Hi, I'm Carl. I build AI that doctors can check.

• Shipped multiple AI systems into production, spanning candidate matching, team planning and assistants inside the messaging channels people already use, each returning output with the reasoning attached.
• Built the agent infrastructure for a client deployment and the evaluation framework behind it, with test sets and scoring so output quality stays measurable after release.
• Co-delivered a £15,000+ recruitment-sector build, integrated with the workflow software their consultants already use.

• Translating the PhD tumor-board decision-support work toward clinical deployment, with privacy-preserving infrastructure that keeps patient data within the hospital perimeter.
• Dresden Exists LifeTech incubator. Y Combinator Spring 2026 interview.

• Consumer-facing RAG reference for natural medicine, with each entry grounded in a Cochrane review, EMA HMPC monograph, EFSA authorised health claim or major-journal RCT.
• Personalised pre-generation checks for drug interactions, contraindications and allergies, with severity-tiered alerts and auditable event records.

In collaboration with Andrea Bauer.

• Benchmarked seven foundation-model encoders on 527 fresh-frozen pancreatic whole-slide images, achieving 96.8% balanced accuracy on the 475-slide PDAC/pancreatitis/normal subset in patient-level cross-validation.
• Evaluated calibrated abstention on the five-class differential: 95.1% accuracy at 77% coverage (confidence ≥0.90). External PDAC-vs-rest detection achieved 0.936 AUROC on 257 TCGA-PAAD frozen slides.
• Evaluated pathology-transcriptomics fusion on 303 slides from 301 patients. Rare cystic and neuroendocrine tumours received greater genomic weighting across four random seeds.

Supervised by Tom Hähnel.

• Developed calibrated Parkinson’s progression-subtype prediction from 17 routine scores in 409 PPMI patients, using per-patient OLS slopes and intercepts.
• Compared Random Forest, XGBoost and logistic regression with missing-score handling and class-conditional conformal abstention.
• Assessed fixed-model predictions against motor, cognitive and biomarker outcomes in the later PPMI 2.0 cohort. Independent subtype-level validation remains outstanding.

• Benchmarked Hyena-DNA, DNABERT-2 and NucleotideTransformer-v2 across 19 TCGA cancer types (7,674 patients). Hyena-DNA embeddings with a residual feed-forward network achieved 0.94 mean-class AUROC at 54.96% overall accuracy.
• Improved NucleotideTransformer-v2 accuracy by almost 10% with mutation-centred windows, approaching DNABERT-2. Results suggested greater sequence-shift sensitivity with k-mer than byte-pair tokenisation.

Clinical LLM evaluation harness for citation verification, unsupported confidence and abstention, with human-validated LLM judging, DeepEval integration and reproducible audit reports.

Platform where medical students find doctoral positions and read verified reviews of supervision, live with 135 positions across 28 research groups. Ratings are structurally separated from paid listings so promotion cannot influence them, named scores stay hidden until four independent verified reviews corroborate them, and verification documents are discarded after checking.

Live Streamlit app with calibrated predictions, abstention, SHAP and counterfactual explanations. Single-patient and batch workflows, plus reproducible PPMI analysis respecting the data-use agreement. Demo: parkinson-subtype-predictor.onrender.com.

Heart-failure prototype combining explainable deterioration risk with guideline-based GDMT titration. XGBoost/LightGBM on 98 trajectory features. Zigong evaluation with patient-level splits and bootstrap confidence intervals.

First-author throughout. Four manuscripts complete, in co-author review.

• PROMPT. a deterministic guideline tree achieves similar automated guideline-conformance scores to multi-agent LLMs for prostate cancer tumour-board decisions. Pöhl, Sondermann, Kather, Mehralivand.
• Pan-pancreatic diagnosis on fresh-frozen sections: a foundation-model characterization of the open multi-class differential, calibrated abstention, and class-conditional multimodality. Pöhl et al. DKFZ Heidelberg + University Hospital Heidelberg.
• A foundation model reads a molecularly anchored inflammatory-infiltrate axis from fresh-frozen pancreatic histology. Pöhl et al. University Hospital Heidelberg + DKFZ Heidelberg + University of Verona.
• A Calibrated, Abstaining Prediction Model for Parkinson’s Disease Progression Subtypes from a Variable Set of Routine Clinical Scores. Pöhl, Falkenburger, Hähnel. TU Dresden. Basis of the Dr. med. thesis.

• Nov 2026Poster (accepted), ESMO AI & Digital Oncology Congress, Berlin: multi-agent decision support for the prostate-cancer tumor board.
• Sep 2026Invited lab meeting, Dewey Lab, University of Cambridge: “Agreeing with the tumor board is not the same as being right.”
• Jul 2026Invited talk, DKFZ Heidelberg: prostate-cancer decision support.
• Jun 2026Invited talk, Urology, University Hospital Basel: guideline-grounded AI.
• May 2026Invited lab meeting, Krauthammer Lab, University of Zurich: clinical LLMs.
• Mar 2026Poster, ELSA TrustworthyAI4Health: prostate-cancer tumor boards.
• Oct 2024Invited talk, Connectome Fall Symposium: DNA-language models.

• Co-developed the kick-off strategy for a client's market exit and prepared execution workshops with global stakeholders.

• Built the division's first data-driven targeting model for sales-activity planning, with no in-house data science function to build on, replacing gut-feel prioritisation. A retrospective backtest indicated savings of up to ¥120M. Presented findings to the head of the Asia-Pacific division.

• Dr. rer. medic. (PhD equivalent), AI in Medicine: multi-agent decision support for the prostate-cancer tumor board.
• Dr. med. (medical doctorate, research thesis): calibrated progression-subtype prediction in Parkinson’s disease.

• Second national medical examination (M2) passed 2025, good (2.0), ~top 20% nationally. Final examination December 2026.
• At TU Dresden since 10/2022, after pre-clinical studies at Semmelweis University, Budapest (09/2020–07/2022). Physiology and Biochemistry examinations at the top grade.
• International clinical rotations across six settings: cardiology (Buenos Aires) · surgery + dermatology (Windhoek, Namibia) · visceral surgery + neurosurgery (University Hospital Heidelberg) · gastroenterology + haematology/oncology (University Hospital Zurich) · radiology (TUM University Hospital, Munich) · general practice (southern Germany).

• RWTH Aachen (10/2018–11/2024): final grade good (2.0), completed part-time alongside medicine. Mathematics very good (1.3), minor in Business Administration.
• EPFL Lausanne (09/2019–03/2020): exchange semester in Computer Science, SEMP scholarship.
• HKUST Hong Kong (09/2017–10/2018): Dual Degree Program in Technology & Management (Computer Science & Business). GPA 3.74/4.0, Dean's List both semesters.

• McKinsey Capstone Programme, member (2020 – present).
• Dresden Exists LifeTech Incubator Program, incubator place for ConcordAInce (2025).
• Porsche IT Scholarship, competitive technology scholarship (2020–2021).

• German, Spanish and English (native) · French (fluent) · Italian (conversational) · Japanese and Mandarin (basic).
• Raised across Ecuador, Mexico, Spain, Germany, Japan and Norway.
• Concert piano performance · chess · alpine skiing · sailing.