Arush Jasuja

CTO

New York, New York, United States3 yrs 2 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Delivered AI solutions generating $20M+ in annual value.
Published researcher in cognitive impairment and emotion recognition.
Expertise in end-to-end ML pipelines and computer vision systems.

Stackforce AI infers this person is a Machine Learning and AI specialist with a strong focus on Healthcare and Manufacturing sectors.

Contact

arushjasuja@gmail.com LinkedIn

Skills

Core Skills

Machine LearningComputer VisionDeep Learning

Other Skills

AWSC/C++DockerGCPKubernetesNatural Language Processing (NLP)OpenCVPredictive AnalyticsPyTorchPythonPython (Programming Language)SQLScikit-learnTensorFlow

About

AI/ML Engineer with 3+ years of experience driving innovation in manufacturing and healthcare through cutting-edge machine learning solutions. Proven track record of delivering high-impact projects, including AI-driven manufacturing optimization systems generating $20M+ in annual value and healthcare AI solutions serving 50+ facilities. My expertise spans developing end-to-end ML pipelines, computer vision systems, and distributed computing solutions using TensorFlow, PyTorch, and MLOps practices. Published researcher in prestigious journals including Springer Nature, with contributions in cognitive impairment diagnosis, emotion recognition, and feature selection algorithms. Currently pursuing MS in Computer Science at NYU's Courant Institute, focused on advancing my expertise in AI/ML, computer vision, and natural language processing. Passionate about leveraging AI to solve complex real-world challenges and drive meaningful business impact. Core competencies: ML/DL: TensorFlow, PyTorch, OpenCV, Scikit-learn MLOps & Cloud: AWS, GCP, Docker, Kubernetes Programming: Python, C/C++, SQL Leadership: Led cross-functional teams of 5+ engineers Open to connecting with fellow AI enthusiasts, researchers, and industry professionals to explore collaborative opportunities in pushing the boundaries of AI innovation.

Experience

Ripik.ai

Lead AI/ML Software Engineering

Aug 2022 – Jul 2024 · 1 yr 11 mos · California, United States

At Ripik Technology, I spearheaded the development of AI solutions that generated $20M+ in annual production value across manufacturing operations. Notable achievements include designing a production line optimizer that increased efficiency by 20%, implementing a computer vision system that improved quality control by 25%, and leading a team that developed an AI-powered steel plate cooling optimizer, reducing quality rejects by 15%.
● Developed AI-driven tools with cross-functional team for the manufacturing sector, enhancing production efficiency, product quality, and reducing environmental impact. Generating $20M+ in annual production value across 3000+ factory workers.
● Production Line Optimizer: Designed an ML optimizer with UI/UX designer that increased production efficiency by 20% and reduced planning time by 30%, aligning daily plans with market demand and operational constraints. Driving $2M annual savings across 500+ production line operators.
● Sinter Sizing Model: Partnered with product manager to build a Computer Vision system for real-time sinter particle classification, improving quality control by 25% and operational efficiency by 18%. Impacting $4M in annual production for 300+ quality control staff.
● Steel Plate Cooling Optimizer: Lead a team of 5 to create an AI tool that reduced quality rejects by 15% and improved tensile strength by 10%, enhancing steel plate cooling uniformity for MULPIC machine. Saving $15M annually in defect costs and serving 200+ cooling line operators.
● Additional Projects: Blast Furnace Optimization, Glass Furnace Fuel/Air Recommender and Monkey Detection System, Sales Prediction Tool, Burden Mix Optimizer. Portfolio of optimization tools serving 1000+ users across multiple facilities, delivering combined annual value of $15M+ through improved efficiency and reduced waste.

Predictive AnalyticsComputer VisionMachine LearningDeep LearningNatural Language Processing (NLP)

Sequoia insilico private ltd

Deep Learning Engineer

May 2021 – Aug 2022 · 1 yr 3 mos · New Delhi, Delhi, India · On-site

At Sequoia Insilico, I engineered healthcare-focused deep learning solutions, including a multimodal depression detection system and COVID-19 diagnostic tools, serving 50+ healthcare facilities. My research work spans dimension reduction techniques for cognitive impairment diagnosis, emotion recognition systems, and genetic algorithms for feature selection, published in respected journals.
● Designed and deployed Deep Learning models in the medical industry, improving diagnostic accuracy and advancing Predictive Analytics capabilities. Serving 50+ healthcare facilities and 500+ healthcare professionals
● Depression Detection System: Designed a multimodal AI model that combined spectrograms, audio transcripts, and hybrid approaches to detect signs of depression from audio and video data, achieving an accuracy of 85%. Supporting 100+ mental health professionals and potentially saving $2M+ in early intervention costs.
● COVID-19 Diagnosis: Built a Deep Learning classifier for COVID-19 detection using chest X-ray scans with 90% accuracy for real-time diagnostics. Deployed across 30+ hospitals, serving 200+ radiologists and reducing diagnostic time worth $1.5M annually
● Secondary Structure Prediction: Implemented an LSTM-based sequence-to-sequence Deep Learning model to predict SS3 and SS8 secondary structures from amino acid sequences, achieving 78% accuracy in predictive performance. Supporting 50+ research institutions and accelerating drug development processes valued at $3M+ annually.

Deep LearningComputer VisionMachine LearningNatural Language Processing (NLP)Python (Programming Language)

National informatics centre, govt of india

Machine Learning Engineer

Jun 2019 – Aug 2019 · 2 mos · New Delhi, Delhi, India

Design a prediction model for subsidy approval under Pradhan Mantri Awas Yojana. Worked on the development of semi-supervised prediction model in Rural Housing Division,deployed the project with an online interface that greatly enhances user experience