Heri Ramampiaro
Bakgrunn og aktiviteter
Ramampiaro er instuttleder og professor ved Institutt for datateknologi og informatikk, Norges teknisk-naturvitenskapelige universitet (NTNU). Han har tidligere vært gruppeleder for forskningsgruppen for Data og kunstig intelligens, og vært sentral i etableringen av Telenor – NTNU AI-Lab (nå Norwegian Open AI-Lab), som han også var leder for. Hans hovedforskningsinteresser er innen tekstanalyse, informasjonsgjenfinning, og maskinlæring.
Mer informasjon om Ramampiaros forskningsavktiviteter finnes her.
Emner
- IT8802 - Videregående informasjonsgjenfinning
- IT3902 - Masteroppgave i informatikk: Databaser og søk
- TDT4305 - Big Data-arkitektur
Vitenskapelig, faglig og kunstnerisk arbeid
Et utvalg av nyere tidsskriftspublikasjoner, kunstneriske produksjoner, bok, inklusiv bokdeler og rapport-del. Se alle publikasjoner i databasen
Tidsskriftspublikasjoner
- (2022) Evaluating Top-N Recommendations Using Ranked Error Approach: An Empirical Analysis. IEEE Access. vol. 10.
- (2022) Towards human-level performance on automatic pose estimation of infant spontaneous movements. Computerized Medical Imaging and Graphics. vol. 95.
- (2022) Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches. Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART). vol. 3.
- (2021) Exploring Decomposition for Solving Pattern Mining Problems. ACM Transactions on Management Information Systems (TMIS). vol. 12 (2).
- (2021) Density Guarantee on Finding Multiple Subgraphs and Subtensors. ACM Transactions on Knowledge Discovery from Data. vol. 15 (5).
- (2021) Fully automated clinical movement analysis from videos using skeleton-based deep learning. Gait & Posture. vol. 90.
- (2021) New automatic, efficient, and highly precise tracking of infant spontaneous movements. Developmental Medicine & Child Neurology. vol. 63.
- (2021) Machine Learning in Financial Market Surveillance: A Survey. IEEE Access. vol. 9.
- (2020) Space–time series clustering: Algorithms, taxonomy, and case study on urban smart cities. Engineering Applications of Artificial Intelligence. vol. 95.
- (2020) Fast and accurate group outlier detection for trajectory data. Communications in Computer and Information Science. vol. 1259.
- (2020) EfficientPose: Scalable single-person pose estimation. Applied intelligence (Boston).
- (2020) Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles. Proceedings of Machine Learning Research (PMLR). vol. 124.
- (2019) Towards efficiently mining closed high utility itemsets from incremental databases. Knowledge-Based Systems. vol. 165.
- (2019) Deep Learning‐based infant motion tracking facilitating early detection of cerebral palsy. Developmental Medicine & Child Neurology. vol. 61.
- (2019) Locality-adapted kernel densities of term co-occurrences for location prediction of tweets. Information Processing & Management. vol. 56 (4).
- (2019) Forecasting Intra-Hour Imbalances in Electric Power Systems. Proceedings of the AAAI Conference on Artificial Intelligence. vol. 33 (1).
- (2018) A deep network model for paraphrase detection in short text messages. Information Processing & Management. vol. 54.
- (2018) Applying temporal dependence to detect changes in streaming data. Applied intelligence (Boston). vol. 48 (12).
- (2018) High utility drift detection in quantitative data streams. Knowledge-Based Systems. vol. 157.
- (2018) Spatial Statistics of Term Co-occurrences for Location Prediction of Tweets. Lecture Notes in Computer Science (LNCS). vol. 10772.