AI Researcher & Engineer

Rohit PatelMTech in AI

IIT Jodhpur

Exploring the frontiers of Artificial Intelligence through rigorous research, innovation, and a passion for pushing the boundaries of machine learning. Aspiring PhD candidate dedicated to advancing AI for real-world impact.

About Me

Bridging Theory & Practice in AI

A passionate AI researcher combining rigorous academic training with hands-on experience in machine learning, deep learning, and emerging AI technologies.

Academic Excellence

MTech in Artificial Intelligence from IIT Jodhpur, one of India's premier institutes

Future Goals

Pursuing PhD opportunities to contribute to cutting-edge AI research

Innovation Focus

Passionate about solving real-world problems through AI and machine learning

My Journey in AI

My journey into Artificial Intelligence began with a fascination for how machines can learn, reason, and make decisions. At IIT Jodhpur, I've had the privilege of diving deep into the mathematical foundations, algorithmic innovations, and practical applications that define modern AI.

Through my MTech program, I've explored diverse areas including deep learning, natural language processing, computer vision, reinforcement learning, and AI ethics. Each course, project, and research paper has strengthened my conviction that AI can be a powerful force for positive change in society.

My technical background spans cloud computing, DevOps, and system architecture, giving me a unique perspective on deploying AI solutions at scale. I'm particularly interested in the intersection of AI research and practical engineering, where innovative algorithms meet real-world constraints.

Research Interests

Areas of Exploration

Focusing on cutting-edge AI domains where innovation meets impact, with a commitment to advancing both theoretical understanding and practical applications.

Deep Learning

Neural architecture design, optimization techniques, and training methodologies for complex AI systems

Natural Language Processing

Large language models, transformers, multilingual NLP, and conversational AI systems

Computer Vision

Object detection, image segmentation, visual recognition, and multimodal learning

Reinforcement Learning

Policy optimization, multi-agent systems, and decision-making under uncertainty

AI Systems & MLOps

Scalable ML infrastructure, model deployment, monitoring, and production AI systems

AI Safety & Ethics

Responsible AI, fairness in ML, interpretability, and ethical implications of AI systems

PhD Research Vision

My PhD aspirations are driven by a desire to contribute meaningfully to the AI research community. I'm particularly interested in exploring problems at the intersection of multiple domains, where innovative solutions can have far-reaching impact.

I envision research that not only advances the state-of-the-art but also addresses practical challenges in deploying AI systems responsibly. This includes work on model efficiency, interpretability, fairness, and robustness—ensuring AI technologies can be trusted and deployed at scale.

Through collaboration with leading researchers and institutions, I aim to push the boundaries of what's possible in AI while maintaining a strong ethical foundation and commitment to societal benefit.

Learning Journey

MTech Key Learnings

A comprehensive journey through AI, from foundational theory to cutting-edge research and real-world implementation at IIT Jodhpur.

Theoretical Foundations

  • Advanced machine learning algorithms and statistical learning theory
  • Deep neural networks: CNNs, RNNs, Transformers, and attention mechanisms
  • Optimization techniques: SGD, Adam, learning rate scheduling, and regularization
  • Probabilistic graphical models and Bayesian inference
  • Information theory and its applications in machine learning

Technical Skills

  • PyTorch and TensorFlow for building and training complex neural networks
  • Large-scale data processing with distributed computing frameworks
  • MLOps: Model versioning, experiment tracking, and production deployment
  • Cloud AI platforms: AWS SageMaker, GCP AI Platform, Azure ML
  • Research tools: Jupyter, Weights & Biases, MLflow, and collaborative notebooks

Research & Innovation

  • Conducting literature reviews and staying current with latest AI papers
  • Experimental design and rigorous methodology for ML research
  • Writing technical reports and presenting research findings
  • Reproducing and improving upon state-of-the-art models
  • Open-source contribution and knowledge sharing in the AI community

Practical Applications

  • End-to-end ML project lifecycle from ideation to deployment
  • Real-world dataset handling: cleaning, augmentation, and feature engineering
  • Model evaluation: cross-validation, A/B testing, and performance metrics
  • Collaborative development using Git, Docker, and CI/CD pipelines
  • Ethical AI: bias detection, fairness metrics, and responsible deployment
15+
Advanced AI Courses
10+
Research Projects
100+
Research Papers Read
Technical Expertise

Skills & Technologies

A comprehensive toolkit spanning AI research, software engineering, and production-grade system development.

Programming & Frameworks

Python95%
PyTorch90%
TensorFlow85%
Scikit-learn90%
C++75%

AI & Machine Learning

Deep Learning92%
NLP88%
Computer Vision85%
Reinforcement Learning80%
MLOps82%

Data & Analytics

Data Processing90%
SQL & NoSQL85%
Data Visualization80%
Big Data Tools75%
Statistical Analysis88%

Cloud & Infrastructure

AWS85%
Google Cloud80%
Docker & Kubernetes82%
Linux Systems90%
Azure75%

Development Tools

Git & GitHub90%
CI/CD80%
Jupyter Notebooks95%
VS Code90%
Weights & Biases85%

Security & Ethics

Network Security85%
Ethical Hacking80%
AI Ethics88%
Model Security82%
Privacy-Preserving ML78%

Additional Competencies

Research MethodologyTechnical WritingExperiment DesignModel OptimizationTransfer LearningHyperparameter TuningData AugmentationModel InterpretabilityDistributed TrainingReal-time InferenceModel CompressionAutoMLFederated LearningEdge AIAPI DevelopmentSystem Architecture
Academic Work

Publications & Projects

Research contributions and academic projects completed during my MTech journey at IIT Jodhpur.

Advanced Techniques in Deep Neural Network Optimization

MTech Thesis, IIT Jodhpur2024Thesis

Comprehensive study on novel optimization techniques for training deep neural networks efficiently.

Scalable Machine Learning Systems for Production

Technical Report2024Report

Analysis of MLOps practices and deployment strategies for large-scale AI systems.

Natural Language Processing with Transformers

Course Project2023Project

Implementation and evaluation of transformer architectures for multilingual NLP tasks.

Achievements

  • Published research work during MTech program
  • Contributed to open-source AI projects
  • Presented at academic conferences and seminars
  • Mentored junior students in AI coursework
  • Active participant in AI research community

Research Interests

My research focuses on developing efficient, scalable, and responsible AI systems. I'm particularly interested in bridging the gap between theoretical advances and practical deployment challenges.

Looking forward to pursuing a PhD where I can contribute to cutting-edge research while addressing real-world problems through innovative AI solutions.

Get in Touch

Let's Connect

Interested in collaboration, research opportunities, or just want to discuss AI? I'd love to hear from you!

Open to Opportunities

Currently seeking PhD positions in Artificial Intelligence and Machine Learning. I'm particularly interested in programs that emphasize both theoretical research and practical impact.

PhD OpportunitiesResearch CollaborationsAI ConsultingSpeaking Engagements