Param has over 20 years of hands-on and leadership experience in information technology projects with Silicon Valley companies such as Sun Microsystems, Oracle and other startups. Param has done Masters degree in Systems Engineering and MBA from San Jose State University, California, USA. At Xen.AI, Param is leading a passionate group of Machine Learning engineers and Data Scientists to develop innovative solutions using AI, Machine Learning, Deep Learning and Data Science technologies to help our clients improve the efficiency and reduce the operating cost. Please feel free to reach out to Param at Param@xen.ai to explore opportunities to apply AI technologies.

Babu Arunachalam has more than 20 years of experience in engineering leadership at VizExplorer, Broadcom, Nokia, Ericsson and Qualcomm. Babu has led several engineering teams on projects small and large distributed in various countries. He has experience and expertise in a breadth of technologies - data analytics, data visualization, machine learning, databases, micro services, distributed systems, low level firmware on embedded devices and wireless protocols. Babu has a Masters degree in Computer Science from the University of Southern California and a Bachelors degree in Electronics and Communications Engineering from National Institute of Technology, Trichy, India.

Dr. Dmitry Bandurin has solid experience in experimental research, data analysis and modeling. He is a co-author of many software packages in physics experiments, industry and SaaS analytical platform developed in the digital advertising field. He has done practical application of various machine learning techniques and live data monitoring. He wrote software codes to control hardware operation. Dr. Dmitry was the leader of data science group and a few algorithmic and physics groups at Fermi National Accelarator Laboratory. He has supervised many undergraduate/PhD students, data scientists and interns in various projects. Dr. Dmitry is the primary author of many papers published in major peer-reviewed physics journals with application of machine learning algorithms.

Dr. Bhrigu has over 20 years of Data, Engineering, Product leadership experience, including managing large engineering teams involving building and implementing predictive models and machine learning. He is passionate about helping organizations solve challenges and become more efficient by deploying machine learning. Prior to Xen.ai, Bhrigu was Vice President, Software Engineering at Sony New Media Solutions and Executive Director, Sony Pictures where he was leading large teams. Bhrigu has his PhD in Computer Science from University of California, Riverside and Data Science Specialization from Harvard University. Bhrigu is also adjunct faculty at the Computer Science Department at California State University, Dominguez Hills.

Dr. Satya has over 18 years of Data Science experience at various levels, including 9 years of experience in creating and leading data analytics programs in large organizations from conception to conclusion. He is passionate about helping organizations solve challenges and deploying machine learning. Prior to Xen.AI, Satya lead data science engagements at Air Products, Orbytel Group, UPS, Prudential Financial, Select Systems, Rodale, BehaviorMatrix, Trendium, TargetRx, and Nielsen. Satya has his PhD in Industrial Engineering & Management from IIT Kharagpur, and Post Doctoral from The Hong Kong University of Science and Technology. Dr. Satya has patent, papers published in major peer-reviewed Journals: IEEE, Applied Statistical, and conferences.

Dr. Hamda has significant research and work experience in the application of machine learning and AI-driven technologies in biomedical research; manufacturing industries as well as in climate sciences. He is skilled in applied mathematics and advanced probabilistic programming inference techniques. His recent works focus on the integration of machine learning and mechanistic models for a mechanism-based understanding of clinical trials outcomes and drug transports inside tumor micro environment. He is also skilled and experienced in building knowledge graph-based Database system for end-to-end data integration and feature engineering of unstructured ‘Big Data’. Dr. Hamda holds MSc. in Biochemical Engineering in computing, Ph.D. in Bioinformatics and Theoretical Biology from Vrije University, Amsterdam, Netherlands and Ph.D. in Modelling from Jagiellonian University, Poland.

Dale Less has more than 30 years of experience in data analytics projects across multiple industries including healthcare, manufacturing, government, retail, travel and entertainment, consulting, and many others. Dale has a broad background spanning all aspects of data science including machine learning, social network analysis, ensemble modeling, decision trees, support vector machine (SVM), neural networks/deep learning, regression modeling and various other data science techniques. Dale also has strong background in inferential statistics, regression including linear, logistic, Cox, time series analysis, survival analysis, health research, epidemiology and engineering. Dale has a Masters degree in Healthcare Administration and Allied Health Research from Texas State University and a Bachelor's degree in Industrial Engineering from Tennessee Tech University.

Nutchapol has a Master’s degree in Computational and Mathematical Engineering from Stanford University. Nutchapol has an extensive machine learning experience from working as a data scientist with multiple companies and through research at Stanford. He managed a core data science engine and helped a start-up company launching its first wave of product. He has worked on developing machine learning technology in multiple applications ranging from predictive weather modeling, detecting geological structure, simplifying complex fluid flow simulation, and counting the number of objects in the bin. Moreover, he also has a consulting experience working with McKinsey & Company.

Tim has more than 25 years as a hands on business development professional and proficient client relationship manager with a substantial focus on the consultative solutions approach to solving customers demands. Prior to joining Xen.AI Tim has worked in business development leadership capacity for Tyco International and General Electric creating value and solutions for security, audio video, surveillance, building automation, fire protection and lighting. With his tertiary education Tim has more than twenty manufacturers product certifications.

Dr. Serge is involved in artificial intelligence and machine learning since 1980s. He has graduate degrees in economics, mathematics & philosophy and a PhD in Economics. He taught banking, business and corporate finance in many colleges . He also developed many financial products for largest financial and insurance companies.

Samarth has done his masters degree from IIT Madras and Bachelors degree from NIT, Bhopal. Samarth has hands on experience in Data Science and analytics field, synthesizing data, defining the problem, feature engineering, building the model, deploying the same in production. He is skilled in implementing machine learning techniques and working with large unfiltered data sets using distributed computing tools such as Google’s Tensorflow. He is experienced in Machine learning building applications and important features for AI Platform. Also, he is well aware of other Machine Learning frameworks like Caffe, Theano, MXNet, and Pytorch etc.

Experienced Machine Learning developer with a demonstrated history of working in the industry. Skilled in Deep Learning, Machine Learning, Word Processing, Computer Vision, and Content Strategy with a Bachelor of Engineering Degree from BITS Pilani and Masters Degree in Power and Control from IIT Guwahati, India.

Dr. Georgy Golovanov has hands-on experience in data analysis, data acquisition and software development. He received his Ph.D in particle physics with practical application of various machine learning techniques and algorithms. Dr. Georgy carried out research for over 13 years in world-famous physics labs in Russia (JINR), Switzerland (CERN), Germany (GSI), and USA (Fermilab) with a strong interest in Data Science and Machine learning application in data analysis and modeling of physics processes, collecting and processing raw data. He is a co-author of wide range of software tools for data analysis, data acquisition as well as hardware components. He published original results in leading peer-reviewed physics journals.