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Advaith SiddharthanMember status icon

Professor of Computer Science and Society
Advaith Siddharthan Photograph

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My research specialisation is in Computational Linguistics and Data Science, with a focus on communicating complex data and making information and data (particularly telemetric data) accessible through text analytics, summarisation, reformulation and natural language generation. I have a particular interest in Citizen Science, and in particular, technologies that break down the divide between professional scientists and lay public and facilitate the meaningful engagement of the public with science.

Keys: Natural Language Generation, Citizen Science, Data Analytics, Language Technologies, Artificial Intelligence

Team: Phillimon Mumba, Stefan Rueger, Nirwan Sharma, Kai Waddington


20 Mar 2024

15 Jul 2022

08 Jun 2022

25 Jan 2022

24 Nov 2020

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Publications | Visit External Site for Details Publications | Visit External Site for Details  

Colucci-Gray, L., Hancock, J., Islam, R., Sharma, N., Manches, A., Bowers, L., Lakeman-Fraser, P., Mozier, S., Newman, J., Reuger, S. and Siddharthan, A. (2024) Seeing with hands and touching with eyes: recovering sensorial attention to nature in primary schools, First International Conference on Embodied Education, Danish School of Education (DPU), Tuborgvej 164, 2400 Copenhagen, Denmark

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Hancock, J., Colucci-Gray, L., Siddharthan, A., Manches, A., Sharma, N., Islam, R., Bowers, L., Reuger, S., Lakeman-Fraser, P., Newman, J., Mozier, S. and Barry, R. (2023) 'We felt the textures from nature and it gave us new ideas': Investigating sustainability education through primary school children's natural and digital haptic touch explorations, SERA Conference 2023, Queen Margaret University, Musselburgh, United Kingdom

Publications | Visit External Site for Details Publications | Visit External Site for Details  

Ao, S., Rüger, S. and Siddharthan, A. (2023) Empirical Optimal Risk to Quantify Model Trustworthiness for Failure Detection, 2023 IJCAI Joint Workshop on Artificial Intelligence Safety and Safe Reinforcement Learning, AISafety-SafeRL, Macau, China

Publications | Visit External Site for Details  

Ao, S., Rüger, S. and Siddharthan, A. (2023) Two Sides of Miscalibration: Identifying Over and Under-Confidence Prediction for Network Calibration, Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence, Pittsburgh, PA, USA

Publications | Visit External Site for Details Publications | doi 

Schiller, D., Yu, A., Alia-Klein, N., Becker, S., Cromwell, H., Dolcos, F., Eslinger, P., Frewen, P., Kemp, A., Pace-Schott, E., Raber, J., Silton, R., Stefanova, E., Williams, J., Abe, N., Aghajani, M., Albrecht, F., Alexander, R., Anders, S., Aragón, O., Arias, J., Arzy, S., Aue, T., Baez, S., Balconi, M., Ballarini, T., Bannister, S., Banta, M., Barrett, K., Belzung, C., Bensafi, M., Booij, L., Bookwala, J., Boulanger-Bertolus, J., Boutros, S., Bräscher, A., Bruno, A., Busatto, G., Bylsma, L., Caldwell-Harris, C., Chan, R., Cherbuin, N., Chiarella, J., Cipresso, P., Critchley, H., Croote, D., Demaree, H., Denson, T., Depue, B., Derntl, B., Dickson, J., Dolcos, S., Drach-Zahavy, A., Dubljević, O., Eerola, T., Ellingsen, D., Fairfield, B., Ferdenzi, C., Friedman, B., Fu, C., Gatt, J., deGelder, B., Gendolla, G., Gilam, G., Goldblatt, H., Gooding, A., Gosseries, O., Hamm, A., Hanson, J., Hendler, T., Herbert, C., Hofmann, S., Ibanez, A., Joffily, M., Jovanovic, T., Kahrilas, I., Kangas, M., Katsumi, Y., Kensinger, E., Kirby, L., Koncz, R., Koster, E., Kozlowska, K., Krach, S., Kret, M., Krippl, M., Kusi-Mensah, K., Ladouceur, C., Laureys, S., Lawrence, A., Li, C., Liddell, B., Lidhar, N., Lowry, C., Magee, K., Marin, M., Mariotti, V., Martin, L., Marusak, H., Mayer, A., Merner, A., Minnier, J., Moll, J., Morrison, R., Moore, M., Mouly, A., Mueller, S., Mühlberger, A., Murphy, N., Muscatello, M., Musser, E., Newton, T., Noll-Hussong, M., Norrholm, S., Northoff, G., Nusslock, R., Okon-Singer, H., Olino, T., Ortner, C., Owolabi, M., Padulo, C., Palermo, R., Palumbo, R., Palumbo, S., Papadelis, C., Pegna, A., Pellegrini, S., Peltonen, K., Penninx, B., Pietrini, P., Pinna, G., Lobo, R., Polnaszek, K., Polyakova, M., Rabinak, C., HeleneRichter, S., Richter, T., Riva, G., Rizzo, A., Robinson, J., Rosa, P., Sachdev, P., Sato, W., Schroeter, M., Schweizer, S., Shiban, Y., Siddharthan, A., Siedlecka, E., Smith, R., Soreq, H., Spangler, D., Stern, E., Styliadis, C., Sullivan, G., Swain, J., Urben, S., Stock, J., Kooij, M., Overveld, M., Rheenen, T., VanElzakker, M., Ventura-Bort, C., Verona, E., Volk, T., Wang, Y., Weingast, L., Weymar, M., Williams, C., Willis, M., Yamashita, P., Zahn, R., Zupan, B., Lowe, L., Gabriela, G., F, H. and Leonie, L. (2023) The Human Affectome, pp. (Early access), Elsevier

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