Associate Professor
Department of Electrical Engineering
Indian Institute of Technology Hyderabad (IITH)
Indian Institute of Technology Hyderabad (IITH)
+91 40 2301 6463
Sumohana has been on the faculty of the Electrical Engineering department at IITH since July 2012. At IITH, Sumohana directs the Lab for Video and Image Analysis (LFOVIA) where problems on image and video quality assessment, biomedical image processing and machine learning are explored. Problems on task-specific image quality assessment such as for face recognition or autonomous navigation are of particular interest to his group. He is a recipient of the Excellence in Teaching Award at IITH (in 2013 and 2017), and the QUALSTAR Award at Qualcomm.
Current autonomous navigation systems rely on a number of sensors including LiDARs, vision cameras and radars for environment sensing and decision making. Given the complexity associated with handling large point clouds associated with LiDAR data, there has been an increasing push towards completely vision based autonomous navigation systems. In this discussion, we will deliberate on the challenges, benefits and drawbacks of building vision-only autonomous navigation systems.
Professor, IISc Bangalore
Research Head & Director, I-Hub for Robotics and
Autonomous Systems Innovation Foundation (ARTPARK)
My current research is in Tele-Robotics – especially with a focus on tele-autonomous intelligence involving speech, language, vision and action, to enable high quality, multi-modal interaction of humans to interact with remote environments through intelligent robots. I am exploring both engineering and research questions related to this technology, in the context of various use cases like remote nursing care, remote drone operation, remote driving etc.
Assistant Professor and Director of the Robot Learning Lab Department of Computer Science University of Freiburg
Abhinav Valada's research lies at the intersection of robotics, machine learning, and computer vision with a focus on tackling fundamental robot perception, state estimation, and control problems using learning approaches in order to enable robots to reliably operate in complex and diverse domains. His Robot Learning group has developed several innovative techniques for scene understanding, state estimation, and motion planning that have defined the state of the art and ranked at the top of benchmarks. His group has also won many awards such as the winner of the CVPR 2021 Embodied AI Challenge, and winner of the ECCV 2020 Robust Vision Challenge. Abhinav Valada’s research spans several machine learning problems including self-supervised learning, unsupervised learning, interactive learning, and continual learning. His current research projects are focused on tackling challenges in autonomous driving, robot navigation in urban and unstructured environments, human-robot interaction for assistive home robots, mobile manipulation, agricultural robotics, and search and rescue with ground and aerial robots. Abhinav is a co-chair of the IEEE Robotics and Automation Society (IEEE RAS) Technical Committee on Robot Learning and a founding member of the European Laboratory for Learning and Intelligent Systems (ELLIS) Unit Freiburg.
IIT Hyderabad
Dr. P Rajalakshmi, is Professor in the Department of Electrical Engineering, IIT Hyderabad, which she joined in 2009. Her research is in the area of Drone based sensing, wireless communications, Internet of Things, Cyber Physical Systems targeting applications like agriculture, transportation – aerial and terrestrial, healthcare, environmental monitoring and smart buildings. She has been handling R&D projects as PI/co-PI, funded by industry and Government of India in these areas. She is also the Project Director of DST NMICPS Technology Innovation Hub on Autonomous Navigations Foundation (TiHAN) at IITH. Along with fundamental theoretical research in IoT/CPS about wireless communications, low-complex signal processing algorithms, sensor development, she also emphasize on translational research which involves development of minimum viable and user beneficial products. Out of her research activities, she has filed 10 patents, published over 30 Journals and 100 conference peer-reviewed papers. She is awarded Young Faculty Research Fellowship under Visvesvaraya PhD Programme starting January 2016 for a period of 5 years, ‘Digital Trail Blazer Award 2016’ by India Today at National Level and in Telangana state, best paper/poster Awards in reputed conference. She is a Member of CII Telangana Digital Transformation and IT Panel since August 2018. She is a mentor for Start-up company (SKIoT) incubated at IITH, founded by 2 PhD students from her lab.
Karlsruhe Institute of Technology
My research is focused on the intersection of machine learning, robotics and human-robot interaction. My goal is to create data-efficient machine learning algorithms that that are suitable for complex robot domains. In my research, I always aim for a strong theoretical basis for my developed algorithms which are derived from first order principles. Yet, I also believe that an exhaustive assessment of the quality of an algorithm in a practical application is of equal importance. My group focuses on the development of new algorithms for different aspects of autonomous learning systems:
Assistant Professor Center for infrastructure, Sustainable Transportation and Urban Planning (CiSTUP), Indian Institute of Science
Our research group at IISc focuses on the optimization of traffic systems and transportation networks. In the past few years, we have applied Markov decision processes and reinforcement learning techniques to various contexts. For example, we used deterministic policy gradient methods to find threshold policies for inventory management in large-scale bicycle-sharing systems that reduce lost customer demand. We also integrated online routing algorithms in equilibrium frameworks of network games to model rerouting among travelers in the presence of non-recurring congestion and studied extensions involving dynamic tolls that achieve socially optimal outcomes. More recently, we applied dynamic discrete choice-based econometric methods to understand departure time decisions of households faced with a threat of evacuating during hurricanes. Our research group also focuses on public transportation systems and shared mobility. We have developed faster routing algorithms for bi-criteria Pareto optimal journeys using nested graph partitioning methods, agent-based simulators to test the impact of providing first- and last-mile services, control methods to prevent bus bunching, and branch-and-price based methods for ride-matching.
TU Darmstadt
georgia.chalvatzaki@tu-darmstadt.de
My research interests concern the development of learning methods for intelligent robot behavior. My research philosophy entails that the long-wished autonomy in robotic assistants will be achieved by examining the interconnection of classical robotics methods and machine learning, understanding the benefits of both fields, and developing techniques that will allow the intelligent behavior of robots to emerge through their interaction with their environment. My previous experience and research breakthroughs lie in the field of assistive robotics. Through my primary focus on embodied Artificial Intelligence (AI) of robot assistants (mobile and humanoid robots), I have developed methods for human motion and action prediction, while my work on interactive Reinforcement Learning (RL) for Human-Robot Interaction (HRI) enabled the planning of human-adaptive robot behaviors. In particular, I have previously addressed the challenges of developing intelligent assistant robots during my doctoral studies following the robotics paradigm of "sense, plan, act". My future research seeks to answer the fundamental research question on how can embodied AI systems, like mobile manipulator robots, learn manipulation skills for planning household tasks and interacting with humans in home environments.
My long-term research vision entails studying classical robotics and machine learning methods for developing new algorithms for intelligent robotic assistants. My research focuses on learning of mobile manipulation for long-horizon tasks and safe and trustful HRI. Throughout my research career, I developed a combination of knowledge in machine learning and robotics, with hands-on experience in real and complex robotic systems and a deep understanding of the procedures and protocols of user studies. I believe that hands-on engineering experience is fundamental for understanding the advantages/limitations of robotic platforms towards developing novel algorithms to advance robotics research. Moreover, I have conducted several user studies. I have worked alongside doctors, physicians, and psychologists to develop novel assistive behaviors for robots. I publicly represent my lab in dissemination activities, like international conferences and reach-out.
As a young researcher, I received one of the most important research grants of the German Research Foundation when I got accepted into the Emmy Noether program in December 2020, only one year after my doctoral thesis defense. Only nine projects out of 91 applications were selected for funding. Following that, I have started my independent research group, iROSA, to study "Robot Learning of Mobile Manipulation for Intelligent Robotic Assistants" in March 2021. I am a co-chair of the IEEE RAS technical committee of Mobile Manipulation, and I have been voted “AI-Newcomer” for 2021 by the the German Infotmatics Society.
General Manager
Automotive Rearch
Association of India, Pune
