Vision : Building a dynamic organization at the forefront of technology adoption and innovation
Mission : Pursuing creation and dissemination of solutions to render digitally native enterprises with access to user-centric solutions that foster greater Collaboration and Transparency, and Deliver Excellence
Ramesh Babu
Ramesh Babu is an MPharm from Bangalore University, and he is currently pursuing Phd from JNTU. Ramesh Babu carries more than 20 years of diversified experience in the Life Sciences space encompassing various areas such as QA, Audit and Regulatory Affairs with successful track record of regulatory inspections in the areas of both Good Manufacturing Practices (GMP) and Good Clinical Practice (GCP). He brings forth rich domain expertise to the mix to allow rapid product iterations that account for ever evolving industry landscape.
Fadi Nassar
Mr. Fadi Nassar being the Member of the Institute of Chemical Engineers UK, is a senior business leader with 30 years of proven experience in pharmaceutical and chemical industries and being recognized as a major contributor to the growth of various reputed pharma companies across the globe in EU, USA and MENA, China and India.
As a strategic Advisor Fadi plays an active advisory role at Aizen Algo with his direct experience operating in various global regulatory environments, to have a say in securing the quality of life saving products while improving the efficiency of life sciences companies across the globe through Digitalizing the entire R&D to Commercialization narrative.
Chandra Dasika
A Chemical Engineer Graduate from IIT Bombay and a Data and Digital Leader with 17 years of experience in delivering best-in-class Digitalization solutions to several industries including Healthcare, Finance, Technology, eCommerce etc., Chandra has led large Technology & AI led Change programmes successfully for global corporates over several years. He commenced his career with JP Morgan Investment Banking and then worked with large conglomerates such as S&P and Tata Group. Currently Heading Technology & Operations at A.i.zen Algo.
Dr. Haragopal V.
Dr. Haragopal is spearheading the development of several Artificial Intelligence (AI) Systems at A.i.zen Algo. He has more than 38 years of experience in Academia and Research involving Applied Statistics and Data Analytics - across Industries and Institutes of higher learning. Till recently he worked as the Head and Chairman Board of Studies, Director Centre for Quantitative Methods at Osmania University, Hyderabad. Also, he was associated with Data Sciences wing under the Dept of Mathematics in BITS Pilani - Hyderabad campus.
Dr. Haragopal has published around 130+ research publications in National and International journals of repute in the fields of Natural language Processing, Pharmacokinetics, Image Processing, Statistical Genetics, Machine learning, Neural Networks, Time series, Deep learning etc. He has also actively delivered 600+ Data Analytics projects including several Industrial use cases. He was associated with leading Pharma companies as their Institutional Review member for BA/ BE studies and clinical trials
Venkatesh Natarajan
Venkat has a masters in Artificial Intelligence and brings in 20+ years of technology leadership experience in all facets of IT product development and business analytics implementation lifecycle. Venkat has led large cross functional and geographically distributed teams in successfully building and implementing Enterprise scale applications for customers in India and overseas.
His areas of expertise include defining R&D strategy, long term technology roadmaps, product architecture for building robust applications, building cloud enabled solutions and reusable frameworks.
Venkat has previously held leadership positions in Oracle, GE and has co-founded Dhanush Infotech - an IT services company.
Bithunshal U.
Bithunshal U. B. is a Chemical Engineer from BITS Pilani. He has several years of experience in Pharmaceutical R&D. He is spearheading Smart Formulation initiatives that are designed to provide end-to end research and development automation opportunities. These initiatives are designed to accelerate product development life cycle without compromising on the product quality, by leveraging Mathematical Modelling & Simulation, Machine Learning and Robotics.