CV
Kaushik Karthikeyan
[linkedin] . [kkaushikk2002@gmail.com] . [+41 772 444 514] . [@ Zürich, Switzerland]
Education
MSc in Computer Science @ Eidgenössische Technische Hochschule Zürich
📆 2024-2027 (expected)
- Current GPA: 5.4/6
- Major: Machine Intelligence | Minor: Data Management Systems
BSc in Computer Science and Engineering @ Delft University of Technology
📆 2021-2024
- Graduated with Honours, Cum Laude
- GPA: 8.94/10
Skills
- Programming Languages
- Python, Java, C++, C#, JavaScript, Scala, SQL, R
- Frameworks
- PyTorch, Spring Boot, React, Flask, Bootstrap, LangChain
- Tools
- Docker, MongoDB, Spark, Pandas, NumPy, Scikit-learn
- Concepts
- Software Engineering, Deep Learning, Large Language Models, Computer Vision, Reinforcement Learning
Work Experience
Full-Stack Software Engineer Intern @ OpenGrant – Remote
📆 April 2023 – September 2023
- Collaborated with a team of four to build a platform leveraging LLMs to accelerate grant writing by 20× at 20% of the cost
- Built advanced web scraping pipelines to extract grant data and PDFs, reducing administrative work by 75%
- Leveraged LLMs to evaluate AI-generated grant applications, improving system reliability
- Developed the front end using ReactJS and Bootstrap, and the back end using Spring Boot and Flask microservices
- Automated application transfer from OpenGrant to Erasmus+ using Selenium, cutting manual effort by 80%
University Projects
SentimentAI: Sentiment Classification of Reviews
📆 May 2025
- Finetuned Qwen3 and SmolLM2 for sentiment classification, and implemented RAG to improve performance by 25%
Human Motion Prediction using Transformers
📆 April 2025
- Implemented a Spatio-Temporal Transformer-based 3D Human Motion Predictor
Off-Policy Reinforcement Learning to Balance a Pole on a Cart
📆 December 2024
- Implemented a Reinforcement Learning (TD3) agent to learn to balance a pole on a cart
Land-use Classification using Bayesian Neural Networks
📆 October 2024
- Implemented a calibrated model using SWAG to classify land use patterns from satellite imagery
Research Experience
Honours Programme Delft @ Interactive Intelligence, Delft University of Technology
📆 November 2022 – July 2024
- Report Title: Personalisation of Social Robots in Child-Robot Interactions [PDF]
- Applied statistical analysis techniques (Benjamini-Hochberg Procedure and Linear Mixed Models) to improve reliability of eye-gaze-based detection of memorable moments in child-robot interactions
- Developed an ACT-R based user simulator to replicate eye gaze behaviour for training RL agents
- Designed and implemented an educational 2D role-playing game in Unity to raise awareness of neurodiversity
Research Project @ Delft University of Technology
📆 May 2024 – July 2024
- Thesis Title: Embodiment and Human-Inspired Socio-Cognitive Mechanisms in Artificial Agents: A Systematic Scoping Review [PDF]
- Conducted a systematic scoping review exploring the role of embodiment and human-inspired socio-cognitive mechanisms in artificial agents