<Avinash />
Data Scientist · Deep Learning Researcher
<About Me />
Data Scientist and Deep Learning researcher focused on turning difficult datasets into practical systems. I work across time series, quantitative modeling, document intelligence, and ML tooling, with an emphasis on reproducible experiments and production-ready results.
<Publications />
<Work Experience />
❯ Machine Learning Engineer
[Bonsai Lab RIT · Research]
Aug 2025 - Apr 2026
- Architected a modular Self-Supervised Learning (SSL) pipeline in PyTorch, enabling faster representation testing and reducing experiment iteration time by 60%.
- Optimized data loading with pre-fetching and caching, increasing GPU utilization and reducing training time.
- Implemented automated experiment tracking and artifact versioning to ensure reproducibility across distributed training and standardize team-wide metric reporting.
Skills: PyTorch, Self-Supervised Learning, Experiment Tracking
❯ Graduate Researcher
[Rochester Institute of Technology · Part-time]
Oct 2025 - Dec 2025
Rochester, New York, United States · On-site
- Conducted in-depth research on ontologies for deepfake detection under the guidance of Dr. Matthew Wright.
- Collaborated with a multidisciplinary team to explore innovative solutions in cybersecurity.
- Engaged in critical analysis and evaluation of existing deepfake detection methodologies.
- Developed skills in research methodologies, data analysis, and cybersecurity principles.
Skills: Data Analysis
❯ Co-Founder
[ZoAI · Self-employed]
Apr 2024 - Nov 2024
- Co-founded ZoAI and was instrumental in developing an AI-driven call assistant for healthcare clients.
- Built and managed a web application and backend system to streamline communication across 20+ clinics.
- Collaborated with the team to maintain high service uptime and responsiveness to client needs.
- Worked directly with clients to capture requirements and implement feedback-driven service enhancements.
❯ Machine Learning Engineer Intern
[Incribo · Full-time]
Jan 2024 - Jul 2024
Bangalore
- Designed and deployed a fault-tolerant microservices architecture for multi-agent AI systems on Kubernetes and Docker with RabbitMQ for asynchronous messaging.
- Optimized Large Language Model (LLM) serving with gradient checkpointing and dynamic batching, reducing GPU memory usage by 15% and improving inference latency.
- Developed a Go-based CLI to automate container orchestration and deployment workflows, improving consistency across environments.
- Integrated synthetic data generation workflows using CPPN-NEAT neuroevolution, scaling generation rates by 15% for stronger training and validation.
Skills: Kubernetes, Docker, RabbitMQ, Go, LLM Serving
❯ Data Science/ML TA
[Scaler · Part-time]
Nov 2022 - Dec 2023
Bangalore
- Mentored 200+ students through weekly live sessions, small-group breakouts, and personalized office hours, maintaining a 4.8/5 feedback score.
- Designed real-world assessments and automated grading workflows using tools such as scikit-learn and PySpark to improve engagement and outcomes.
Skills: Deep Learning, Data Science, scikit-learn, PySpark