Dr. Anirban Das

Anirban Das is an Assistant Professor and researcher specializing in IoT, human sensing, and ambient intelligence. With a Ph.D. in Computer Science and postdoctoral experience at IIT Kharagpur, his work focuses on intelligent sensing systems, mmWave technology, and real-time data processing for human activity recognition.

He has a research record, with publications in top-tier conferences (CORE A*), high-impact journals, and patents in smart sensing applications. Passionate about hands-on learning and interdisciplinary collaboration, he actively mentors students and leads innovative projects in emerging technologies.

Beyond academia, he has a keen interest in photography, painting, and exploring advancements in intelligent systems. 

Anirban Das has recently joined the faculty at UPES as an Assistant Professor. Prior to this, he was an Assistant Professor at NIIT University, where he played a key role in curriculum development, research initiatives, and establishing an IoT lab to support both academic and applied research.

Before his tenure at NIIT University, he served as a Postdoctoral Researcher at IIT Kharagpur, where his work focused on mmWave sensing for multi-user activity recognition and MACH kernel optimizations. His research contributions have been published in top-tier conferences such as IPSN and PerCom.

Earlier in his career, he worked as a Lecturer at Jimma University, Ethiopia, teaching core computer science subjects and mentoring undergraduate research projects. He also gained research experience as a Project Trainee at ISI Kolkata, where he developed sentiment analysis systems for the telecom Industry. 

Anirban's research focuses on intelligent sensing, edge computing, and data-driven optimization for smart environments. His work explores innovative ambient, wireless, and acoustic sensing methodologies with applications in human activity recognition, Internet of Things (IoT) systems, and cybersecurity. His ongoing research revolves around acoustic sensing, fault detection in large-scale wireless sensor networks, road condition assessment leveraging in-car views, and microservice fault analysis. His research also delves into testbed solutions, where he has developed strategies to enhance data processing efficiency in shared IoT setups, reducing computational overhead by including contextual information.

Looking ahead, he aims to expand his research into emerging areas such as multimodal sensing for smart infrastructure, privacy-aware ambient intelligence, and advanced human-computer interaction using alternative auxiliary sources. He is particularly interested in exploring brain-computer interfaces, leveraging EEG and other biosignals to develop novel interaction models. Additionally, he is actively working on enhancing cybersecurity frameworks with a focus on malware detection and prevention. He seeks to bridge the gap between theoretical advancements and practical applications through interdisciplinary collaborations and real-world implementations, driving innovation in intelligent sensing and computing systems. 

Anirban's teaching philosophy is rooted in the belief that effective education goes beyond simply imparting knowledge—it's about inspiring students to think critically, ask the right questions, and creatively apply their learning to real-world challenges. Drawing from his own experiences as both a student and teacher, he prefers to walk through a personalized approach to teaching, focusing on understanding students' individual learning needs. By establishing strong rapport and creating an engaging environment, he tries to ensure that each student not only grasps fundamental principles but can also connect theory with practical applications. His teaching strategies often incorporate hands-on activities and real-world case studies to make learning relevant and impactful.

Having experienced various academic settings, Das is committed to creating a learning atmosphere fostering curiosity, collaboration, and a deep intellectual responsibility. He believes that research and teaching should go hand-in-hand, enabling students to explore ideas that bridge gaps between classroom learning and cutting-edge research. By continually integrating his research into his courses, Das provides students with an enriched learning experience that prepares them for industry roles and equips them with the skills needed to contribute to future technological innovations. 

Anirban Das has taught a range of undergraduate and postgraduate courses throughout his career.

• Computer Architecture and Organization: This course introduces students to the fundamental concepts of computer architecture, covering the structure and operation of computers and the interaction between hardware and software.  
• Data Communication and Computer Networks: Dr. Das’s approach to teaching this course involves real-world case studies and practical exercises, helping students understand the principles of networking, data transmission, and network protocols.
• Internet of Things – Design Fundamentals: In this course, Dr. Das provides an in-depth exploration of the design and implementation of IoT systems. He incorporates both theoretical knowledge and hands-on with micro controllers, sensors and communication technologies allowing students to work on experimental setups and real-world IoT projects.
• Operating System Concepts This course introduces students to the fundamental concepts of Operating Systems (OS) and helps them explore core OS principles through theory and projects.

Additionally, Dr. Das has played a pivotal role in designing the curriculum for IoT-related courses and has contributed to setting up an IoT lab, where students and researchers can experiment with state-of-the-art devices and systems.

His previous teaching experience includes courses like Health Informatics, Operating Systems, Computer Networks, and Network Security & Cyber Laws, at institutions such as the School of Computing, Jimma University (Ethiopia), and Barak Valley Engineering College (India). 

1. Anirban Das, Sandip Chakraborty, & Suchetana Chakraborty (2022). Where do all my smart home data go? Context-aware data generation and forwarding for edge-based microservices over shared IoT infrastructure. Future Generation Computer Systems, 134, 204-218. (IF=7.5)
2. Anirban Das, Navlika Singh, & Suchetana Chakraborty (2024). UniPreCIS: A data preprocessing solution for collocated services on shared IoT. Future Generation Computer Systems, 153, 543-557. (IF=7.5)  
3. Argha Sen, Anirban Das, Swadhin Pradhan, and Sandip Chakraborty (2024). Continuous Multi-user Activity Tracking via Room-Scale mmWave Sensing. In 23rd ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2024) (CORE A∗).                             
4. Argha Sen, Avijit Mandal, Prasenjit Karmakar, Anirban Das, and Sandip Chakraborty (2023). mm- Drive: mmWave Sensing for Live Monitoring and On-Device Inference of Dangerous Driving. In 21st IEEE International Conference on Pervasive Computing and Communications (PerCom 2023). pp. 2-11 (CORE A∗).                     
5. Anirban Das, and Suchetana Chakraborty. ”Experience: Developing a Testbed for Ambient Sensing and in-Network Data Processing.” 2022 14th International Conference on COMmunication Systems & NETworkS (COMSNETS). IEEE, 2022.  

Patents:                            

”A SYSTEM FOR IN-VEHICLE PASSIVE MONITORING OF DRIVER BEHAVIORS.” in Indian Patent. Status: Submitted                         

”SOCIAL ENGINEERING ATTACKS DETECTING AI- DEVICE” in Indian Patent (Design registered).  

anirban.das@ddn.upes.ac.in