Prof Iadh Ounis he/him

With over three decades of experience in information retrieval, artificial intelligence and data science, my research focuses on developing intelligent, data-driven systems that learn from the user interactions to support effective and responsible information access. My work spans web and expert search, news and social media retrieval, search result diversification, fairness and transparency in AI, as well as deep neural models for search and recommendation. I appear in the top 2% cited scientists list by Stanford University and Elsevier since its inception in 2020 (updated in 2024) in the Artificial Intelligence field.

My research is inherently interdisciplinary. I have collaborated with social and political scientists, urbanists, journalists, clinicians, archivists, and marketing experts on numerous pluri-displinary projects that bridge technical innovation with societal needs. I have also led or contributed to large-scale, cross-sector initiatives in the UK and internationally, working with both public institutions and industry partners — from SMEs to global multinational tech companies through government departments.

I have graduated 27 PhD students from four continents, including four women and over 85% international students. My former PhD students have gone on to senior roles at leading tech companies (e.g., Microsoft, Amazon, Meta/Facebook, Siemens), academic positions at institutions such as Glasgow, Sheffield, Copenhagen, UFMG (Brazil), Beijing & CAS (China), and Putra (Malaysia), as well as roles in the public sector (e.g., Thailand). I take pride in being a supportive, collaborative supervisor who encourages independence, team work, critical thinking, and ethical awareness.

Within the DiveIn CDT, I’m particularly interested in projects focused on responsible AI, developing fair, transparent, and explainable technologies that help people access the right information. I’m keen to co-supervise interdisciplinary PhD projects that leverage technical innovation to address real-world challenges (e.g. misinformation, bias), and to collaborate with colleagues across disciplines to explore the societal impact of intelligent systems.

As a member of an ethnic minority in the UK, I am deeply committed to equity, diversity, and inclusion (EDI). I actively foster an inclusive research environment and advocate for fairness and transparency in both research practices and academic culture. My research group takes pride in its long-standing diversity, hosting academics, researchers, students and visitors from across the world. I look forward to contributing meaningfully to the DiveIn community’s mission and mentoring the next generation of responsible AI researchers.