CV

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Table of Contents:

• Programming languages
• Software
• Technical Skills \& Statistics
• Work experience
• Education
• Languages
• Publications

Programming languages

• Python
• SQL
• R

Software

• Data Visualization: Matplotlib / Seaborn / Plotly
• Data Wrangling: Numpy / Pandas / SciPy
• Machine Learning: Scikit-Learn / XGBoost
• Neural Network: Pytorch / TensorFlow / Keras
• Pretrained models: Transformers (Hugging Face)
• LLM Frameworks: LlamaIndex / LangChain
• Version Control: Git / GitHub
• Development & Deployment: FastAPI / Weights & Biases / Docker
• Dashboards: Tableau

Technical Skills & Statistics

• Exploratory Data Analysis / Data Visualization
• Regression / Classification / Decision Trees
• Neural Networks
• Structured & Unstructured Data
• Supervised & Unsupervised Learning / Hyperparameters Tuning
• Embeddings / Vector Databases
• Large Language Models
• Statistical Modeling
• Bayesian Statistics / Hypothesis Testing
• Unit testing

Work experience

• 2023 - Present │ Data Scientist & Co-Founder at Dailogy (Berlin, Germany; Tbilisi, Georgia)
  • Deployed an API endpoint to enhance LLM-generated output, optimizing the text processing pipeline
  • Developed minimum viable products by quickly testing and implementing solutions, securing funding and forming successful partnerships
  • Researching and implementing NLP tools and LLM solutions
  • Integrated cutting-edge AI advancements, ensuring the system remained up-to-date
  • Tested open-source LLMs, increasing project independence and reducing reliance on third-party software
• 2016 - 2023 │ Research Group Leader at Humboldt-Universität zu Berlin (Berlin, Germany)
  • Led two high-impact research projects, focusing on management and research, and secured over €550,000 in funding
  • Implemented advanced models using Python and R, analyzing structured and unstructured data
  • Created and optimized data pipelines for preprocessing, feature extraction, and analysis
  • Presented compelling data visualizations and reports, effectively communicating insights to both technical and non-technical audiences
• 2014 - 2016 │ Researcher at Tomsk Polytechnic University (Tomsk, Russia)
  • Managed a cross-functional, multicultural team, bridging the gap between economists, computer scientists, and web designers
  • Defined analytical approaches to ensure robust data collection, preprocessing, and analysis, leading to successful project outcomes
  • Tested technologies to enhance well-being, including a tablet-based virtual gym application to mitigate age-related decline
  • Coordinated collaborative projects with universities in Italy and Russia in partnership with founding institutes
• 2012 - 2014 │ Researcher at Burapha University (Saen Suk, Chonburi, Thailand)
  • Instructed university-level courses on data analysis, focusing on data handling and inferential statistics (hypothesis testing).
  • Mentored several Ph.D. students in their research projects, guiding them in advanced data analysis techniques.

Education

• Data Science Retreat (link), Berlin (Germany), 06/2023 - 09/2023
• Ph.D. in Cognitive Sciences, University of Trento (Italy), 11/2008 - 10/2011
• M.sc in Cognitive Science, University of Trento (Italy), 10/2005 - 09/2008
• B.sc in Philosophy, University of Genova (Italy), 09/2000 - 10/2005

Languages

• Italian: native speaker
• English: proficient
• German: basic knowledge

Publications

See also: Google Scholar

• Didino, D., Brandtner, M., Glaser, M, & Knops, A. (2023). Probing the Dual-Route Model of the SNARC Effect by Orthogonalizing Processing Speed and Depth. Experimental Psychology, 2. doi: 10.1027/1618-3169/a000577
• Didino, D., Brandtner, M., & Knops, A. (2022). No influence of masked priming on the multiplication fact retrieval in a result verification task. Journal of Numerical Cognition, 8. doi: 10.5964/jnc.8319
• Labree, B., Corrie, H., Karolis, V., Didino, D., & Cappelletti, M. (2020). Parietal alpha-based inhibitory abilities are causally linked to numerosity discrimination. Behavioural Brain Research, 387. doi: 10.1016/j.bbr.2020.112564
• Didino, D., Taran, E.A., Barysheva, G.A., & Casati, F. (2019). Psychometric evaluation of the Russian version of the flourishing scale in a sample of older adults living in Siberia. Health Qual Life Outcomes, 17(34). doi: 10.1186/s12955-019-1100-6
• Didino, D., Breil, C., & Knops, A. (2019). The influence of semantic processing and response latency on the SNARC effect. Acta psychologica, 196. doi: 10.1016/j.actpsy.2019.04.008
• Didino, D., Pinheiro-Chagas, P., Wood, G., & Knops, A. (2019) Response: Commentary: The Developmental Trajectory of the Operational Momentum Effect. Frontiers in Psychology, 10:160. doi: 10.3389/fpsyg.2019.00160
• Pinheiro-Chagas, P., Didino, D., Haase, V. G., Wood, G., & Knops, A. (2018). The developmental trajectory of the operational momentum effect. Frontiers in Psychology, 9:1062. doi: 10.3389/fpsyg.2018.01062
• Didino, D., Taran, E. A., Gorodetski, K., Melikyan, Z. A., Nikitina, S., Gumennikov, I., Korovina, O., & Casati, F. (2017). Exploring predictors of life satisfaction and happiness among Siberian older adults living in Tomsk Region. European Journal of Ageing, 15(2). doi: 10.1007/s10433-017-0447-y
• Nikitina, S., Didino, D., Baez, M., & Casati, F. (2018). Feasibility of virtual tablet-based group exercise among older adults in siberia: findings from two pilot trials. JMIR Mhealth Uhealth, 6(2), doi: 10.2196/mhealth.7531
• Baez, M., Far, I. K., Ibarra, F., Ferron, M., Didino, D., & Casati, F. (2017). Effects of online group exercises for older adults on physical, psychological and social wellbeing: a randomized pilot trial. PeerJ, 5. doi: 10.7717/peerj.3150
• Yen, M.H., Han, C.C., Yu, P.C., Yang, T.H., Didino, D., Butterworth, B., & Yen, N.S. (2017). The influence of memory updating and number sense on junior high school math attainment. Learning and Individual Differences, 54. doi: 10.1016/j.lindif.2017.01.012
• Lecce, F., Walsh, V., Didino, D., & Cappelletti, M. (2015). “How many” and “how much” dissociate in the parietal lobe. Cortex, 73. doi: 10.1016/j.cortex.2015.08.007
• Didino, D., Knops, A., Vespignani, F., & Kornpetpanee, S. (2015). Asymmetric activation spreading in the multiplication associative network due to asymmetric overlap between numerosities semantic representations? Cognition, 141. doi: 10.1016/j.cognition.2015.04.002
• Cappelletti, M., Didino, D., Stoianov, I., & Zorzi, M. (2014). Number skills are maintained in healthy ageing. Cognitive Psychology, 69. doi: 10.1016/j.cogpsych.2013.11.004
• Didino, D., Vespignani, F., & Lombardi, L. (2014). Operands-order effect in multiplication and addition: The long-term effects of reorganization process and acquisition sequence. Experimental Psychology. 61(6). doi: 10.1027/1618-3169/a000264
• Cappelletti, M., Gessaroli, E., Hithersay, R., Mitolo, M., Didino, D., Kanai, R., Cohen Kadosh, R., & Walsh, V. (2013). Transfer of cognitive training across magnitude dimensions achieved with concurrent brain stimulation of the parietal lobe. The Journal of Neuroscience, 33(37). doi: 10.1523/JNEUROSCI.1692-13.2013
• Bahrami, B., Didino, D., Frith, C., Butterworth, B., & Rees, G. (2013). Collective enumeration. Journal of Experimental Psychology: Human Perception and Performance, 39(2). doi: 10.1037/a00229717