Distinguished Technologist at Hewlett Packard Labs, USA
Dejan is a distinguished technologist at Hewlett Packard Labs, Palo Alto, CA (1998-) leading system software teams over 4 continents and projects with budgets of hundreds US$M. He worked at the OSF Research Institute in Cambridge, MA and at the Mihajlo Pupin Institute in Belgrade, Serbia. Milojicic received his PhD from Kaiserslautern University, Germany; and his MSc/BSc from Belgrade University, Serbia. He was a technical director of the Open Cirrus Cloud Computing Testbed, with academic, industrial and government sites in the US, Europe, and Asia. He has published 2 books and 180 papers; he has 37 granted patents. He is an IEEE Fellow (2010) and ACM Distinguished Engineer (2008). Milojicic was on 8 PhD thesis committees and taught Cloud management course at SJSU. As president of the IEEE Computer Society (2014), he started Technology Predictions, the top viewed CS news. As the industry engagement chair, he started IEEE Infrastructure'18 conference.
Abstract: The deceleration of transistor feature size scaling has motivated a growing adoption of specialized accelerators, such as GPUs, FPGAs and ASICs, and more recently new types of computing such as neuromorphic and quantum. There is a tension between specialization and generalization, former enabling raw performance improvement and latter enabling standard software stacks. This talk will address System Software functionality for memristor- based accelerators by exploring one accelerator implementation (the Dot Product Engine, or DPE) for a select pattern of applications in machine learning and neural networks. It will also describe a new instruction set architecture and accompanying software stack and toolchain, with its compiler, loader, device driver and emulators. Measurements of performance and power consumption will demonstrate that making an accelerator such as the DPE more generalized can lead to a broader adoption and better utilization.
Senior Director, Engineering, Qualcomm Research India
Dhananjay Gore is the Head of Qualcomm Research India at Bangalore. He is responsible for all R&D efforts at the center spanning 3G/4G (UMTS & LTE) protocol and modem design, imaging, virtual reality, ASIC enablement and embedded software. He also leads the modem and multi-media systems engineering teams for chipset product development at Qualcomm India. Dhananjay received his Bachelor of Technology Degree in Electrical Engineering from IIT-Bombay and Masters and Ph.D. Degrees in Electrical Engineering from Stanford University. He is a recipient of the Institute Silver Medal from IIT-Bombay for graduating first in his class. While at Stanford, Dhananjay co-authored a graduate level text book on MIMO, "Introduction to space-time wireless communications". He has 88 US patents to his credit.
Abstract: Updated soon....
KT Endowed Chair Professor, KAIST, KOREA.
Jong-Hwan Kim received his Ph.D. degree in Electronics Engineering from Seoul National University, Korea, in 1987. Since 1988, he has been with the School of Electrical Engineering at KAIST and is KT Endowed Chair Professor. Dr. Kim is Director of both of the KohYoung-KAIST AI Joint Research Center and Machine Intelligence and Robotics MSREP (Multi-Sponsored Research and Education Platform). His research interests include InT (Intelligence Technology), machine intelligence learning, intelligent interactive technology, AI robots. Dr. Kim has authored 5 books and 5 edited books, 2 journal special issues and over 400 refereed papers in technical journals and conference proceedings. Dr. Kim has delivered over 200 invited talks on machine intelligence and robotics including over 50 keynote speeches at the international conferences.
He served as an Associate Editor for the IEEE T. on Evolutionary Computation for 1997-2015 and the IEEE Computational Intelligence Magazine for 2008-2015. Dr. Kim was one of the co-founders of the International Conference on Simulated Evolution and Learning in 1996 and International Conference on Robot Intelligence Technology and Applications (RiTA) in 2012. His name was included in the Barons 500 Leaders for the New Century in 2000 as the Father of Robot Football. He is the founder and the organizing chair for the first AI World Cup 2018 in Korea. Dr. Kim was the recipient of the science and technology award from the President of Republic of Korea in 1997 and was elevated to IEEE Fellow in 2009.
Abstract: To develop agent-embedded robots with MI (Machine Intelligence), iOA (intelligence operating architecture) needs to be designed for sensing, thinking and action. The key modules of iOA are the perception module, the memory module for storing knowledge after learning, reasoning module using the mechanism of thought, and motion execution module, among others. This talk introduces recent research outcomes of the RIT laboratory on MIL (Machine Intelligence Learning) for active knowledge acquisition and adaptive knowledge application. MIL is applied to an agent-embedded robot to build MI based on iOA. This talk focuses on the development of long-term memory. The long-term memory is developed as an integrated multi-memory neural model, in which episodic memory is designed using a Deep DRN (Developmental Resonance Network) neural model, semantic memory is built using the 3D scene graph, and emotional memory is designed based on OICRN (Online Incremental Classification Resonance Network). Procedural memory is also designed using RNNCI (Recurrent Neural Network with Context Information) to store the trajectories of the manipulator along with context information and then retrieve them according to the context without any calculations and conscious thinking. The effectiveness of MIL for the agent-embedded robot is verified through experiments with a humanoid robot, Mybot, developed in the RIT Lab. Agent-embedded Mybot is introduced mainly for natural interactions including VQA (Visual Question Answering) with humans. In the last part, AI World Cup is introduced, which has three categories, AI Soccer, AI Commentator, and AI Journalist . The 2nd AI World Cup will be held at KAIST on November 1-3, 2019.
Vinod A Prasad
Professor and Dean (Industry Collaboration& Sponsored Research), IIT Palakkad
Vinod A Prasad is a Professor in Electrical Engineering Department of IIT Palakkad and the Dean of Industry Collaboration& Sponsored Research. He has 24 years of work experience in industry and academics. Prior to joining IIT Palakkad in October 2017, Dr. Vinod has been a tenured Associate Professor in School of Computer Engineering, Nanyang Technological University (NTU), Singapore. Vinod's research interests include digital signal processing, low power, reconfigurable circuits & systems for wireless communications, Brain-Computer Interface and its applications. He has on- going and completed external research grants from various funding agencies - Ministry of Education, Singapore, Ministry of Defence, Singapore, DSO National Laboratories, Singapore, European Aeronautic Defence& Space Company, Singapore Millennium Foundation, Civil Aviation Authority of Singapore and Airbus Group Innovations amounting over $3 million as principal investigator. He has published over 240 papers in refereed international journals and international conferences. He has supervised and graduated 15 Ph.D. students and 1 Master of Engineering (By Research) student. Currently, he is guiding 5 Ph.D. students and 3 Post-doctoral Fellows. He is an Associate Editor of IEEE Transactions on Human-Machine Systems, and Associate Editor of Springer Journal of Circuits, Systems & Signal Processing, Senior Member of IEEE and Track Co-Chair (Brain-Machine Interface Systems) of IEEE Systems, Man & Cybernetics Society for which he won the award of the 'Most Active Technical Committee in Human-Machine Systems' of IEEE Systems, Man and Cybernetics Society in three consecutive years - 2015, 2016 and 2017. Vinod has won the Nanyang Award for Excellence in Teaching 2009, the highest recognition conferred by NTU Singapore to individual faculty for teaching.
Abstract: Brain-Machine Interfaces are systems that translate the user's intention coded by brain activity measures into a control signal without using activity of any muscles or peripheral nerves. These control signals can potentially be employed to substitute motor capabilities (e.g. brain-controlled prosthetics for amputees or patients with spinal cord injuries, brain-controlled wheel chair); to help in the restoration of such functions (e.g. as a tool for stroke rehabilitation), to enable alternative communication (e.g. virtual keyboard, speller etc.) for those who are disabled or otherwise unable to communicate, and other applications such as serious games for enhancing cognition skills.
This talk will provide an overview of Brain-Machine Interface (BMI), applications, methods for brain signal acquisition and their comparison, relevant Electroencephalogram (EEG) signal features for BMI and signal processing& machine learning tools for BMI. Further, the talk will cover some selected non- invasive BMI research work from our group, which includes decoding of hand movement kinematics from Electroencephalogram (EEG) and neurofeedback games for improving the attention and cognitive skills. Some of our recent work using low cost commercially available EMOTIV EEG system (which has only fewer electrodes compared to conventionally used EEG systems) for decoding motor imagery directions, and detection of familiarity (possible applications in psychology, criminal investigation etc.) will also be discussed. The talk will conclude highlighting potential future BMI research topics.