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Journal Articles (64)

Agres KR, Schaefer RS, Volk A, Van Hooren S, Holzapfel A, Dalla Bella S, Muller M, de Witte M, Herremans D, Ramirez Melendez R, Neerincx M, Ruiz S, Meredith D, Dimitriadis T, Magee WL. Music, Computing, and Health: A Roadmap for the Current and Future Roles of Music Technology for Health Care and Well-Being. Music and Science 2021; 4(0).

Beardsley M.; Hernandez-Leo D.; Ramirez-Melendez R.. Seeking reproducibility: assessing a multimodal study of the testing effect. Journal of Computer Assisted Learning 2018; 34(4): 378-386.

Blanco A.D.; Ramirez R.. Evaluation of a Sound Quality Visual Feedback System for Bow Learning Technique in Violin Beginners: An EEG Study. Frontiers in Psychology 2019; 10(165).

Blanco A.D.; Tassani S.; Ramirez R.. Effects of Visual and Auditory Feedback in Violin and Singing Voice Pitch Matching Tasks. Frontiers in Psychology 2021; 12: 1-15.

Blanco A.D.; Tassani S.; Ramirez R.. Real-Time Sound and Motion Feedback for Violin Bow Technique Learning: A Controlled, Randomized Trial. Frontiers in Psychology 2021; 12: 1-15.

Conklin D.; Anagnostopoulou C.; Ramirez R.. Intelligent Data Analysis: Guest editorial. Intelligent Data Analysis 2010; 14(5).

Conklin D.; Ramirez R.. Introduction to the special issue on music and machine learning. Journal of New Music Research 2011; 40(2): 91-92.

Conklin D.; Ramirez R.; Iñesta J.M.. New Directions in Music and Machine Learning. Journal of New Music Research 2014; 43(3): 251-254.

Dalmazzo D, Ramirez R. Bow Gesture Classification to Identify Three Different Expertise Levels: A Machine Learning Approach. Communications in Computer and Information Science 2020; 1168 CCIS(0): 494-501.

Dalmazzo D.; Ramirez R.. Bowing gestures classification in violin performance: a machine learning approach. Frontiers in Psychology 2019; 10(344).

Dalmazzo D.; Waddell G.; Ramirez R.. Applying deep learning techniques to estimate patterns of musical gesture. Frontiers in Psychology 2021; (11).

Giraldo S.; Ramirez R.. A machine learning approach to ornamentation modeling and synthesis in jazz guitar. Journal of Mathematics and Music 2016; 10(2): 107-126.

Giraldo S.; Waddell G.; Nou I.; Ortega A.; Mayor O.; Perez A.; Williamon A.; Ramirez R.. Automatic assessment of tone quality in violin music performance. Frontiers in Psychology 2019; 10(334): 1-12.

Giraldo S.I.; Ramirez R.. A Machine Learning Approach to Discover Rules for Expressive Performance Actions in Jazz Guitar Music. Frontiers in Neuroscience 2016; 7.

Hazan A.; Ramirez R.; Maestre E.; Perez A.; Pertusa A.. Modeling Expressive Performance: a Regression Tree Approach Based on Strongly Typed Genetic Programming. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2006; 3907: 676-687.

Heroux I.; Giraldo S.; Ramirez R.; Dube F.; Creech A.; Thouin-Poppe L.E.. Measuring the impacts of extra-musical elements in guitar music playing: a pilot study.. Frontiers in Psychology 2020; 11(1964): 1-10.

Iñesta J.M.; Conklin D.; Ramirez R.. Machine learning and music generation. Journal of Mathematics and Music 2016; 10(2): 87-91.

Kitahara T, Giraldo S, Ramirez R. JamSketch: Improvisation Support System with GA-Based Melody Creation from User¿s Drawing. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2018; 11265 LNCS(0): 509-521.

Kosta K.; Ramirez R.; Bandtlow O.F.; Chew E.. Mapping between dynamic markings and performed loudness: a machine learning approach. Journal of Mathematics and Music 2016; 10(2): 149-172.

Maestre E.; Ramirez R.. An approach to predicting bowing control parameter contours in violin performance. Intelligent Data Analysis 2010; 14(5): 587-599.

Maestre E.; Ramirez R.; Kersten S.; Serra X.. Expressive concatenative synthesis by reusing samples from real performance recordings. Computer Music Journal 2009; 33(4): 23-42.

Marchini M, Ramirez R, Papiotis P, Maestre E. A Machine Learning Approach to String Quartet Expressive Performance Modeling. Journal of New Music Research 2014.

Marchini M.; Ramirez R.; Papiotis P.; Maestre E.. The Sense of Ensemble: a Machine Learning Approach to Expressive Performance Modelling in String Quartets. Journal of New Music Research 2014; 43(3): 303-317.

Marinescu M, Ramirez R. Learning singer-specific performance rules. International Journal of Modeling and Optimization 2012; 2(2): 97-102.

Ortega F.J.M.; Giraldo S.I.; Perez A.; Ramirez R.. Phrase-Level Modeling of Expression in Violin Performances. Frontiers in Psychology 2019; 10(776).

Papatzikis E.; Zeba F.; Sarkamo T.; Ramirez R.; Grau-Sanchez J.; Tervaniemi M.; Loewy J.. Mitigating the impact of the novel coronavirus pandemic on neuroscience and music research protocols in clinical populations. Frontiers in Psychology 2020; (11).

Pérez A, Ramirez R, Kersten S. Modeling Moods in Violin Performances. Proceedings of the SMC Conferences 2008.

Perez-Sancho C.; Rizo D.; Iesta J.M.; De Leon P.J.P.; Kersten S.; Ramirez R.. Genre classification of music by tonal harmony. Intelligent Data Analysis 2010; 14(5): 533-545.

Ponce León P, Rizo D, Ramirez R, Iñesta JM. Melody Characterization by a Genetic Fuzzy System. Proceedings of the SMC Conferences 2008.

Ramirez R. First-order Rule Discovery with Ant Colony Optimization. Applied Soft Computing 2016.

Ramirez R. Inductive Logic Programming and Music. International Computer Music Conference Proceedings 2004; 0(0): 1-4.

Ramirez R. Learning Sets of Musical Rules. International Computer Music Conference Proceedings 2003; 0(0).

Ramirez R, Gomez E, Vicente V, Puiggros M, Hazan A, Maestre E. Modeling expressive music performance in bassoon audio recordings. Lecture Notes in Control and Information Sciences 2006; 345(0): 951-957.

Ramirez R, Hazan A. A learning scheme for generating expressive music performances of jazz standards. IJCAI: proceedings of the conference 2005; 0(0): 1628-1629.

Ramirez R, Hazan A. Learning Expressive Performance Rules in Jazz. International Computer Music Conference Proceedings 2004; 0(0): 1-4.

Ramirez R, Hazan A, Maestre E, Serra X. A Genetic Rule-based Expressive Performance Model for Jazz Saxophone. Computer Music Journal 2008; 32(1): 338-350.

Ramirez R, Puiggros M. A genetic programming approach to feature selection and classification of instantaneous cognitive states. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2007; 4448 LNCS(0): 311-319.

Ramirez R, Puiggros M. A Genetic Programming Approach to Feature Selection and Classification of Instantaneous Cognitive States, European Workshop on Evolutionary Computation in Image Analysis and Signal Processing. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2007.

Ramirez R, Santosa AE. Declarative concurrency in Java. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2000; 1800 LNCS(0): 332-339.

Ramirez R.. Inducing Musical Rules with ILP. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2003; 2916: 502-504.

Ramirez R.. Representing and executing real-time systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 1998; 1470: 279-287.

Ramirez R.. Concurrent object-oriented programming in Tempo++. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 1996; 1179: 244-253.

Ramirez R.; Hazan A.. A Tool for Generating and Explaining Expressive Music Performances of Monophonic Jazz Melodies. International Journal on Artificial Intelligence Tools 2006; 15: 673-691.

Ramirez R.; Hazan A.. Understanding Expressive Music Performance Using Genetic Algorithms. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2005; 3449: 508-516.

Ramirez R.; Hazan A.; Gomez E.; Maestre E.; Serra X.. Discovering Expressive Transformation Rules from Saxophone Jazz Performances. Journal of New Music Research 2005; 34(4): 319-330.

Ramirez R.; Maestre E.; Perez A.; Serra X.. Automatic Performer Identification in Celtic Violin Audio Recording. Journal of New Music Research 2011; 40(2): 165-174.

Ramirez R.; Maestre E.; Pertusa A.; Gomez E.; Serra X.. Performance-based Interpreter Identification in Saxophone Audio Recordings. IEEE Transactions on Circuits and Systems for Video Technology 2007; 17(3): 356-364.

Ramirez R.; Maestre E.; Serra X.. A Rule-Based Evolutionary Approach to Music Performance Modeling. IEEE Transactions on Evolutionary Computation 2012; 16(1): 96-107.

Ramirez R.; Maestre E.; Serra X.. Automatic performer identification in commercial monophonic Jazz performances. Pattern Recognition Letters 2010; 31(12): 1514-1523.

Ramirez R.; Martinez J.. Constraint-based Synchronization and Verification of Distributed Java Programs. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004; 3132: 473-474.

Ramirez R.; Palencia-Lefler M.; Giraldo S.; Vamvakousis Z.. Musical neurofeedback for treating depression in elderly people. Frontiers in Neuroscience 2015; 9(354).

Ramirez R.; Perez A.; Kersten S.; Rizo D.; Roman P.; Inesta J.M.. Modeling violin performances using inductive logic programming. Intelligent Data Analysis 2010; 14(5): 573-585.

Ramirez R.; Planas J.; Escude N.; Mercade J.; Farriols C.. EEG-based analysis of the emotional effect of music therapy on palliative care cancer patients. Frontiers in Psychology 2018; 9(254).

Ramirez R.; Puiggros M.. A Machine Learning Approach to Detecting Instantaneous Cognitive States from fMRI Data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2007; 4426: 248-259.

Ramirez R.; Santosa A.E.. Event Logic Programming. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2001; 2127: 314-318.

Ramirez R.; Santosa A.E.; Hong L.W.. Implementing declarative concurrency in Java. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2000; 1900: 700-708.

Ramirez R.; Vamvakousis Z.. Detecting Emotion from EEG Signals using the Emotiv Epoc Device. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2012.

Ramirez-Melendez R, Reija X. The Creative Drummer: An EEG-Based Pilot Study on the Correlates of Emotions and Creative Drum Playing. Brain Sciences 2023; 13(1).

Ramirez-Melendez R.; Matamoros E.; Hernandez D.; Mirabel J.; Sanchez E.; Escude N.. Music-Enhanced Emotion Identification of Facial Emotions in Autistic Spectrum Disorder Children: A Pilot EEG Study. Brain Sciences 2022; 12(6): 1-11.

Sayis B.; Ramirez R.; Pares N.. Mixed reality or LEGO game play? Fostering social interaction in children with Autism. Virtual Reality 2022; 26(2): 771-787.

Torres-Hernandez A, Brambila-Paz F, Ramirez-Melendez R. Proposal for Use of the Fractional Derivative of Radial Functions in Interpolation Problems. Fractal and Fractional 2024; 8(1).

Vamvakousis Z, Ramirez R. A high-throughput auditory P300 interface for everyone. Assistive Technology Research Series 2013; 33(0): 478-482.

Vamvakousis Z, Ramirez R. Temporal control in the eyeharp gaze-controlled musical interface. Proceedings of the International Conference on New Inferfaces for Musical Expression 2012; 0(0).

Vamvakousis Z.; Ramirez R.. The EyeHarp: A Gaze-Controlled Digital Musical Instrument. Frontiers in Psychology 2016; 7: 1-14.

Books (1)

Ramirez R, Conklin D, Iñesta JM (eds.). Proceedings of the 10th International Workshop on Machine Learning and Music (MML 2017). Barcelona: 2017.

Book Chapters (9)

Ramirez A, Ramirez R. A Mathematical Analysis of Mexican Brick Vaults and Domes. In: AA.VV. Architecture and mathematics from antiquity to the future. Basel: Birkhauser Verlag; 2013.

Ramirez R. Modelling, Analysing, Identifying and Synthesizing Expressive Popular Music Performances. In: Kirke, Alexis; Reck Miranda, Eduardo. Guide to Computing for Expressive Music Performance. London - New York: Springer; 2013. p. 123-144.

Ramirez R. Identifying saxophonists from their playing styles. In: Shen, Jialie et al., Editors. Intelligent Music Information Systems: Tools and Methodologies. Hershey, PA: Information Science Reference; 2008. p. 102-119.

Ramirez R. Identifying Famous Interpreters from Their Playing Style. In: Shen, Jialie et al., Editors. Intelligent Music Information Systems: Tools and Methodologies. Hershey, PA: Information Science Reference; 2008. p. 221-238.

Ramirez R, Hazan A, Maestre E, Serra X. Evolutionary Computing for Expressive Music Performance. In: Romero, Juan; Machado, Penousal (Eds.). The Art of Artificial Evolution. Berlin-Heidelberg: Springer; 2008. p. 123-144.

Ramirez R, Hazan A, Maestre E, Serra X. A Machine Learning Approach to Expressive Performance in Jazz Standards. In: Valery A. Petrushin and Latifur Khan (eds.).. Multimedia Data Mining and Knowledge Discovery. London: Springer; 2007. p. 1-2.

Ramirez R, Hazan A, Maestre E, Serra X. A Data Mining Approach to Expressive Music Performance Modeling. In: Valery A. Petrushin and Latifur Khan (eds.).. Multimedia Data Mining and Knowledge Discovery. London: Springer; 2007. p. 379-399.

Ramirez-Melendez R.; Giraldo S.; Waddell G.; Williamon A.. A Machine Learning Approach to Automatic Sound Quality Assessment in Violin Learning. In: -. -. -; 2022.

Torres-Hernandez A, Brambila-Paz F, Ramirez-Melendez R. Sets of fractional operators and some of their applications. In: Abou Jaoudé A (ed.). Operator theory - recent advances, new perspectives and applications.. Intechopen; 2023. p. 79-96.

Manuals (47)

Gregory S, Ramirez R. Tempo: a Declarative Concurrent Programming Language. MIT Press; 1995.

Hazan A, Ramirez R, Maestre E, Perez A, Pertusa A. Modelling Expressive Performance: a Regression Tree Approach Based on Strongly Typed Genetic Programming. Springer-Verlag; 2006.

Ramirez R. Concurrent and Distributed Programming Using Constraint Logic Programs. ACM Press; 2004.

Ramirez R. Inductive Logic Programming and Music. ICMA Press; 2004.

Ramirez R. Inducing Musical Rules with ILP. Springer-Verlag; 2003.

Ramirez R. Inductive Logic Programming for Learning Musical Rules. 2003.

Ramirez R. Learning Sets of Musical Rules. ICMA Press; 2003.

Ramirez R. constraint-based methodology for coordination in multi-agent systems. 2002.

Ramirez R. A coordination model for real-time programming. Springer-Verlag; 1999.

Ramírez R. A Concurrent Object-Oriented Real-Time Programming Language. 1998.

Ramirez R. Representing and executing real-time systems. Springer-Verlag; 1998.

Ramirez R. Time, Communication and Synchronisation in an Agent-Based Programming Language. IEEE Press; 1998.

Ramirez R. A logical approach for specification and execution of concurrent real-time systems. IEEE Press; 1997.

Ramirez R. Towards declarative concurrent real-time programming. Springer-Verlag; 1997.

Ramirez R. A logic-based concurrent object-oriented programming language . 1996.

Ramirez R. Concurrent Object-Oriented Programming in Tempo++. Springer-Verlag; 1996.

Ramirez R. Declarative Concurrent Object-Oriented Programming in Tempo++. 1995.

Ramirez R. Nets, Logic and Object-Oriented Programming. 1995.

Ramirez R. Precedence Constraints in Tempo. 1995.

Ramirez R, Hazan A. A Learning Scheme for Generating Expressive Music Performances of Jazz Standards. 2005.

Ramirez R, Hazan A. An Approach to Expressive Music Performance Modeling. 2005.

Ramirez R, Hazan A. Modeling Expressive Music Performance in Jazz. AAAI Press; 2005.

Ramirez R, Hazan A. Understanding Expressive Music Performance Using Genetic Algorithms. Springer-Verlag; 2005.

Ramirez R, Hazan A. Learning Expressive Performance Rules in Jazz. ICMA Press; 2004.

Ramirez R, Hazan A. Rule induction for expressive music performance modeling. 2004.

Ramirez R, Hazan A, Gomez E, Maestre E. A Machine Learning Approach to Expressive Performance in Jazz Standards. 2004.

Ramirez R, Hazan A, Gomez E, Maestre E. Understanding Expressive Transformations in Saxophone Jazz Performances Using Inductive Machine Learning. 2004.

Ramirez R, Hazan A, Maestre E. A Sequential Covering Evolutionary Algorithm for Expressive Music Performance. AAAI Press; 2006.

Ramirez R, Hazan A, Maestre E. Intra-note Features Prediction Model for Jazz Saxophone Performance. 2005.

Ramirez R, Hazan A, Maestre E, Serra X. A Data Mining Approach to Expressive Music Performance Modeling. Springer; 2006.

Ramirez R, Hazan A, Maestre E, Serra X. Evolutionary Expressive Music Performance Modeling. Springer; 2006.

Ramirez R, Martinez J, Santosa A. Constraint-based Concurrent and Distributed programming in Java. 2004.

Ramirez R, Martinez J, Santosa A. Constraint-based Synchronization and Verification of Distributed Java Programs. ACM Press; 2004.

Ramirez R, Martinez J, Santosa A. Model Checking Constraint-based Concurrent Java Programs. 2004.

Ramirez R, Martinez J, Santosa A. Poster Presentation: Constraint-based Synchronization and Verification of Distributed Java Programs. Springer-Verlag; 2004.

Ramirez R, Martinez J, Santosa A. The Implementation of a Constraint-based Distributed Java Programming Framework. ISCA Press; 2004.

Ramirez R, Peralta J. A constraint-based melody harmonizer. 1998.

Ramirez R, Santosa A. Formal Verification of Concurrent and Distributed Constraint-based Java Programs. IEEE Press; 2005.

Ramirez R, Santosa A. A Methodology for Concurrent and Distributed Java Applications. IEEE Computer Society Press; 2003.

Ramirez R, Santosa A. An Aspect-Oriented Framework for Concurrent Applications. 2003.

Ramirez R, Santosa A. A Methodology for Reliable Concurrent Programming. Chillarege Press; 2002.

Ramirez R, Santosa A. Distributed Programming Using Constraint Logic Programs. CSREA Press; 2002.

Ramirez R, Santosa A. Event Logic Programming. Springer-Verlag; 2001.

Ramirez R, Santosa A. A Declarative Approach to Concurrency in Java. 2000.

Ramirez R, Santosa A. Declarative concurrency in Java. Springer-Verlag; 2000.

Ramirez R, Santosa A, Wei Hong L. Implementing declarative concurrency in Java. Springer-Verlag; 2000.

Ramirez R, Santosa A, Yap R. Concurrent programming made easy. IEEE Press; 2000.

Conference proceedings (36)

Anglade A, Ramirez R, Dixon S. First-order logic classification models of musical genres based on harmony. In: VV.AA.. Sound and Music Computing Conference 2009. MIT Press; 2009. p. 309-314.

Anglade A.; Ramirez R.; Dixon S.. Genre classification using harmony rules induced from automatic chord transcriptions. In: VV.AA.. Proceedings of the 10th International Society for Music Information Retrieval Conference ISMIR 2009. Kobe: International Society for Music Information Retrieval; 2009. p. 669-674.

Bantula H.; Giraldo S.; Ramirez R.. Jazz ensemble expressive performance modeling. In: Devaney J, Mandel MI, Turnbull D, Tzanetakis G (eds.). Proceedings of the 17th International Society for Music Information Retrieval Conference ISMIR 2016. ISMIR; 2016. p. 674-680.

Blanco A.; Ramirez R.. Evaluation of audio-based feedback technologies for bow learning technique in violin beginners. In: AA. VV.. Proceedings of the 1st ACM SIGCHI International Workshop on Multimodal Interaction for Education. 2017. p. 41-43.

Blanco AD, Ramirez R. Neural correlates of bow learning technique. In: Ramirez R, Conklin D, Iñesta JM (eds.). Proceedings of the 10th International Workshop on Machine Learning and Music (MML 2017). Barcelona: 2017. p. 1-6.

Dalmazzo D.; Ramirez R.. Air Violin: A Machine Learning Approach to Fingering Gesture Recognition. In: -. MIE 2017: 1st international workshop on multimodal interaction for education. Glasgow: ACM, 2017; 2017. p. 63-66.

Dalmazzo D.; Tassani S.; Ramirez R.. A Machine learning approach to violin bow technique classification: a comparison between IMU and MOCAP systems. In: Matthies DJC, Haescher M, Yordanova K, Bieber G, Schröder M, Kirste T, Urban, B (eds.). 5th international Workshop on Sensor-based Activity Recognition and Interaction, Proceedings. Berlin: Association for Computing Machinery; 2018.

Diaz D.; Ramirez R.; Hernandez-Leo D.. The effect of using a talking head in academic videos: An EEG study. In: AA.VV.. 2015 IEEE 15th International Conference on Advanced Learning Technologies (ICALT). huanlien: IEEE; 2015. p. 367-369.

Giraldo S, Ramirez R. Performance to Score Sequence Matching for Automatic Ornament Detection in Jazz Music. In: -. International Conference on New Music Concepts. ABEditore; 2015.

Giraldo S, Ramirez R. Optimizing Melodic Extraction Algorithm for Jazz Guitar Recordings Using Genetic Algorithms. In: VV.AA.. International Computer Music Conference/Sound and Music Computing Conference. 2014.

Giraldo S.; Ortega A.; Perez A.; Ramirez R.; Waddell G.; Williamon A.. Automatic assessment of violin performance using dynamic time warping classification. In: -. 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018. IEEE; 2018. p. 1-3.

Kersten S.; Ramirez R.. Concatenative synthesis of expressive saxophone performance. In: Supper, Martin; Weinzierl, Stefan (eds.). SMC 08 5th Sound and Music Computing Conference sound in space - space in sound, July 31st - August 3rd, 2008, Berlin, Germany proceedings. Berlin: Universita¿tsverlag der TU, Universita¿tsbibliothek; 2008.

Lionello M.; Ramirez R.. A machine learning approach to violin vibrato modelling in audio performances and a didactic application for mobile devices. In: AA. VV. The 15th International Sound & Music Computing Conference. 2018. p. 347-353.

Marinescu M.C.; Ramirez R.. A timing-based classification method for human voice in opera recordings. In: AA.VV.. 8th International Conference on Machine Learning and Applications, ICMLA 2009. IEEE; 2009. p. 577-582.

Marinescu M.C.; Ramirez R.. Expressive performance in the human tenor voice. In: Supper, Martin; Weinzierl, Stefan (eds.). SMC 08 5th Sound and Music Computing Conference sound in space - space in sound, July 31st - August 3rd, 2008, Berlin, Germany proceedings. Berlin: Universita¿tsverlag der TU, Universita¿tsbibliothek; 2008.

Martinez-Pelaez J.J.; Buenabad-Chavez J.; Rangel-Garcia J.; Ramirez-Melendez R.. BDSP: A big data start platform. In: Pei J., Tang J., Silvestri F. Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015. Association for Computing Machinery; 2015. p. 1110-1117.

Muneratti Ortega FJ, Perez-Carrillo A, Ramírez R. Predicting Dynamics in Violin Pieces with Features from Melodic Motifs. In: Cellier P, Driessens K (eds.). Machine Learning and Knowledge Discovery in Databases International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part II. Springer Nature; 2019. p. 517-523.

Neocleous A.; Ramirez R.; Perez A.; Maestre E.. Modeling emotions in violin audio recordings. In: AAVV. Proceedings of 3rd international workshop on Machine learning and music. ACM; 2010. p. 17-20.

Ortega F.J.M.; Giraldo S.I.; Ramirez R.. Bowing modeling for violin students assistance. In: AA. VV.. Proceedings of the 1st ACM SIGCHI International Workshop on Multimodal Interaction for Education. 2017. p. 60-62.

Ortega FJM, Giraldo S, Ramírez R. Phrase-level modeling of expression in violin performances. In: -. 10th International Workshop on Machine Learning and Music. 2017. p. 49-54.

Perez A.; Ramirez R.; Kersten S.. Modeling Moods in Violin Performances. In: Supper, Martin; Weinzierl, Stefan (eds.). SMC 08 5th Sound and Music Computing Conference sound in space - space in sound, July 31st - August 3rd, 2008, Berlin, Germany proceedings. Berlin: Universita¿tsverlag der TU, Universita¿tsbibliothek; 2008. p. 30-33.

Puiggròs M, Gómez Gutiérrez E, Ramírez R, Serra X, Bresin R. Automatic characterization of ornamentation from bassoon recordings for expressive synthesis. In: Baroni, M (ed.). Proceedings of 9th International Conference on Music Perception and Cognition. Society for Music Perception & Cognition; European Society for the Cognitive Sciences of Music; 2006. p. 1533-1538.

Ramirez R, Gómez E, Vicente V, Puiggros M, Hazan A, Maestre E. Modeling Expressive Music Performance in Bassoon Audio Recordings. In: A.A.V.V. Intelligent Computing in Signal Processing and Pattern Recognition. Berlin: Springer; 2006. p. 951-957.

Ramirez R, Santosa A. A framework for separation of concerns in concurrent programming(. In: AA.VV.. 31st Annual International Computer Software and Applications Conference, COMPSAC 2007. IEEE; 2007. p. 619-624.

Ramirez R.. Relational-AntMiner: First-order rule discovery with ant colony optimization. In: AA.VV.. Proceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology. Institute of Electrical and Electronics Engineers; 2016. p. 47-50.

Ramirez R.. Ant colony optimization for first-order rule discovery. In: AA.VV.. 2015 IEEE Symposium Series on Computational Intelligence, SSCI. IEEE; 2015. p. 1141-1145.

Ramirez R.; Conklin D.; Anagnostopoulou C.. MML'10 Chairs' welcome message. In: AAVV. Proceedings of 3rd international workshop on Machine learning and music. ACM; 2010.

Ramirez R.; Perez A.; Kersten S.. Performer Identification in Celtic Violin Recordings. In: Bello, Juan Pablo (ed.); Chew, Elaine (ed.); Turnbull, Douglas (ed.). International Conference on Music Information Retrieval. 2008. p. 483-488.

Ramirez R.; Volpe G.; Canepa C.; Ghisio S.; Kolykhalova K.; Giraldo S.; Mayor O.; Perez A.; Mancini M.; Volta E.; Waddell G.; Williamon A.. Enhancing music learning with smart technologies. In: -. ACM International Conference Proceeding Series. 2018.

Sayis B.; Crowell C.; Benitez J.; Ramirez R.; Pares N.. Computational modeling of psycho-physiological arousal and social initiation of children with autism in interventions through full-body interaction. In: AA.VV.. Proceedings 2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII). Cambridge: IEEE; 2019. p. 573-579.

Torres-Hernández A, Brambila-Paz F, Ramírez-Meléndez, R. Abelian groups of fractional operators. In: M. Cruz-Duarte, J.; Toledo-Hernández, P. (eds.). Proceedings Computer Sciences & Mathematics Forum (MWFC 2022). University of Veracruz; 2022. p. 1-12.

Vamvakousis Z, Prez A, Ramirez R. Acquisition of violin instrumental gestures using an infrared depth camera. In: AA. VV. The 15th International Sound & Music Computing Conference. 2018. p. 171-176.

Vamvakousis Z, Ramirez R. Is an auditory P300-based Brain-Computer Musical Interface feasible?. In: -. CMMR2015: International Workshop on BCMI. Springer Verlag; 2015.

Vamvakousis Z, Ramirez R. P300 Harmonies: A Brain-Computer Musical Interface. In: VV.AA.. International Computer Music Conference/Sound and Music Computing Conference. 2014.

Vamvakousis Z, Ramirez R. A High-Throughput Auditory P300 Interface for Everyone. In: Encarnaçao P, Azevedo L, Jan Gelderblom G, Newell AF, Mathiassen NE. Assistive technology from research to practice, AAATE 2013. IOS Press; 2013. p. 478-482.

Yesiler F, Ramirez R. A machine learning approach to classification of phonation modes in singing. In: AA. VV. The 15th International Sound & Music Computing Conference. 2018. p. 362-367.

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