Keynote Speaker I


Prof. Kamesh Namuduri

Electrical Engineering Department, University of North Texas

Title: Emerging Technologies and Standards for Unmanned Aircraft Systems Traffic Management


Integration of Unmanned Aircraft Systems (UAS) into the National Airspace (NAS) is expected to increase the air traffic significantly requiring enhanced situational awareness and safety. Direct communication between aircraft systems within the Radio Line of Sight (LOS) and Beyond LOS (BRLOS) will help achieve the required levels of situational awareness and safety. IEEE created P1920.1 Working Group (WG) for developing the standards for aerial communications and networking. The purpose of this presentation is to share the progress made so far in the communications and networking domain.

Three paradigms have emerged for facilitating command, control, and navigation for UASs and to accelerate the integration of UASs into the national airspace. They are based on satellite, cellular, or aerial communications. These three paradigms are not necessarily competing, instead, they may be used to complement one another for back-up or redundancy. A UAS may incorporate one or a combination of these three architectures depending on its capability and mission. 

Space-based (satellite) data link communication (SATCOM) is a key technology that could facilitate Beyond Radio Line-of-sight (BRLOS) operations in non-segregated airspace. It has the ability to offer global, broadband and safe communications for both payload and safety communications [Ref]. 

NASA is working towards UAS Traffic Management (UTM) through cellular-networking. “UTM is designed to enable safe low-altitude civilian UAS operations by providing pilots information needed to maintain separation from other aircraft by reserving areas for specific routes, with consideration of restricted airspace and adverse weather conditions,” according to Parimal Kopardekar, lead of NASA’s UTM efforts. 

IEEE is the leading the third paradigm, by taking the initiative to develop the standards (IEEE P1920.1) for aerial communications and networking. Integration of UAS into the National Airspace increased the air traffic significantly requiring enhanced situational awareness and safety. Direct communication between aircraft systems within the RLOS and BRLOS will help achieve the required levels of situational awareness and safety. The overarching goal for the P1920.1 standards is to facilitate sharing of information necessary for navigation and control among the UASs. It has the advantages of low-latency compared to other means of information sharing. 


Kamesh Namuduri is a Professor of Electrical Engineering at the University of North Texas. He is serving as the chair for the IEEE P1920.1 standards working group for “Aerial Networks and Communications”. Over the past few years he co-organized a series of workshops on “Airborne Networking and Communications” in conjunction with AIAA, AUVSI, and ACM Conferences. Over the past few years, he has been leading a public safety action cluster working towards the development of “Deployable Communication Systems”. This living laboratory project has been demonstrated during the Global City Teams Challenge Exhibitions during 2014, 2015 and 2016. 

Keynote Speaker II


 Prof. Ian Robert McAndrew

Embry-Riddle Aeronautical University,UK

Title: A review of the Navier-Stokes Equation for the Theoretical Maximum Design of Twin Wing Aircraft


Twin Wing aircraft were the classical answer for maximizing lift in the early days of flight. They had high levels of drag and limited top speed. They do have low stall speeds and small turning circles. However, nowadays they are not used as modern power plants allow for higher speeds, and hence greater lift using a mono-wing concept. This research is focusing on using Twin Wing designs for Unmanned Aerial Vehicles, UAV, to fly at high altitudes, above classical commercial altitudes. Previous research has shown that optimised designs can approach higher levels and allow for greater lift at relatively low speeds. The research will show that optimizing designs can be achieved and this will be discussed and linked to how UAVs may be used to operate in different airspace without the need of interaction between piloted and UAV aircraft.


Prof. Ian R. McAndrew PhD is a mechanical engineer that has worked in education for over 25 years. His teaching and research has been globally, starting in London and now with Embry Riddle Aeronautical University. He has taught in over 20 countries and published with many academics from all over the world. He is currently the Department Chair for Graduate Studies in the college of Aeronautics, where he is responsible for 6 Masters degrees and over 3000 students. He has 5 degrees, also a qualified Electrical engineer and FRAeS. He has supervised over 25 PhDs and has almost 50 peer reviewed publications. His current research is in aerodynamics and low speed flight. He is a keen supporter of conferences as this is where junior researchers can develop their skills for a life in research.

Prof. Ian McAndrew FRAeS is a Tenured Faculty and Full professor at Embry Riddle Aeronautical University. He has worked in academia for over 27 years and lectured globally. Currently his research is in the area of low speed aerodynamics for UAVs. He has more than 55 journal and conference publications and almost 30 successful PhD supervisions. He is frequently invited to deliver Keynote speeches and is the Chair of several International Conferences. Additionally, he is the editor or assistant editor in chief of several International Journals.

Keynote Speaker III


Prof. Petra Perner

Institute of Computer Vision and Applied Computer Sciences, Leipzig, Germany

Title: Health Monitoring by an automated System for Biological Hazardous Material in the Air


Human beings are exposed every day to bioaerosols in the various fields of their personal and/or professional daily life. The European Commission has rules protecting employees in the workplace from biological hazards. Airborne fungi, yeast, bacteria, and viruses can be detected and identified by an image acquisition and interpretation system. In this talk we present results on the development of an image interpretation system for detecting biological hazardous material in the air. We explain the application domain and describe the development issues. The development strategy and the architecture of the system are described. Finally we give results.


Petra Perner (IAPR Fellow) is the director of the Institute of Computer Vision and Applied Computer Sciences IBaI. She received her Diploma degree in electrical engineering and her PhD degree in computer science for the work on “Data Reduction Methods for Industrial Robots with Direct Teach-in-Programing”. Her habilitation thesis was about “A Methodology for the Development of Knowledge-Based Image-Interpretation Systems". She has been the principal investigator of various national and international research projects. She received several research awards for her research work and has been awarded with 3 business awards for her work on bringing intelligent image interpretation methods and data mining methods into business. Her research interest is image analysis and interpretation, machine learning, data mining, big data, machine learning, image mining and case-based reasoning. Recently, she is working on various medical, chemical and biomedical applications, information management applications, technical diagnosis and e-commerce applications. Most of the developments are protected by legal patent rights and can be licensed to qualified industrial companies. She has published numerous scientific publications and patents and is often requested as a plenary speaker in distinct research fields as well as across disciplines. She is developing efficient data mining and big data methods and parallel computer architectures such as clouds. Her vision is to build intelligent flexible and robust data-interpreting systems that are inspired by the human case-based reasoning process.

Keynote Speaker IV


Prof. Wenbing Zhao

Cleveland State University, USA

Title: Reducing Lower-Back Injuries with a Privacy-Aware Compliance Tracking System


Lost productivity from lower back injuries in workplaces costs over $100 billion per year in the United States alone. A significant fraction of such workplace injuries are the result of workers not following best practices. In this talk, Dr. Zhao will present the design, implementation, and evaluation of a novel computer-vision-based system that aims to increase the workers’ compliance to best practices in using proper body mechanics. The system consists of inexpensive programmable depth sensors, smartwatches, and smartphones. The system is designed to track the activities of consented workers using the depth sensors, alert them discreetly on detection of noncompliant activities, and produce cumulative reports on their performance. Essentially, the system provides a valuable set of services for both workers and administrators toward a healthier and, therefore, more productive workplace.


Dr. Zhao is a Professor at the Department of Electrical Engineering and Computer Science, Cleveland State University. He earned his Ph.D. at University of California, Santa Barbara in 2002. He has over 170 peer-reviewed publications. Dr. Zhao’s research spans from dependable distributed systems to human centered smart systems. His research has been funded by the US NSF, US Department of Transportation, Ohio Bureau of Workers’ Compensation, Ohio Department of Higher Education, and Ohio Development Services Agency. He has delivered more than 10 keynotes, tutorials, public talks and demonstrations in various conferences, industry and academic venues. Dr. Zhao is an associate editor for IEEE Access, MDPI Computers, and PeerJ Computer Science, and a member of the editorial board of several international journals, including Computers, Applied System Innovation, Internal Journal of Parallel, Emergent and Distributed Systems. He is currently an IEEE Senior Member and serves on the executive committee of the IEEE Cleveland Section.

Keynote Speaker V

Prof. Brendan Morris

University of Nevada, Las Vegas, USA

Title: Understanding how to Assess Action Quality by Examining Sports


While action recognition has received plenty of attention from the computer vision community, action quality assessment (AQA), the process of describing how well an action was performed and assigning a "score", still remains relatively unattended. AQA is crucial for areas such as sports, training, and health care yet there is limited data available to develop general quality metrics for action.  This talk will discuss an effort to address action quality assessment by introducing a new sports AQA dataset with quality measured by professional judges.  In addition, a deep-learning framework is introduced to learn a generic action quality measure across sports.  Experimental results demonstrate how quality can be generalized between sports and how the recurrent model is able to highlight errors in performance.


Prof. Brendan Morris is a Assistant Professor at the Department of Electrical and Computer Engineering in University of Nevada, Las Vegas, USA. The research interests are Computer Vision, Machine Learning, and Pattern Recognition with a focus on real-time acquisition and processing.

Keynote Speaker VI


Dr. Chiman Kwan

Signal Processing, Inc., Rockville, Maryland, USA

Title: Image Resolution Enhancement for Remote Sensing Applications


We present a brief overview of recent image resolution enhancement algorithms with emphasis on remote sensing applications. Because resolution may have different meanings, we emphasize that our focus in this paper is on spatial, spectral, and temporal resolution enhancement algorithms. We will discuss and review recent algorithms in enhancing spatial resolution, spectral resolution, spatial-spectral resolution, and spatial-temporal resolution of remote sensing images. Several representative and interesting applications related to the fusion of Landsat and MODIS images, the fusion of color and hyperspectral images, and the fusion of Mars rover images will be presented. Finally, some future directions in this research area will be highlighted.


Chiman Kwan received his BS (honors) with major in electronics and minor in mathematics from the Chinese University of Hong Kong in 1988, and MS and Ph.D. degrees in electrical engineering from the University of Texas at Arlington in 1989 and 1993, respectively. He is the founder and Chief Technology Officer of Signal Processing, Inc. and Applied Research LLC, leading research and development effort in real-time control, chemical agent detection, biometrics, speech processing, image fusion, remote sensing, mission planning for UAVs, and fault diagnostics and prognostics.

From April 1991 to February 1994, he worked in the Beam Instrumentation Department of the SSC (Superconducting Super Collider National Laboratory) in Dallas, Texas, where he was heavily involved in the modeling, simulation and design of modern digital controllers and signal processing algorithms for the beam control and synchronization system. He later joined the Automation and Robotics Research Institute in Fort Worth, where he applied intelligent control methods such as neural networks and fuzzy logic to the control of power systems, robots, and motors. Between July 1995 and April 2006, he was the Vice President of Intelligent Automation, Inc. in Rockville, Maryland.

Over the past 25 years, Dr. Kwan has served as Principal Investigator/Program Manager for more than 111 competitively selected projects with total funding more than 35 million dollars from various government agencies and private companies such as Ford, Motorola, Boeing, Honeywell, and Stanford Telecom. He has 14 issued and pending patents, 50 invention disclosures, 80+ journal papers, 200+ conference papers, and 350+ technical reports. He received numerous awards and recognitions from NASA, US Navy, US Air Force, and IEEE.

Keynote Speaker VII


Prof. Henry Yang

Cancer Science Institute of Singapore, National University of Singapore, Singapore

Title: Integrated bioinformatics analysis of large-scale data for novel discovery in RNA biology


Bioinformatics has become an important part of many areas of biology and an essential tool to interpret and understand various large-scale genomic/proteomic datasets. Many high-throughput technologies, such as next-generation sequencing, microarray, mass spec, and high-throughput screening, are now available for biologists to perform large-scale profiling of cellular events for extracting relevant biological insights. As each type of data generated by these technologies describes biological events from different angles/aspects and alone can only provide information on a biological system from a limited viewpoint, integrated viewpoints from different disparate datasets are often required to better understand the complex biological regulatory mechanisms. In this talk, a novel modular integration platform will be discussed which contains two steps: 1) indivivual data analysis portal and 2) modular data integration portal. Given a biological question, we can integrate different data at different stages modularly to better answer the question asked. Several examples with the application of this platform will be highlighted, including grwth/transcriptional factors, alternative splicing, RNA editing and lncRN expression during hematopoiesis, leukemia or stem cell development.


Prof. Henry Yang heads the Bioinformatics group at Cancer Science Institute of Singapore & is an Associate Professor at Department of Biochemistry, National University of Singapore. His research interests are computational genomics, next-generation sequencing (NGS) data analysis, large-scale data analysis & integration. He has over 130 peer-reviewed publications. The main research focuses of his group are in analysis, integration and interpretation of the large-scale genomic/epigenomic data. The group handles diverse genomic data such as hybridization-based microarrays (expression, SNP, methylation and CGH arrays) as well as various NGS data (DNA-seq, RNA-seq, ChIP-seq and their derivatives), works closely with biologists and clinical scientists on development of sophisticated analysis/ interpretation/ integration methods and pipelines, and also provides bioinformatics training and support services to biomedical/biological researchers. 

Keynote Speaker VIII


Dr. Zhijin(Jean) Wu

Brown University, USA

Title: Two-phase differential expression analysis for single cell RNA-seq


Single-cell RNA-sequencing (scRNA-seq) has brought the study of the transcriptome to higher resolution and makes it possible for scientists to provide answers with more clarity to the question of ‘differential expression’. Specifically, scRNA-seq data allows us to observe binary (from Off to On) as well as continuous (the amount of expression) regulations. We present a method that identifies the phase of expression a gene is in, by taking into account of both cell- and gene-specific contexts, in a model-based and data-driven fashion. We then identify two forms of transcription regulation: phase transition, and magnitude tuning. We demonstrate that compared with existing methods, SC2P provides substantial improvement in sensitivity without sacrificing the control of false discovery, as well as better robustness. The ability to separately detect different forms of differential expression provides better interpretation of the nature of expression regulation. 


Dr. Zhijin Wu is Associate Professor of Biostatistics at Brown University. She received her PhD in Biostatistics from Johns Hopkins University and joined Brown faculty in 2005. Her research focuses on developing statistical methods and software for high throughput technologies such as next generation sequencing, DNA microarrays, and high throughput screening assays. Her research is primarily funded by the NSF and the NIH.