education includes Intermediate (PCM) at JSRK Inter College, Jhinjhana (1998-2000) with 69.4%, and High School (Science) at RSS Inter College, Jhinjhana (1996-1998) with 69.8% šŸ“š

 

Teaching Experience:

Dr. Sushil Kumar has extensive teaching experience in computer engineering šŸ–„ļø. Since November 22, 2022, he has been an Assistant Professor (Gr-I) at the Department of Computer Engineering, NIT Kurukshetra šŸ«. Prior to this, he served as an Assistant Professor (Gr-I) at NIT Warangal from April 9, 2018, to November 21, 2022 šŸ“š. From January 5, 2015, to January 30, 2018, he was an Assistant Professor at Amity University, Noida šŸ¢. He also taught at Lovely Professional University, Jalandhar, from August 18, 2014, to December 15, 2014 šŸŒŸ, and earlier at Amity University from September 23, 2008, to December 30, 2009 šŸ‘Øā€šŸ«.

Achievements:

Dr. Sushil Kumar has a commendable list of achievements and awards šŸŒŸ. He qualified GATE-2006 in Computer Science and Engineering šŸŽ“. He received an MHRD Fellowship of ā‚¹5000/month for his M.Tech. (2006-2008) and fellowships of ā‚¹18000/month (2009-2011) as JRF and ā‚¹20000/month (2011-2014) as SRF during his Ph.D. at IIT Roorkee šŸ…. He was funded by CSIR for attending an international conference in Poland (2012-2013) āœˆļø. During his high school years, he secured distinctions in Mathematics, Science, and Technical Drawing (1996-1998) and in Physics in Intermediate (1998-2000) šŸ†.

Research focus :

Dr. Sushil Kumar’s research focuses on advanced topics in computer science, particularly in the areas of image processing and optimization šŸ“øšŸ”. His Ph.D. work on “Metaheuristics: Applications for Image Segmentation and Image Enhancement” underscores his expertise in developing algorithms to improve image quality and analysis šŸ§ . Additionally, he explores metaheuristic approaches for solving complex optimization problems, enhancing computational efficiency and accuracy šŸ–„ļø. His research also extends to genetic engineering and sustainable agriculture, where he applies computational methods to address challenges in these fields šŸŒ±šŸŒ¾. Dr. Kumar’s interdisciplinary approach combines computer science with practical applications in various domains šŸ“š.
Publications:Ā 
  • An evolutionary Chameleon Swarm Algorithm based network for 3D medical image segmentation by Rajesh, C., Sadam, R., Kumar, S. – Expert Systems with Applications, 2024 – šŸ“ 1 citation
  • Machine Learning for Cloud-Based DDoS Attack Detection: A Comprehensive Algorithmic Evaluation by Naithani, A., Singh, S.N., Kant Singh, K., Kumar, S. – Confluence 2024, 2024 – šŸ“ 0 citations
  • An evolutionary U-shaped network for Retinal Vessel Segmentation using Binary Teachingā€“Learning-Based Optimization by Rajesh, C., Sadam, R., Kumar, S. – Biomedical Signal Processing and Control, 2023 – šŸ“ 7 citations
  • Automatic Retinal Vessel Segmentation Using BTLBO by Rajesh, C., Kumar, S. – Lecture Notes in Networks and Systems, 2023 – šŸ“ 1 citation
  • Improved CNN Model for Breast Cancer Classification by Satya Shekar Varma, P., Kumar, S. – Lecture Notes in Networks and Systems, 2023 – šŸ“ 0 citations
  • An evolutionary block based network for medical image denoising using Differential Evolution by Rajesh, C., Kumar, S. – Applied Soft Computing, 2022 – šŸ“ 20 citations
  • Machine learning based breast cancer visualization and classification by Shekar Varma, P.S., Kumar, S., Sri Vasuki Reddy, K. – ICITIIT 2021, 2021 – šŸ“ 2 citations
  • An intelligent lung tumor diagnosis system using whale optimization algorithm and support vector machine by Vijh, S., Gaur, D., Kumar, S. – International Journal of System Assurance Engineering and Management, 2020 – šŸ“ 34 citations
  • Diet recommendation for hypertension patient on basis of nutrient using AHP and entropy by Vijh, S., Gaur, D., Kumar, S. – Confluence 2020, 2020 – šŸ“ 2 citations
  • Brain tumor segmentation using DE embedded OTSU method and neural network by Sharma, A., Kumar, S., Singh, S.N. – Multidimensional Systems and Signal Processing, 2019 – šŸ“ 29 citations

 

Pritom Jyoti Goutom | Artificial Intelligence | Best Researcher Award

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Mr Pritom Jyoti Goutom | Artificial Intelligence | Best Researcher Award

 

Research Scholar and Project Associate I at Dibrugarh University ,India

Profile:

ScopusĀ 

Education:

Pritom Jyoti Goutom is affiliated with the Centre for Computer Science and Applications at Dibrugarh University in Assam, India šŸ‡®šŸ‡³. His research focuses on natural language processing (NLP), particularly related to the Assamese language šŸ—£ļø.

Some of his notable contributions include:

  1. Text Summarization šŸ“„: He has co-authored papers on text summarization techniques using deep learning, such as “An Abstractive Text Summarization Using Deep Learning in Assamese” and “Text Summarization in Assamese Language Using Sequence to Sequence RNNs”怐5ā€‹ (ORCID)ā€‹ā€‹ (Dibrugarh University)ā€‹2. Collaboration with Dr. Nomi Baruah šŸ¤: He often works with Dr. Baruah and others on projects aimed at improving NLP for low-resource languages.

For more details about his educational background and academic contributions, you can check his profile on academic platforms like ORCID怐5ā€‹ (ORCID)

Professional Experience:

šŸŽ“ Research Scholar at Dibrugarh University
Specializing in Natural Language Processing (NLP) and AI-generated text in Assamese.
šŸ” Research Focus: Text summarization, part-of-speech tagging, and fake news detection.

šŸ‘Øā€šŸ’» Project Associate I, Dept. of Computer Science and Engineering
Contributing to cutting-edge projects and innovations in AI and NLP.

Research Ā FocusĀ  Ā :

  • Text Summarization: Developing algorithms for concise representation of Assamese text.
  • Machine Translation: Enhancing language conversion models for Assamese.
  • Sentiment Analysis: Analyzing opinions and emotions expressed in Assamese text.
  • Named Entity Recognition (NER): Identifying and categorizing entities in Assamese text.
  • Fake News Detection: Implementing models to identify misinformation in Assamese news sources.
  • Language Modeling: Building computational models to understand and generate Assamese text.

 

Contributions :

  • Co-authored research on abstractive text summarization using deep learning approaches, focusing on the nuances of the Assamese language.
  • Investigated LSTM and BiLSTM algorithms for fake news detection, enhancing accuracy and reliability in Assamese news sources.
  • Developed attention-based transformer models for text summarization in Assamese, improving content extraction and generation.
  • Worked on automatic spelling error identification using deep learning algorithms tailored for Assamese language nuances.

Citations:

Total Citations: šŸ“ˆ 13

Total Documents:Ā  šŸ“‚3

h-index: šŸŒŸ 1

Publication Top Notes:

  • Goutom, P. J., Baruah, N., & Sonowal, P. (2023). An abstractive text summarization using deep learning in Assamese. International Journal of Information Technology, 15(5), 2365-2372. (6 citations)

 

  • Phukan, R., Goutom, P. J., & Baruah, N. (2024). Assamese Fake News Detection: A Comprehensive Exploration of LSTM and Bi-LSTM Techniques. Procedia Computer Science, 235, 2167-2177.

 

  • Goutom, P. J., Baruah, N., & Sonowal, P. (2024). Attention-based Transformer for Assamese Abstractive Text Summarization. Procedia Computer Science, 235, 1097-1104.

 

  • Phukan, R., Neog, M., Goutom, P. J., & Baruah, N. (2024). Automated Spelling Error Detection in Assamese Texts using Deep Learning Approaches. Procedia Computer Science, 235, 1684-1694.

 

  • Goutom, P. J., & Baruah, N. (2023). Text summarization in Assamese language using sequence to sequence RNNs. Indian Journal of Science and Technology, 16(SP2), 22-29.