Curriculum Vitae

• Working at the interface of drug discovery, medical data science and generative AI, focusing on large language models, graph-based methods and large-scale analytics for biomedical and chemical data.
• Contributing as a data scientist to large European and German-funded consortia in translational medicine and pharmacology, including the Innovative Health Initiative project SYNTHIA and the EU project Proxidrugs.
• Designing and implementing data and AI pipelines for early-stage drug discovery, including integration of knowledge graphs, classical machine learning and modern LLM-based approaches.

• Assisted in research activities on the use of large language models and neural networks on knowledge graphs for drug discovery.
• Supported development of retrieval-augmented generation (RAG) and AI pipelines for small-molecule and target discovery.
• Contributed to the data preparation, evaluation and documentation of AI workflows within EU and German-funded research projects.

• LLM training and fine-tuning (Mistral, Llama) for client-specific business use cases.
• Machine learning optimisation and integration for analytics-driven decision-making.
• Cloud services and infrastructure management (Microsoft Azure, Google Cloud Platform, AWS, Terraform).
• MLOps and LLMOps: monitoring and deployment of ML and LLM models (Azure AutoML, Azure OpenAI Service).
• Containerisation and orchestration using Docker and Kubernetes.

• Docker and Kubernetes Cluster Management for Service Deployment and Scaling
• Web and RESTful API Development (Python Tornado, Flask, Django)
• AI Model Integration and Deployment (Diffusion Models, GPTs) with Kubernetes and Containerization
• Rigorous Testing and Monitoring for AI Model Reliability and High Availability

• Data Analysis & Expressive and Insights driven Data Visualizations using Pandas & Matplotlib
• Training and Testing Machine Learning & Deep Learning Models using Scikit-Learn, XGBoost, LightGBM, Keras, TensorFlow
• Development of Fulfillment Based Healthcare Chatbot with RASA Framework
• API Development & Deployment with FastAPI and Flask Frameworks
• Development of Test Driven ML UI with Streamlit
• Deployment, Regular Update & Monitoring of ML Models on GCP & Amazon EC2 Platforms

• Comment classification on Twitter Livestream data with Word Vector Embeddings (word2vec, BERT)
• Development of Interactive web-app for real-time toxic words classification from sentences
• Deployment and monitoring of ML across Google Cloud Platform

• Data Visualization and Analysis using Tableau and PowerBI
• Data Curation, EDA, Analysis and Insights generation on Plant Disease Data with SVM, PCA, Bagging (Ensemble Learning models) and Boosting (XGBoost, CatBoost & LightGBM)

• Specialization in Generative AI, LLMOps, Bioinformatics, and Cheminformatics
• Master Thesis: "Leveraging LLMs for Enhanced Drug Discovery: Extracting Insights from Patents and Scientific Documents"
  Grade: 1.0

• Focus on AI/ML applications and software systems
• Minor in Data Science
• Bachelors Thesis: "Sahayak: An Interactive AI-Powered Web Healthcare System"

A sophisticated implementation of RASA Conversational AI on a HealthCare Bot integrated with a Web and Android Software written in Python, Java and JavaScript.