Profile of Board Members

Dr. Mahesh Panchagnula

Dr. M. Thenmozhi
Dr. M.Thenmozhi is a Professor in Department of Management Studies of Indian Institute of Technology Madras, Chennai with more than 32 years of academic experience. She has also been the Director of National Institute of Securities Markets, Mumbai. Prior to joining IIT Madras, she was working as a Faculty in the Management Division of the Department of Industrial Engineering and Management at Anna University, Chennai. She has been ranked in "Top 100 Women in Finance in India" in 2019 and 2020 by AIWMA. She specialises in applied and policy implications-based research in the domain of corporate finance, market microstructure and financial time series modelling. She has developed hybrid AI and Support Vector Machine based forecasting models for stock market trading and investing, models to test information transmission between markets, determinants of ETFs performance, Commodity market price discovery, impact of family and promoter driven firm’s governance and country level determinants of FDI and Cross border acquisitions.

Mr. Anuj Kumar
Mr. Anuj Kumar is the Managing Director of CAMS. He joined CAMS as a Chief Operating Officer – Asset Management Services on March, 2016 and was appointed as Whole time Director and CEO with effect from November 6, 2018. He was appointed as Managing Director with effect from 1st August 2021.
He joined CAMS after 25 years of professional experience with Godrej & Boyce Mfg. Co. Ltd., Blow Plast Limited, Escorts Finance Limited, BillJunction Payments Limited, IBM India Private Limited and Concentrix Daksh Services India Private Limited.
He holds a Bachelor degree in Mechanical Engineering from Birla Institute of Technology, Ranchi and a Post Graduate Diploma in Management (PGDM) from IIM, Kolkata.

Mr. Ram Charan Sesharaman
Mr. Ram Charan Sesharaman joined CAMS as Chief Financial Officer- Designate in March 2020. He was appointed as Chief Financial Officer with effect from 1st August 2021.
He joined CAMS after 22 years of experience with organisations like TVS , SSI , Lason India , Photon Interactive and Reliance Jio. He holds a Bachelor degree in Commerce from University of Madras and is a qualified Chartered Accountant.

Prof. John Augustine
John Augustine is a professor in the Department of Computer Science and Engineering (CSE) at the Indian Institute of Technology Madras. He holds a PhD from the Donald Bren School of Information and Computer Sciences at UC Irvine. His research interests are in distributed algorithms specifically focusing on distributed trust issues that emerge in settings where participants may behave maliciously. He has co-authored many refereed articles that have appeared in highly reputed conferences (SODA, FOCS, PODC, NEURIPS, DISC, SPAA, IPDPS, etc.) and journals (Algorithmica, SICOMP, TCS, JPDC, TPDS, etc).
He was the chair of the distributed computing track at ICDCN 2022 and is currently serving as an associate editor at the Journal of Parallel and Distributed Computing. At IIT Madras, he is a founding member of the Cryptography, Cybersecurity, and Distributed Trust group (CCD) as well as the Blockchain Innovation Centre (BiC). He is also affiliated with the Theory group in CSE..

Mr. Kaushik Narayanan

Mr. Ravi Kethana

Dr. Nandan Sudarsanam
Nandan Sudarsanam is a faculty member in the Department of Management Studies and a core member of the Robert Bosch Center for Data Science and Artificial Intelligence (RBCDSAI) at IIT Madras. He earned his PhD from the Engineering Systems Division at MIT, following which, he worked as a quantitative researcher for five years at a high-frequency algorithmic trading firm in New York. His research and work experience focuses on applications of experimentation, machine learning and the abstraction of data to models and algorithms. This spans data and problems across different domains, including but not limited to finance, urban mobility, digital platforms, civic services, and criminology. He publishes in machine learning conferences as well as peer-reviewed journals in engineering and applied statistics.