Hi, I’m
Pushkar Bansal
Post Doctoral Research Associate
Salt Lake City,UT
Summary
Ph.D. in Mechanical Engineering with expertise in Machine Learning, Deep Learning, and Computer Vision. I specialize in creating and deploying AI-driven LLMs and CNN models, including transfer learning and YOLO models. Strong background in integrating AI solutions into scientific workflows and collaborating with interdisciplinary teams.
Overview
6
years of professional experience
Work History
University of Utah
Postdoctoral Research Associate
06.2024 - Current
Job overview
- Developed AI pipelines for classification & segmentation in biomedical imaging using PyTorch.
- Implemented OpenCV-based image processing techniques (stitching, noise reduction, deconvolution), manual annotations and augmentation for high-throughput analysis.
- Optimized hyperparameters with Optuna monitored model metrics progress using plotly, generated model metrics using Scikit-learn, tracked and logged model performance using MLflow.
- Integrated pretrained Language Models (LLMs) for inference generation in AI-driven applications directly from Hugging Face platform.
- Created a GUI based application to integrated AI driven components using PyQT
- Created installable and executable applications using PyInstaller and deployed AI based GUI app using FastAPI and Flask
- Knowledge of deploying AI-driven application via MS Azure and Heroku
- Presented research findings at national and international conferences, promoting networking opportunities and attracting potential collaborators.
- Collaborated with multidisciplinary teams for successful project completion and timely results dissemination.
- Expanded collaborative networks by engaging with fellow researchers across various institutions and disciplines.
- Reviewed manuscripts for reputable scientific journals, ensuring the publication of high-quality research articles.
- Mentored undergraduate and graduate students in research skills, fostering a passion for scientific inquiry.
- Streamlined data management practices by utilizing advanced software tools for improved organization and accessibility of information.
- Authored professional scientific papers for publishing in peer-reviewed journals.
University of Illinois, UIC
PhD Graduate Assistant
01.2019 - 05.2024
Job overview
- Conducted locomotor and cardiac activity response investigation in larval zebrafish
- Performed optogenetic monitoring and signal processing analyses of neuron activity using
genetically encoded calcium indicators (GCaMPs) in transgenic zebrafish models - Conducted behavior control studies by optogenetically manipulating neuron activity in a novel transgenic zebrafish line and performed behavioral activity quantification using
- Particle Image Velocimetry (PIV) (Computational Fluid Dynamics
- Performed predictive analysis on in-lab collected brain activity data using machine learning
- Facilitated workshops covering various topics related to professional development for fellow graduate students.
- Managed laboratory operations, ensuring timely completion of experiments and accurate data collection.
- Prepared engaging presentations showcasing research findings to diverse audiences both within academia and beyond.
- Conducted comprehensive literature reviews to inform research direction and ensure relevance within the field.
- Analyzed large datasets using advanced statistical methods, providing valuable insights into complex phenomena.
- Monitored student progress to identify weaknesses and provide recommendations for improvement.
- Documented attendance and completed assignments to maintain full class and student records.
- Evaluated emerging trends within the field, integrating new ideas and perspectives into research projects to maintain relevancy and drive innovation.
Education
University of Illinois At ChicagoChicago, IL
Ph.D. from Mechanical Engineering
05.2001
University of Illinois At ChicagoChicago, IL
Master of Science from Chemical Engineering
05.2001
Lovely Professional UniversityIndia
Bachelor of Science from Biotechnology
05.2001
Skills
Neural Network Architectures: Transformers, CNNs, VAEs, Semantic and Instance Segmentation, YOLO, GAN, Diffusion Models, NLP, LLM APIs
Programming & Tools: Python, TensorFlow, PyTorch, OpenCV, Scikit-learn, NumPy, Pandas, PyQt, Flask
MLOps & Optimization: Optuna, MLflow, Model Deployment, ONNX
Data Processing: Image Denoising, Segmentation, Feature Extraction, Annotation, Augmentation
AI Tools and Sources: Roboflow, Hugging Face, MLflow, FastAPI, MS Azure, Ultralytics
Timeline
Postdoctoral Research Associate
University of Utah
06.2024 - Current
PhD Graduate Assistant
University of Illinois, UIC
01.2019 - 05.2024
University of Illinois At Chicago
Ph.D. from Mechanical Engineering
05.2001
University of Illinois At Chicago
Master of Science from Chemical Engineering
05.2001
Lovely Professional University
Bachelor of Science from Biotechnology
05.2001