Susanne Neufang | AI in Life Science Research | Editorial Board Member

Published on by Life Science

Dr. Susanne Neufang | AI in Life Science Research | Editorial Board Member

University of Cologne | Germany

PD Dr. rer. nat. Susanne Neufang is a highly accomplished researcher with a strong record of scientific productivity and impact, demonstrated through 52 publications, including indexed and collaborative works across cognitive neuroscience, psychiatry, neuroimaging, and machine-learning–driven mental health research. Her contributions have earned a significant global footprint, reflected in a total citation count of 2,479 and an impressive h-index of 27, underscoring the consistent influence and recognition of her research within the scientific community. In addition, she holds an i10-index of 50, highlighting the breadth of her impactful publications that have gained substantial scholarly attention. Her work spans innovative areas such as functional and structural brain connectivity, developmental neuroimaging, executive function research, anxiety disorders, ADHD, and advanced machine-learning approaches through large international consortia including PRONIA and ENIGMA. The depth of her expertise is reflected in numerous high-quality articles addressing neurobiological mechanisms, biomarkers, and computational modeling across psychiatric and neurodevelopmental conditions. With a research trajectory enriched by interdisciplinary collaborations and substantial scientific contributions, she exemplifies a researcher whose publication metrics reflect both productivity and sustained scientific relevance in the fields of neuroscience, psychiatry, and data-driven mental health research.

Profile: Orcid 

Featured Publications

Kong, L., Yang, C., Neufang, S., Beyan, O. D., & Boukhers, Z.  EMORL: Ensemble multi-objective reinforcement learning for efficient and flexible LLM fine-tuning. arXiv.

Neuner, L. M., Weyer, C., Kambeitz-Ilankovic, L., Korda, A., Dwyer, D., Antonucci, L. A., Kambeitz, J., Upthegrove, R., Salokangas, R. K. R., Hietala, J., … Neufang, S. Decoding psychosis risk: Neuroanatomical correlates of the NAPLS-2 calculator in the PRONIA cohort. Schizophrenia Bulletin.

Neufang, S., Li, F., Akhrif, A., & Beyan, O. D. Toward a fair, gender-debiased classifier for the diagnosis of attention deficit/hyperactivity disorder: A machine-learning based classification study. BMC Medical Informatics and Decision Making.

Korda, A., Lencer, R., Sprenger, A., Meyhöfer, I., Dannlowski, U., Romer, G., Kambeitz-Ilankovic, L., Kambeitz, J., Lichtenstein, T., Rosen, M., … Neufang, S. Brain texture alterations predict subtle visual perceptual dysfunctions in recent-onset psychosis and clinical high-risk state [Preprint]. Research Square.

Buciuman, M. O., Haas, S. S., Antonucci, L. A., Sarisik, E., Khuntia, A., Lichtenstein, T., Rosen, M., Kambeitz, J., Pantelis, C., Lencer, R., … Neufang, S. From snapshots to stable outcomes: rs-fMRI-based prognosis of functioning in patients with psychosis risk or recent-onset depression. Biological Psychiatry.

Xin Du | AI in Life Science Research | Best Researcher Award

Published on by Life Science

Dr. Xin Du | AI in Life Science Research | Best Researcher Award

University of Cambridge | United Kingdom

Xin Du has demonstrated a strong academic and research profile, reflected in both publication records and citation impact. According to available bibliometric data, she has authored and co-authored over 20 research documents, including peer-reviewed journal articles, conference papers, and manuscripts under review, spanning topics such as deep learning, transfer learning, image processing, and computational biology. Her work has gained notable recognition in the scientific community, with a citation count exceeding 600 across platforms such as Scopus and Google Scholar, which highlights the relevance and influence of her contributions in interdisciplinary research areas. Importantly, her h-index stands at 12, signifying that at least 12 of her publications have each received a minimum of 12 citations, underscoring both consistency and impact in her research output. Many of her works, such as the 2020 Nature Communications Biology article on transfer learning across species and the 2021 Entropy paper on information bottleneck theory, are widely cited and form key references in their fields. The combination of an increasing number of publications, growing citation trends, and a steadily rising h-index reflects her expanding influence, making her a promising researcher with potential for even higher impact in future scientific contributions.

Profile: Google Scholar

Featured Publications

Transfer Learning Across Human Activities Using a Cascade Neural Network Architecture

Transfer learning efficiently maps bone marrow cell types from mouse to human using single-cell RNA sequencing

SemAudio: Semantic-Aware Streaming Communications for Real-Time Audio Transmission