Dr. Kashif is a distinguished AI Research Scientist with over 8 years of specialized experience in natural language processing and large language model development. Currently serving as Senior AI Research Scientist at Axon, he has previously held key research positions at Hippocratic AI and completed postdoctoral research at Cedars-Sinai Medical Center. His expertise spans the full spectrum of AI development, from conducting large-scale pretraining of language models like the ALAYA-7B series to developing domain-specific applications in finance and healthcare. With deep technical knowledge in BERT, GPT, and transformer architectures, he has successfully led multi-node distributed training initiatives and pioneered innovative approaches in semantic analysis, knowledge graph construction, and multimodal AI systems across diverse international markets.
Dr. Umar is a distinguished AI Research Scientist with over 8 years of specialized experience in computer vision, generative AI, and multimodal machine learning. Currently serving as AI Research Scientist II at Axon, he has previously held key research positions at Meta as a PhD Intern working on LLAMA3 applications and multimodal capabilities, and at Samsung Research America developing advanced 3D AR/VR algorithms and diffusion-based video generation systems. His expertise spans cutting-edge AI domains including action recognition, adversarial robustness, continual learning, and anomaly detection, with deep technical knowledge in PyTorch, NeRF, Gaussian Splatting, and transformer architectures. With extensive research experience at UCF’s Center for Research in Computer Vision and internships at leading tech companies including Microsoft, he has successfully bridged theoretical computer vision research with practical industry applications in next-generation mobile and AR/VR technologies.
Dr Adeel Zafar is a dedicated Computer Science researcher with over 5 years of specialized experience in computer vision, deep learning, and scientific visualization. Currently pursuing his Ph.D. at the University of Houston while serving as a Research Assistant, he focuses on segmentation and extraction of physical structures from large-scale turbulent flow simulations using advanced computer graphics and deep learning techniques. His professional experience includes developing image algorithms at Mengbaby Inc. using PyTorch, Keras, and TensorFlow for object detection and image segmentation applications. With a Master’s degree from Shanghai Jiao Tong University where he received the Shanghai Government Scholarship, his expertise spans fluid flow visualization, computer vision systems, and data analytics. Having worked across diverse technical domains from banking database systems at Techlogix to data visualization at Teradata, he brings a multidisciplinary approach to solving complex computational problems in scientific computing and machine learning.
Dr Safa Nasir is an accomplished Senior Data Engineer with over 7 years of specialized experience in financial systems, regulatory reporting, and machine learning research. Currently serving as Senior Data Engineer at Citi, she builds robust data pipelines for critical CCAR regulatory reporting processes and ensures end-to-end compliance across Banking Book and Wholesale portfolios. Her expertise spans the full data engineering lifecycle, from developing cutting-edge Statistical & Regulatory Reporting solutions at Hubio Technology to optimizing equity reporting systems at Morgan Stanley, where she reduced SLA completion times by 50%. With a strong research background from Shanghai Jiao Tong University focusing on deepfakes and unsupervised video retargeting, she combines advanced machine learning knowledge with practical financial engineering skills. Her technical proficiency includes Python, SQL, AWS cloud services, and various database systems, enabling her to deliver scalable data solutions that drive key business decisions in high-stakes financial environments.
Experienced Data Scientist and AI Consultant with over 8 years of expertise in developing intelligent systems using Generative AI, Machine Learning, and NLP technologies. Currently serving as Principal Consultant-Data Science at Systems Limited, specializing in building AI-powered chatbots, customer support solutions, and healthcare applications using RAG architecture and Azure AI Stack. Proven track record of architecting end-to-end ML pipelines, implementing telecom customer support systems, and developing predictive models for diverse industries including healthcare, telecommunications, and government sectors. Strong technical proficiency in Python, ChatGPT, Azure cloud services, and modern AI frameworks, with demonstrated leadership experience in mentoring data science teams. Successfully delivered production-ready solutions ranging from virtual doctors and misinformation detection systems to customer engagement models and meeting automation tools.
Data Scientist and Software Engineer with diverse experience spanning blockchain analytics, academic research, and full-stack development across multiple international locations including China and the United States. Currently serving as Research Assistant at University of Alabama, with previous roles as Graduate Research and Teaching Assistant at University of Nevada, Reno, demonstrating strong academic foundation in data science methodologies. Specialized expertise in blockchain technology and cryptocurrency analytics, having developed sophisticated trading bots, smart contracts, and anti-money laundering detection systems during tenure as Junior Data Scientist at blockdynamics in Shanghai. Comprehensive technical proficiency encompasses Python data science stack (Keras, sklearn), cloud platforms (Google Cloud, AWS), web frameworks (Flask, Django), and database technologies (SQL, NoSQL, BigQuery). Additional experience includes full-stack development roles at Pixarsart and MeeCube, Java development internships, and teaching positions, showcasing adaptability across programming languages and development environments. Strong foundation in both theoretical research and practical application development, with proven ability to deliver end-to-end solutions from algorithm design to deployment.
A Senior Solutions Architect specializing in cloud-native AI systems, edge computing, and scalable machine learning architectures. Experienced in designing distributed AI solutions across multi-cloud environments, implementing edge AI deployments for real-time inference at IoT endpoints, and architecting hybrid cloud-edge systems for latency-critical applications. Expert in containerized ML pipelines, serverless AI services, and infrastructure-as-code approaches using Kubernetes, Docker, and Terraform. Proven ability to design secure, fault-tolerant AI systems that seamlessly integrate cloud scalability with edge performance, delivering enterprise-grade solutions that optimize both computational efficiency and operational costs.
Experienced Data Scientist with over 6 years of expertise specializing in AI-driven healthcare solutions, having successfully completed 60+ projects while collaborating with major US healthcare organizations on critical applications including CHF management, ED optimization, and patient scheduling systems. Proven proficiency in Computer Vision, NLP, and AI web application development, with notable achievements in face recognition, real-time tracking, LLM-based question answering, and satellite signal processing. Former researcher at ITU’s Data Science Lab, where I developed cutting-edge algorithms using Auto-Encoders, BERT, and COMET architectures that surpassed state-of-the-art models in accuracy and performance for crime forecasting and emotion recognition projects. Currently serving as Principal Consultant at Systems Limited, architecting intelligent systems using RAG architecture and Azure AI Stack for telecom and government sectors. Additionally brings 8+ years of academic teaching experience in advanced data science courses, combining practical industry expertise with strong educational background in Big Data Analytics and Deep Learning.
Muhammad Nauman Arshad leads cutting-edge AI and data science initiatives at Sozan AI, empowering businesses to harness advanced analytics and generative AI for operational excellence and competitive advantage. With 6+ years of comprehensive experience spanning data science, AI engineering, and full-stack development, he excels in building enterprise-grade solutions from conception to deployment. His expertise encompasses multilingual AI systems, RAG architectures, natural language processing, computer vision, and cloud infrastructure management across AWS, Azure, and GCP. Proficient in sectors including e-commerce, healthcare, finance, and manufacturing, Nauman drives innovation through end-to-end solution development—from database design and API creation to frontend interfaces and MLOps deployment.
