Varun Dutt, M.S, Ph.D. Associate Professor and Principal Investigator
Varun works as an Associate Professor in School of Computing and Electrical Engineering and School of Humanities and Social Sciences at Indian Institute of Technology (IIT), Mandi. He received his Ph.D. degree in Engineering and Public Policy from Carnegie Mellon University (CMU) in 2011. He also holds a number of M.S. degrees from CMU. Prior to joining IIT Mandi, he was a Post-Doctoral Fellow at the Dynamic Decision Making Laboratory, Carnegie Mellon University. His research is at the intersection of computer science, economics, and decision making, with a special focus on how computational and experimental models could be used for taking decisions on managerial, environmental, and socio-economic issues. Varun serves as the Knowledge Editor of Financial Chronicle, a financial daily, published from India. He also serves as the Review Editor of Frontiers in Cognitive Science and Frontiers in Decision Neuroscience journals. In addition, he has been involved in the Delhi Chapter of IEEE, where he is the Vice-Chair of the IEEE Computer Society Chapter India Council (Conference/Workshop Committee). Office: 304, 3rd Floor, A4 Building, IIT Mandi, Kamand Web: http://faculty.iitmandi.ac.in/~varun/ E-mail: varun[at]iitmandi[dot]ac[dot]in Phone: +91-1905-267150 Fax: +91-1905-267009
Shruti Kaushik, M.S. Ph.D. Student
Ms. Shruti Kaushik is currently pursuing Ph.D. in Computer Science from the Indian Institute of Technology Mandi, India. In her current research, Shruti is using healthcare data-sets to develop dimensionality reduction techniques, frequent pattern mining algorithms, and time-series forecasting algorithms to predict patient-related features. Her research interests include machine learning, data mining & visualization, and deep learning. Office: ACS Lab IIT Mandi E-mail: shruti_kaushik[at] students[dot]iitmandi[dot]ac[dot]in Phone: +91-1905-267184 Fax: +91-1905-267009
Abhinav Choudhury, M.S. Ph.D. Student
Abhinav is currently working on a project for Purdue Pharma. He primarily works in the field of Data Mining. In his project, he is mining prescription histories, referral patterns of doctors/physicians to create a social network. Then using Social Network Analysis techniques he is trying to find Key Opinion Leaders in the Pharmaceutical Sector. His areas of interest include Machine Learning and Data Mining.
Akash is working on a project from Defence Research and Development Organization (DRDO). He is working on the design of a Human-Performance Modeling (HPM) framework for visual cognitive enhancement inVR and AR paradigms in the defence domain. His area of interests include Virtual Reality/Augmented Reality, cognitive modeling and human-computer interaction.
Gitanshu is a Ph.D. Scholar in the School of Humanities and Social Sciences at Indian Institute of Technology, Mandi. His areas of interest are cognitive psychology, human behaviour, human-computer interaction and cognitive modelling and presently he is working in the domain of Climate Change, to understand the various factors that affect people’s perception of climate and is currently developing an experimental study to understand the mitigative pattern followed by people to deal with climate change and its adverse effects.
Praveen is an M.S. student in the School of Computing & Electrical Engineering, Indian Institute of Technology Mandi. He has done his Masters of Computer Application from S.S. Jain Subodh college, Jaipur. As part of Applied Cognitive Science Laboratory, he is doing is research work in the field of landslide monitoring, warning system and prediction in Himachal Pradesh since 2017. He has been involved in developing a MEMS-based IoT system which helps in monitoring landslides. His area of interest comprises Embedded System, Machine Learning, Deep Learning and Artificial Intelligence.
Ankush is an Electrical Engineer graduated from Himachal Pradesh University, Himachal Pradesh India. Presently, he is working in the project named “Landslide Monitoring and Early Warning System.” Here, he is involved in the development and deployment of the landslide monitoring and early warning system. Furthermore, he is included in the site selection for the system deployment and risk communication. He is interested in the field of renewable energy, power system, and artificial intelligence.
Tushar is an M.S. student in the School of Computing & Electrical Engineering, Indian Institute of Technology Mandi. He has done his B.Tech from HMR Institute of Technology & Management, (IP University) Delhi. As part of Applied Cognitive Science Laboratory, he is doing his research work in the field of IoT and ML (Time series forecasting). He has been involved in developing a MEMS-based IoT system which monitors air pollution levels. He is working on a project funded by DEST, Government of Himachal Pradesh. His area of interest comprises Machine Learning, Deep Learning and Artificial Intelligence.
Harsh is an MS student in School of computing and electrical engineering at Indian Institute of Technology, Mandi. He did his B.E. from OP Jindal Institute of technology, Raigarh. His areas of interest are Machine learning, Cyber-security and cognitive science. Currently, he is working on a project from DST, Government of India, in which he is building a game theoretic approach involving experimentation and computational modelling of hacker’s decisions using deception in Cyber Security.
Shashank is an MS student in School of Computing and Electrical Engineering at Indian Institute of Technology Mandi. He completed his Bachelors of Engineering from Birla Institute of Technology Mesra in Computer Science. His areas of interest are Human-Computer Interaction, Cognitive Science and Cybersecurity. As a part of his research, he is working on a project from DST, Government of India, on Deception Techniques in cybersecurity using honeypots.
Shashank is a project technician currently working on the project evaluation of quantitative system pharmacology and machine learning models for blood Glucose prediction his work is to perform the R&D in the area of machine learning and deep learning.