I build intelligent systems that bridge hardware and software. Currently focused on reducing hallucinations in task-oriented dialogue via preference-based optimisation, industrial IoT automation, and applied ML for time-series problems.
Currently available for new roles: Master's thesis, internships, or workstudent positions in ML/DL. Based in Germany, open to relocation.
- 🕸️ hn-knowledge-graph: Public-facing knowledge graph of the HN AI/ML landscape. Typed NER via local llama3.1:8b (Ollama + LangChain) over ~240 stories, alias normalisation, NetworkX co-mention graph (172 entity nodes / 244 edges after pruning), Louvain communities (top-8 coloured), cytoscape.js viewer at anjanamb.github.io/hn-knowledge-graph. Click any entity to jump to its source HN threads.
- 🤖 hn-ml-trends: LangGraph agent for Hacker News AI/ML trend tracking. Silver labels via qwen2.5:14b (Ollama) + Claude spot-check for the ceiling estimate; TF-IDF baseline 43.3% vs llama3.1:8b classifier 62.7% test accuracy; sentence-transformer clustering; conditional drill-down node fires on real category spikes (research +13.3 pp this window). All eight notebooks executed with baked-in outputs.
- ⚡ electricity-demand-kalman: Classical state-space walkthrough on PJME hourly load. Hand-written Kalman filter + Ornstein-Uhlenbeck residual fit + LightGBM overlay, stacked over a per-month additive decomposition. Full-stack MAPE 0.59% vs persistence 3.27% on the held-out 2016-Q4 test window.
- 🧠 Lab Rotation 2 @ HHU (submitted August 2026): DPO for hallucination reduction on task-oriented dialogue NLG. LR1-labelled preferences beat gold/random baselines by 13-24x on faithfulness at matched hyperparameters. E2E transfer arm cuts DK-NLI unfaithfulness by 45% relative on top of a reproduced DataTuner SFT.
- 🔧 sensor-anomaly-detection: Onset-of-degradation detection on NASA C-MAPSS FD004. Isolation Forest + DBSCAN over 20 hypothesis-driven features across seven executed notebooks; 99.5% cycle-level agreement between the two detectors.
- 🏭 RIF Institut, Dortmund (Jul 2025 - Jun 2026): Containerised brewery process control. PLC over MQTT, time-series replay via FastAPI + InfluxDB, Streamlit ops dashboards.
- 🎓 Student Teaching Assistant, HHU Düsseldorf (Oct 2025 - Apr 2026): Evaluated and graded deep-learning course assignments; supported exam preparation, proctoring, and student guidance.
| 🕸️ hn-knowledge-graph | Interactive knowledge graph of the Hacker News AI/ML landscape, live at anjanamb.github.io/hn-knowledge-graph. Typed NER (org / model / tool / concept) via local llama3.1:8b (Ollama + LangChain) over ~240 stories, alias normalisation, NetworkX co-mention graph, Louvain community detection with a top-8 palette, cytoscape.js viewer with search + click-to-see-stories sidebar. Five executed notebooks. |
| 🤖 hn-ml-trends | LangGraph agent that ingests Hacker News AI/ML stories, classifies them into 7 subtopics, embeds and clusters, and produces a trend report with a conditional drill-down node. Silver labels via qwen2.5:14b (Ollama) with Claude spot-check; TF-IDF baseline 43.3% vs local llama3.1:8b classifier 62.7% test accuracy. LangChain + LangGraph + sentence-transformers, entirely offline on Ollama. |
| ⚡ electricity-demand-kalman | Classical state-space forecast on PJME hourly load: hand-written Kalman filter + Ornstein-Uhlenbeck residual + LightGBM overlay, stacked over a per-month additive decomposition. Full-stack MAPE 0.59% vs persistence 3.27% on the held-out 2016-Q4 test window (about 5x better). Seven executed Jupyter notebooks. |
| 🧠 hallucination-preference-lr2 (private) | Lab Rotation 2, HHU Düsseldorf. DPO on task-oriented dialogue NLG. LR1-labelled preferences beat gold/random baselines by 13-24x on faithfulness. E2E transfer arm reproduces DataTuner SFT then applies DPO on top: DK-NLI unfaithfulness 3.38% vs 6.12% (-45% rel). Submitted Aug 2026. |
| 🔧 sensor-anomaly-detection | Onset-of-degradation detection on NASA C-MAPSS FD004, done as a learning-first walkthrough. Seven executed Jupyter notebooks; Isolation Forest (flags all 249 engines, median 210-cycle lead time) + DBSCAN (strict late confirmer, 99.5% agreement with IF on flagged cycles) over 20 hypothesis-driven features. |
| 🔬 Digital-IC-NN-Duplication | NN-based digital twin for sequential circuits. Published at IEEE 2023. |
| 🖼️ image-downsampling-processor | Verilog low-pass + downsample-by-2 processor, validated against Python reference via SSD. |
ML / Deep Learning
Languages
Data & Infrastructure
IoT · Embedded · Networking
Cloud · Tools
💡 Curious devs: poke around the portfolio, toggle ▮ terminal mode and try help. There are easter eggs.



