Person Image

    Education

    • Ph. D. (Computer Science), University of California, USA, 2555
    • วศ. ม. .(วิศวกรรมคอมพิวเตอร์), มหาวิทยาลัยเกษตรศาสตร์, ไทย, 2546
    • วศ. บ..(วิศวกรรมคอมพิวเตอร์), มหาวิทยาลัยเกษตรศาสตร์, ไทย, 2543

    Expertise Cloud

    Artificial intelligenceassociative classificationAuthorship attributionauthorship identificationAutomatic feature extractionBiomedical signal processingChanging environmentchanging environmentsClassificationClassification (of information)Co-Authorship graphconcept driftConcept driftsConvolutional neural networkCorrosion PredictionData acquisitionData communication systemsData ProcessingData streamdata streams classificationDecision MakingDecision treesDeep LearningDimensionality reductionDynamic rule updatingDynamic Time WarpingElectrocardiographyFeature extractionForestryFully connected neural networkhigh dimensional data streamsIncremental associative classificationIncremental data databasesK fold cross validationsLearning systemsLong short-term memoryMulti-author documentsmulti-label classificationmultiple class-association rulesmultiple class-sssociation rulesObstructive sleep apneaObstructive sleep apnea (OSA) severity detectionoff-line mode clusteringOffshore Corrosion PredictionOrder differencePattern RecognitionQuery processingRapid annotationReal time systemsRepresentationsScalable Algorithmsscientometricssemi-supervised learningSet similarity searchShapeletsSimilarity searchSingle channel ECGSleep qualitySleep researchstream clusteringStudentsStylometrysubspace data-dependent ballsSudden cardiac deaths (SCD)Syntacticssyn-thetic minority over-samplingTask analysisTechnical writingTemplate matchingTemporal information extractiontext classificationTextureThai authorshipThai fingerspellingThai studentsThai teenagerThai TeenagersTime SeriesTime series analysisTime Series MiningTime Series ShapeletsTop-of-lien corrosionTrees (mathematics)Uncontrollable factorsUnivariate time seriesWater condensationWriteprintWrite-printการทำนายโครงสร้างของโปรตีน, เดต้าไมน์นิ่การทำนายหน้าที่การทำงานของโปรตีนการวิเคราะห์โปรตีนการสืบค้นโปรตีนขนาดเล็กข้อมูลเชิงเวลาชีวสารสนเทศฐานข้อมูลชีวสารสนเทศด้านโครงสร้างและฟังกแบบกึ่งผู้สอนโปรตีนลำดับกรดอะมิโนอุตสาหกรรมอาหารและยา

    Interest

    Data Mining, Time Series Mining, Machine Learning, Scalable Algorithms

    Administrative Profile

    • มิ.ย. 2565 - ปัจจุบัน รองหัวหน้าภาควิชา คณะวิศวกรรมศาสตร์ ภาควิชาวิศวกรรมคอมพิวเตอร์
    • ธ.ค. 2565 - ธ.ค. 2567 ผู้ช่วยคณบดีฝ่ายวิชาการ คณะวิศวกรรมศาสตร์

    Resource


    งานวิจัยในรอบ 5 ปี

    Project

    งานวิจัยที่อยู่ระหว่างการดำเนินการ
    • ทุนใน 0 โครงการ
    • ทุนนอก 0 โครงการ
    งานวิจัยที่เสร็จสิ้นแล้ว
    • ทุนใน 1 โครงการ (ผู้ร่วมวิจัย 1 โครงการ)
    • ทุนนอก 4 โครงการ (หัวหน้าโครงการ 3 โครงการ, ผู้ร่วมวิจัย 1 โครงการ)

    แนวโน้มผลงานทั้งหมดเทียบกับแนวโน้มผลงานในรอบ 5 ปี

    Output

    • บทความ 44 เรื่อง (ตีพิมพ์ในวารสารวิชาการ 23 เรื่อง, นำเสนอในการประชุม/สัมมนา 21 เรื่อง)
    • ทรัพย์สินทางปัญญา 1 เรื่อง (ลิขสิทธิ์ 0 เรื่อง, เครื่องหมายการค้า 0 เรื่อง, อนุสิทธิบัตร 0 เรื่อง, สิทธิบัตร 1 เรื่อง)
    • สิ่งประดิษฐ์ 0 เรื่อง (ขึ้นทะเบียนพันธุ์พืช หรือพันธุ์สัตว์ หรือสิ่งประดิษฐ์ มก. 0 เรื่อง)
    • Unknown 0 เรื่อง (Unknown 0 เรื่อง)

    แนวโน้มการนำผลงานไปใช้ประโยชน์ในด้านต่างๆ

    Outcome

    • การนำผลงานไปใช้ประโยชน์ 0 เรื่อง (เชิงวิชาการ 0 เรื่อง, เชิงนโยบาย/บริหาร 0 เรื่อง, เชิงสาธารณะ 0 เรื่อง, เชิงพาณิชย์ 0 เรื่อง)

    รางวัลที่ได้รับ

    Award

    • รางวัลที่ได้รับ 0 เรื่อง (ประกาศเกียรติคุณ/รางวัลนักวิจัย 0 เรื่อง, รางวัลผลงานวิจัย/สิ่งประดิษฐ์ 0 เรื่อง, รางวัลผลงานนำเสนอในการประชุมวิชาการ 0 เรื่อง)

    นักวิจัยที่มีผลงานงานร่วมกันมากที่สุด 10 คนแรก

    Person Relation

    Show All (97)

    Scopus h-index

    #Document titleAuthorsYearSourceCited by
    1Searching and mining trillions of time series subsequences under dynamic time warpingRakthanmanon T., Campana B., Mueen A., Batista G., Westover B., Zhu Q., Zakaria J., Keogh E.2012Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,
    pp. 262-270
    902
    2Fast shapelets: A scalable algorithm for discovering time series shapeletsRakthanmanon T., Keogh E.2013Proceedings of the 2013 SIAM International Conference on Data Mining, SDM 2013,
    pp. 668-676
    378
    3Addressing big data time series: Mining trillions of time series subsequences under dynamic time warpingRakthanmanon T., Campana B., Mueen A., Batista G., Westover B., Zhu Q., Zakaria J., Keogh E.2013ACM Transactions on Knowledge Discovery from Data,
    7(3), 10
    206
    4Beyond one billion time series: Indexing and mining very large time series collections with iSAX2+Camerra A., Shieh J., Palpanas T., Rakthanmanon T., Keogh E.2014Knowledge and Information Systems,
    39(1), pp. 123-151
    97
    5Time series epenthesis: Clustering time series streams requires ignoring some dataRakthanmanon T., Keogh E., Lonardi S., Evans S.2011Proceedings - IEEE International Conference on Data Mining, ICDM,
    pp. 547-556, 6137259
    92
    6E-stream: Evolution-based technique for stream clusteringUdommanetanakit K., Rakthanmanon T., Waiyamai K.2007Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
    4632 LNAI, pp. 605-615
    82
    7Single Channel ECG for Obstructive Sleep Apnea Severity Detection Using a Deep Learning ApproachBanluesombatkul N., Rakthanmanon T., Rakthanmanon T., Wilaiprasitporn T.2019IEEE Region 10 Annual International Conference, Proceedings/TENCON,
    2018-October, pp. 2011-2016, 8650429
    53
    8MDL-based time series clusteringRakthanmanon T., Keogh E., Lonardi S., Evans S.2012Knowledge and Information Systems,
    33(2), pp. 371-399
    51
    9Discovering the intrinsic cardinality and dimensionality of time series using MDLHu B., Rakthanmanon T., Hao Y., Evans S., Lonardi S., Keogh E.2011Proceedings - IEEE International Conference on Data Mining, ICDM,
    pp. 1086-1091, 6137319
    44
    10A general framework for never-ending learning from time series streamsChen Y., Hao Y., Rakthanmanon T., Zakaria J., Hu B., Keogh E.2015Data Mining and Knowledge Discovery,
    29(6), pp. 1622-1664
    40
    11A novel approximation to dynamic time warping allows anytime clustering of massive time series datasetsZhu Q., Batista G., Rakthanmanon T., Keogh E.2012Proceedings of the 12th SIAM International Conference on Data Mining, SDM 2012,
    pp. 999-1010
    36
    12A fast LSH-based similarity search method for multivariate time seriesYu C., Luo L., Chan L.L.H., Rakthanmanon T., Rakthanmanon T., Nutanong S.2019Information Sciences,
    476, pp. 337-356
    32
    13Rapid annotation of interictal epileptiform discharges via template matching under Dynamic Time WarpingJing J., Dauwels J., Rakthanmanon T., Keogh E., Cash S., Westover M.2016Journal of Neuroscience Methods,
    274, pp. 179-190
    28
    14Efficient proper length time series motif discoveryYingchareonthawornchai S., Sivaraks H., Rakthanmanon T., Ratanamahatana C.2013Proceedings - IEEE International Conference on Data Mining, ICDM,
    pp. 1265-1270, 6729632
    26
    15Towards never-ending learning from time series streamsHao Y., Chen Y., Zakaria J., Hu B., Rakthanmanon T., Keogh E.2013Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,
    Part F128815, pp. 874-882, 2487634
    25
    16A scalable framework for cross-lingual authorship identificationSarwar R., Li Q., Rakthanmanon T., Rakthanmanon T., Nutanong S.2018Information Sciences,
    465, pp. 323-339
    22
    17CAG : Stylometric Authorship Attribution of Multi-Author Documents Using a Co-Authorship GraphSarwar R., Urailertprasert N., Vannaboot N., Yu C., Rakthanmanon T., Chuangsuwanich E., Nutanong S.2020IEEE Access,
    8, pp. 18374-18393, 8962080
    21
    18Towards a minimum description length based stopping criterion for semi-supervised time series classificationBegum N., Hu B., Rakthanmanon T., Keogh E.2013Proceedings of the 2013 IEEE 14th International Conference on Information Reuse and Integration, IEEE IRI 2013,
    pp. 333-340, 6642490
    21
    19Data mining a trillion time series subsequences under dynamic time warpingRakthanmanon T., Campana B., Mueen A., Batista G., Westover B., Zhu Q., Zakaria J., Keogh E.2013IJCAI International Joint Conference on Artificial Intelligence,
    pp. 3047-3051
    20
    20Native Language Identification of Fluent and Advanced Non-Native WritersSarwar R., Rutherford A.T., Hassan S.U., Rakthanmanon T., Nutanong S.2020ACM Transactions on Asian and Low-Resource Language Information Processing,
    19(4), 55
    17
    21An effective and scalable framework for authorship attribution query processingSarwar R., Yu C., Tungare N., Tungare N., Chitavisutthivong K., Sriratanawilai S., Xu Y., Chow D., Rakthanmanon T., Rakthanmanon T., Nutanong S.2018IEEE Access,
    6, pp. 50030-50048, 8457490
    16
    22StyloThai: A scalable framework for stylometric authorship identification of Thai documentsSarwar R., Porthaveepong T., Rutherford A., Rakthanmanon T., Rakthanmanon T., Nutanong S.2020ACM Transactions on Asian and Low-Resource Language Information Processing,
    19(3), A36
    15
    23A scalable framework for stylometric analysis of multi-author documentsSarwar R., Yu C., Nutanong S., Urailertprasert N., Vannaboot N., Rakthanmanon T., Rakthanmanon T.2018Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
    10827 LNCS, pp. 813-829
    15
    24A minimum description length technique for semi-supervised time series classificationBegum N., Hu B., Rakthanmanon T., Keogh E.2014Advances in Intelligent Systems and Computing,
    263, pp. 171-192
    14
    25Using the minimum description length to discover the intrinsic cardinality and dimensionality of time seriesHu B., Rakthanmanon T., Hao Y., Evans S., Lonardi S., Keogh E.2015Data Mining and Knowledge Discovery,
    29(2), pp. 358-399
    14
    26Image mining of historical manuscripts to establish provenanceHu B., Rakthanmanon T., Campana B., Mueen A., Keogh E.2012Proceedings of the 12th SIAM International Conference on Data Mining, SDM 2012,
    pp. 804-815
    8
    27Mining historical documents for near-duplicate figuresRakthanmanon T., Zhu Q., Keogh E.2011Proceedings - IEEE International Conference on Data Mining, ICDM,
    pp. 557-566, 6137260
    8
    28Object-oriented database mining: use of object oriented concepts for improving data classification techniqueWaiyamai K., Songsiri C., Rakthanmanon T.2004Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
    3036, pp. 303-309
    7
    29Establishing the provenance of historical manuscripts with a novel distance measureHu B., Rakthanmanon T., Campana B.J.L., Mueen A., Keogh E.2015Pattern Analysis and Applications,
    18(2), pp. 313-331
    7
    30SE-Stream: Dimension projection for evolution-based clustering of high dimensional data streamsChairukwattana R., Kangkachit T., Rakthanmanon T., Waiyamai K.2014Advances in Intelligent Systems and Computing,
    245, pp. 365-376
    6
    31SED-Stream: Discriminative dimension selection for evolution-based clustering of high dimensional data streamsWaiyamai K., Kangkachit T., Rakthanmanon T., Chairukwattana R.2014International Journal of Intelligent Systems Technologies and Applications,
    13(3), pp. 187-201
    6
    32Top-of-line corrosion via physics-guided machine learning: A methodology integrating field data with theoretical modelsSilakorn P., Jantrakulchai N., Wararatkul N., Wanwilairat S., Kangkachit T., Techapiesancharoenkij R., Rakthanmanon T., Hanlumyuang Y.2022Journal of Petroleum Science and Engineering,
    215, 110558
    6
    33Thai Fingerspelling Recognition Using Hand Landmark ClusteringPhothiwetchakun W., Rakthanmanon T.2021ICSEC 2021 - 25th International Computer Science and Engineering Conference,
    pp. 256-261
    5
    34Efficiently finding near duplicate figures in archives of historical documentsRakthanmanon T., Zhu Q., Keogh E.2012Journal of Multimedia,
    7(2), pp. 109-123
    5
    35Towards discovering the intrinsic cardinality and dimensionality of time series using MDLHu B., Rakthanmanon T., Hao Y., Evans S., Lonardi S., Keogh E.2013Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
    7070 LNAI, pp. 184-197
    4
    36Efficient evolution-based clustering of high dimensional data streams with dimension projectionChairukwattana R., Kangkachit T., Rakthanmanon T., Waiyamai K.20132013 International Computer Science and Engineering Conference, ICSEC 2013,
    pp. 185-190, 6694776
    4
    37Semi-supervised stream clustering using labeled data pointsTreechalong K., Rakthanmanon T., Waiyamai K.2015Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
    9166, pp. 281-295
    4
    38ACCD: Associative classification over concept-drifting data streamsWaiyamai K., Kangkachit T., Saengthongloun B., Rakthanmanon T.2014Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
    8556 LNAI, pp. 78-90
    3
    39Clustering of symbols using minimal description lengthTataw O.M., Rakthanmanon T., Keogh E.J.2013Proceedings of the International Conference on Document Analysis and Recognition, ICDAR,
    pp. 180-184, 6628608
    3
    40AC-Stream: Associative classification over data streams using multiple class association rulesSaengthongloun B., Kangkachit T., Rakthanmanon T., Waiyamai K.2013Proceedings of the 2013 10th International Joint Conference on Computer Science and Software Engineering, JCSSE 2013,
    pp. 223-228, 6567349
    3
    41Prediction of enzyme class by using reactive motifs generated from binding and catalytic sitesLiewlom P., Rakthanmanon T., Waiyamai K.2007Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
    4632 LNAI, pp. 442-453
    3
    42Concept lattice-based mutation control for reactive motifs discoveryWaiyamai K., Liewlom P., Kangkachit T., Rakthanmanon T.2008Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
    5012 LNAI, pp. 767-776
    3
    43Estimation of ethylene/1-butene copolymerization conditions using the autoencoder modelAmnuaykijvanit O., Anantawaraskul S., Rakthanmanon T.2022Journal of Physics: Conference Series,
    2175(1), 012028
    3
    44Hierarchical multi-label associative classification for protein function prediction using gene ontologySangsuriyun S., Rakthanmanon T., Waiyamai K.2019Chiang Mai Journal of Science,
    46(1), pp. 165-179
    2
    45AutoShapelet: Reconstructable Time Series ShapeletsAjchariyasakchai P., Rakthanmanon T.20202020 24th International Computer Science and Engineering Conference, ICSEC 2020,
    9375153
    1
    46Evolution and affinity-propagation based approach for data stream clusteringSunmood A., Rakthanmanon T., Rakthanmanon T., Waiyamai K.2018ACM International Conference Proceeding Series,
    pp. 97-101
    1
    47Information gain Aggregation-based Approach for Time Series Shapelets DiscoveryKramakum C., Rakthanmanon T., Rakthanmanon T., Waiyamai K.2018Proceedings of 2018 10th International Conference on Knowledge and Systems Engineering, KSE 2018,
    pp. 97-101, 8573365
    1
    48Crowdsourced Data Validation for ASR TrainingPhatthiyaphaibun W., Chaksangchaichot C., Rakthammanon T., Chuangsuwanich E., Nutanong S.2023Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH,
    2023-August, pp. 551-555
    1
    49Using rule order difference criterion to decide whether to update class association rulesKongubol K., Rakthanmanon T., Waiyamai K.2010Studies in Computational Intelligence,
    283, pp. 241-252
    1
    50Searching historical manuscripts for near-duplicate figuresRakthanmanon T., Zhu Q., Keogh E.2011ACM International Conference Proceeding Series,
    pp. 14-21
    1
    51Object-oriened Data Mining System: A Tightly-coupled Association Rule Discovery from Object-oriented DatabasesRakthanmanon T., Songsiri C., Waiyamai K.2003Proceedings of 41st Kasetsart University Annual Conference,
    pp. 296-306
    0
    52Classification model with subspace data-dependent ballsKlakhaeng N., Kangkachit T., Rakthanmanon T., Waiyamai K.2013Proceedings of the 2013 10th International Joint Conference on Computer Science and Software Engineering, JCSSE 2013,
    pp. 211-216, 6567347
    0
    53Data Analytics for Thai Teenager Sleep Quality Check-upMahatkeerati P., Aksornsuwan B., Chinnapatpakdeekul P., Rakthanmanon T., Sangkawetai C.2024International Conference on Cybernetics and Innovations, ICCI 20240
    54CCE-Stream: Semi-supervised Stream Clustering Using Color-based ConstraintsTreechalong K., Rakthanmanon T., Waiyamai K.2023Proceedings of JCSSE 2023 - 20th International Joint Conference on Computer Science and Software Engineering,
    pp. 43-48
    0