AI Engineer with less than a year in multimodal emotion recognition, robotics, and natural language
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Assessing your cultural and operational fit
Engineered real-time multimodal emotion recognition systems, developed AI-assisted autonomous robots for face recognition and navigation, and created mental wellness chatbots using modern LLM APIs. Possessing strong skills in PyTorch, OpenCV, and FastAPI, and experienced in hardware-software integration and backend API development. Currently pursuing an M.Tech in Artificial Intelligence.
Banasthali Vidyapith
M.Tech · Artificial Intelligence
August 1, 2025 – Present
Banasthali Vidyapith
B.Tech · Computer Science Engineering
August 1, 2021 – June 30, 2025
Bhabha Atomic Research Centre
Research Intern
July 1, 2024 – November 1, 2024
India
Multimodal Emotion Recognition System
June 24, 2026 – Present
Engineered a real-time multimodal emotion recognition pipeline integrating facial, speech, and text modalities using ResNet18, LSTM, and DistilBERT models trained on FER2013, RAVDESS, and GoEmotions datasets. Designed confidence-aware late fusion mechanism combining modality-level probability distributions with adaptive weight boosting for high-confidence predictions. Built FastAPI inference backend supporting webcam/image, audio, and text inputs with modular training and inference pipelines. Achieved 82% text classification accuracy using DistilBERT and 61% multimodal visual/audio classification accuracy under real-time inference constraints.
View ProjectAI-Based Autonomous Robot for Face Recognition & Navigation
June 24, 2026 – Present
Developed an AI-assisted autonomous robotic system for real-time face recognition and navigation using OpenCV, Raspberry Pi, and Arduino. Implemented hardware-software communication pipelines for responsive motion control and environment-aware robotic behavior. Worked on edge-based computer vision and navigation workflows during research internship at Bhabha Atomic Research Centre.
View ProjectManoSamvada – AI Mental Wellness Chatbot
June 24, 2026 – Present
Developed an AI-powered mental wellness chatbot using Flask, MySQL, and Groq LLM APIs for emotion-aware conversational support. Designed backend APIs for authentication, session management, reporting workflows, and emotional analytics dashboards. Implemented crisis keyword detection and conversational tracking pipelines with modular chatbot service architecture.
View ProjectCertificate
Bhabha Atomic Research Centre
November 1, 2024 – Present
Cultural Fit Analysis
The candidate's projects show a strong interest in AI applications, including emotion recognition, robotics, and mental wellness chatbots, which aligns well with an AI Engineer role. The diversity of projects and technologies used (PyTorch, Flask, OpenCV, NLP, DistilBERT, Groq API, Raspberry Pi, Arduino) indicates a broad technical curiosity and willingness to learn. However, the lack of professional experience beyond a single internship and the focus on personal projects might suggest a need for more exposure to collaborative, large-scale development environments.
Soft Skills & Operational Fit
The candidate demonstrates initiative and problem-solving skills through personal projects. The project descriptions indicate an ability to design and implement complex systems. However, without specific assessment data on communication, logical reasoning, or teamwork, it is difficult to fully assess soft skills and operational fit.