Ionel Eduard STAN, Ph.D. / University of Milano-Bicocca

Curriculum vitae

Trustworthy (explainable and neuro-symbolic) AI for time series and multimodal signals, with an emphasis on logic-guided learning and representation, auditable explanations, and model monitoring, applied to healthcare, telemonitoring, and smart environments.

This page is built from content/cv.yaml, the single file the printed CV is also generated from, read when the page was built. Turn inspect sources on, in the bar above, to see which part of that file each section comes from. Publications are not repeated here: they have their own index, read from the bibliography.

Download the printed CV (PDF) — typeset from content/cv.yaml by cv/cv.tex when this page was built, so it states the same facts.

Short biocontent/cv.yaml · profile.bio.short

Ionel Eduard Stan is an Assistant Professor (RTD/a) at the University of Milano-Bicocca (DISCo), within the Intelligent Sensing Laboratory (ISLab). His research builds trustworthy, interpretable artificial intelligence (AI) for sequential and multimodal data, combining modern learning with logic-based and neuro-symbolic representations to obtain explanations that can be inspected, validated, and monitored. His work targets high-impact settings—especially healthcare and telemonitoring—and extends to smart environments. He contributes to Italian programmes (ANTHEM/PNC; previously iNEST/PNRR) and serves the community as Associate Editor (Neurocomputing, Frontiers in Artificial Intelligence), including as Lead Editor of a special issue on explainable AI (XAI) for human-centric healthcare, as well as Area Chair and Organizing/Program Committee member for major AI venues. He teaches Databases (B.Sc.), Intelligent Consumer Technologies (M.Sc.), and Foundations of AI (2nd-level Master's).

content/cv.yaml — the profile.bio.short and profile.focus scalars, rendered with the file's own inline grammar (**bold**, _italic_, [text](url)). The same two strings are what scripts/build-cv-data.mjs turns into LaTeX for the PDF.

Appointmentscontent/cv.yaml · appointments[]

content/cv.yaml — appointments[], 3 entries in file order, newest first as written. Keys read: title, place, org, url, dates, announced, items. 3 of 3 carry an items list, shown as the bullets under the organisation.

Educationcontent/cv.yaml · education[]

content/cv.yaml — education[], 3 entries. Keys read: title, place, org, url, dates. The classification in each degree line (cum laude, 110/110) is part of the title string in the file, not added here.

Teachingcontent/cv.yaml · teaching[]

content/cv.yaml — teaching[], 3 entries holding 6 courses between them in their rows[] tables. Each heading line is that entry's org, title, place and dates; each row below it is one row of its rows[], with keys Course, Programme / Level, Key topics, Hours — and those keys, in the order the file writes them, are also the columns of the same table in the printed CV.

University of Milano-Bicocca (DISCo): 2, Bicocca Academy (2nd-level Master, DAI4Health): 1, University of Ferrara: 3 courses. 46 contact hours a year currently, across the 2 posts whose dates run to Present; 107 h/yr summed across all 3 posts on record, the ended ones included (30 h/yr + 6 h/yr + 10 h/yr + 21 h/yr + 20 h/yr + 20 h/yr). Both totals are computed here from the leading number of each Hours column; neither is a figure written in the file.

Supervisioncontent/cv.yaml · supervision

Total supervision: 10+ B.Sc. theses/internships; 5+ M.Sc. theses/internships. Supervision includes problem definition, methodological guidance, implementation support, evaluation protocols, and thesis/report writing.

Topic coverage: Formal Methods; Knowledge-Based AI; Symbolic AI; Robotics; Human–Computer Interaction; Healthcare AI (e.g., dementia prediction); Trustworthy/Explainable AI.

content/cv.yaml — supervision, written as a map: the note paragraphs above, then entries[], 3 rows with keys title, count, detail. The counts in the right-hand column are the count field verbatim, open-ended (10+, 5+, 1) exactly as the file writes them.

Awards and scholarshipscontent/cv.yaml · awards[]

content/cv.yaml — awards[], 4 entries with keys title, detail, dates, items. 1 carry an items list.

Leadership and representationcontent/cv.yaml · leadership[]

content/cv.yaml — leadership[], 5 entries with keys title, detail, dates, place, items. It is an ordinary section of the file that cv/cv.tex does not print, which is the whole answer to keeping a section off the PDF and on the site: leave its \cvpart line out.

These sections exist in content/cv.yaml and this page does not render them: service, projects. The list is derived from the file's own top-level sections minus the ones rendered above. Both have pages of their own, read from this same file: service at /professional_activities/ and projects at /projects/.

Languagescontent/cv.yaml · languages[]

content/cv.yaml — languages[], 5 entries with keys title, detail, in file order. The levels are the file's own words (native, fluent, basic), not a CEFR scale.