Devakinand Dama
Master's Thesis: Analyzing Prompt Engineering for Data Extraction from Unstructured Data
Experience
Master's Thesis: Analyzing Prompt Engineering for Data Extraction from Unstructured Data
Technical Institute of Rosenheim
- Applied advanced machine learning techniques by developing a multi-strategy prompting framework (zero-shot, few-shot, CoT, instruction tuning) to extract structured data from complex financial and medical datasets, significantly enhancing model reliability and achieving an 18% improvement in F1-score through rigorous evaluation using advanced metrics (ROUGE-L, METEOR, Cosine Similarity).
- Designed scalable structured-output workflows and built automated monitoring pipelines (spaCy, ClearML) for continuous performance tracking, simulating real-world MLOps principles.
- Refined prompt strategies iteratively based on meticulous error analysis to ensure robust, production-ready performance.
Student Assistant - AI Validation & Prompt Engineering
Technical Institute of Rosenheim
- Designed and deployed LLM pipelines (GPT-3.5, GPT-4) for document-to-structured data conversion, leading to improved automation and data accuracy, demonstrating the ability to build algorithmic solutions.
- Engineered end-to-end MLOps pipelines for continuous evaluation and reliable LLM deployment, leveraging ClearML to orchestrate CI/CD-like workflows.
- Conducted bias detection and mitigation strategies, improving cross-domain robustness and fairness by 20%.
- Collaborated with IT and research teams to ensure seamless integration of AI agents into existing systems and client environments.
Student Assistant - Explainable AI for Real-Time Prediction
Technical Institute of Rosenheim
- Designed and deployed an Explainable AI (XAI) framework (SHAP and LIME) for predictive modeling in manufacturing (injection molding), improving transparency and driving higher adoption rates of AI solutions among manufacturing stakeholders.
- Automated data preprocessing to accelerate model readiness and ensure rapid deployment and iteration in production environments, successfully moving prototypes from concept to functional tools.
- Collaborated with domain experts to validate model results, ensuring alignment with real-world operational needs and proving the capability to bridge the gap between technology and business.
- Developed advanced visualization dashboards to effectively communicate AI insights to non-technical, cross-functional teams, supporting organizational decision-making.
Synthetic Data Generation for Optical Localization (Master's Project)
Technical Institute of Rosenheim
- Generated over 50,000 labeled synthetic images using Blender's 3D rendering capabilities for object detection model training, significantly enhancing the generalization of detection algorithms.
- Created automated annotation scripts to generate bounding boxes, rotation angles, and pixel coordinates for every frame, ensuring a consistent and scalable data labeling process.
- Integrated synthetic data into a training pipeline for YOLO and Faster R-CNN models, achieving a 15% improvement in detection accuracy on real-world test datasets, validating the effectiveness of synthetic-to-real transfer learning.
Industries Experience
See where this freelancer has spent most of their professional time. Longer bars indicate deeper hands-on experience, while shorter ones reflect targeted or project-based work.
Experienced in Education (1.5 years), Banking and Finance (0.5 years), Healthcare (0.5 years), and Manufacturing (0.5 years).
Business Areas Experience
The graph below provides a cumulative view of the freelancer's experience across multiple business areas, calculated from completed and active engagements. It highlights the areas where the freelancer has most frequently contributed to planning, execution, and delivery of business outcomes.
Experienced in Research and Development (2 years), Information Technology (1.5 years), and Business Intelligence (1 year).
Summary
Master's graduate and hands-on Al/ML Scientist specializing in designing and deploying production-focused Deep Learning, LLM-powered systems, and scalable data & Al solutions. Proven ability to translate complex data science prototypes into functional tools that drive measurable business impact. Eager to apply strong analytical and technical skills in a client-facing, consultancy environment.
Core expertise: Cutting-edge Machine Learning Techniques, MLOps (ClearML), Prompt Engineering, Explainable AI (XAI), and Cross-functional Collaboration to deliver impactful, trustworthy, and algorithmic solutions.
Skills
- Programming: Python, Sql
- Nlp & Llm Techniques: Langchain, Openai Gpt-3.5/4, Instruction Tuning, Chain-of-thought Prompting, Zero-shot/few-shot Learning, Bias Mitigation, Spacy
- Mlops & Tools: Clearml, Git, Jupyter, Virtual Environments, Aws/gcp/azure (Familiarity With Deployment/api Integration)
- Ml/dl Frameworks: Pytorch, Tensorflow, Scikit-learn, Hugging Face Transformers
- Data Handling: Pandas, Numpy, Spacy, Data Cleaning, Token-efficient Processing, Etl Pipelines
- Evaluation & Xai: Rouge-l, Meteor, Cosine Similarity, Model Fine-tuning, Shap, Lime
- Computer Vision/multimodal Al: Opencv, Yolo, Faster R-cnn, Blender, Synthetic Data Generation
Languages
Education
Technical Institute of Rosenheim
Masters in Engineering Sciences, Mechatronics · Mechatronics · Rosenheim, Germany
SRM Institute of Science and Technology
Bachelor of Technology, Mechanical Engineering · Mechanical Engineering · Chennai, India
Certifications & licenses
Convolutional Neural Networks With TensorFlow
Coursera
Crash Course On Python
Coursera
Machine Learning Specialization
Coursera
Neural Networks And Deep Learning
Coursera
Profile
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