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AI Research Engineer with less than a year in Deep Learning & NLP.
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Assessing your cultural and operational fit
AI/ML enthusiast pursuing a Bachelor of Technology in AI and ML, with a strong foundation in Python, Deep Learning, and Computer Vision. Gained hands-on experience through research internships focusing on NLP, multimodal speech-video processing, and lip synchronization. Adept at leveraging PyTorch, TensorFlow, and large-scale datasets to develop and evaluate AI models, eager to contribute to innovative research and development.
DAV Institute of Engineering & Technology
Bachelor of Technology · Engineering Specializing in AI and ML
August 1, 2023 – June 30, 2027
Indian Institute of Technology Jodhpur (IITJ)
AI/ML Intern
May 1, 2026 – June 30, 2026
Jaipur, Rajasthan, India
Dr. B. R. Ambedkar National Institute of Technology Jalandhar (NITJ)
Research Intern
June 1, 2025 – July 31, 2025
Ludhiana, Punjab, India
Analysis of Non-Projective Dependency Trees in Hindi Language
January 1, 2026 – Present
Analyzed non-projective structures in Hindi dependency trees using Universal Dependencies datasets. Developed Python pipelines to preprocess and analyze Hindi treebanks in CoNLL-U format. Measured hierarchical depth and intervening constituent properties of linguistic phenomena. Replicated methodologies from computational linguistics research papers and evaluated results. Applied dependency parsing and statistical analysis techniques to study Hindi syntax.
Voice2Lip Punjabi: A Framework of Realistic Lip Sync Generation
January 1, 2025 – Present
Built an end-to-end audio-visual alignment and lip-sync pipeline using deep learning. Processed large-scale video datasets including face detection, frame extraction, ROI processing. Designed automated preprocessing pipelines in Python/Linux. Trained and evaluated deep neural networks in PyTorch for visual speech generation. Used LLM-assisted workflows for metadata generation, annotation verification, and dataset validation. Research paper based on this work is currently under preparation for publication.
Cultural Fit Analysis
The candidate's academic background and internship experiences are heavily focused on AI/ML research, particularly in NLP and computer vision. This specialization aligns well with a research-oriented culture. Their involvement in projects leading to potential publications indicates a drive for innovation and contribution to the scientific community. The diversity of projects (lip-sync generation, dependency parsing) shows adaptability and a broad interest within AI, which is beneficial for collaborative research environments.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical and problem-solving skills through their research projects. Their ability to work on complex, multi-modal AI problems and contribute to research papers suggests a proactive and detail-oriented approach. The academic background and internship experiences align well with a research-focused role, indicating a good operational fit for an environment that values continuous learning and scientific rigor.