International Speakers

Leifer, Klaus

Professor at Department of Engineering Sciences, 

Applied Materials Science UPPSALA University Sweden.

Professor Leifer has studied physics at the RWTH Aachen University. In his thesis at the Swiss Federal Institute of Technology in Lausanne (EPFL), he focused on materials analysis and in particular, electron microscopy techniques. During his work as a researcher at EPFL, he work on metallic multilayers, semiconductor nanostructures as well as on beam induced deposition techniques. At Uppsala University, Professor Leifer develops and refines advanced electron microscopy and Nano structuring techniques to understand and create materials which obtain their functionality on the micron down to the atomic scale. Professor Leifer has been a member of the CEI-Europe faculty since 2008. He has more than 200 research contributions. Currently he is working on four projects.

Dr. Raziq Yaqub

Associate Professor

Department of Electrical Engineering and Computer Science

Alabama A & M University USA

Dr. Raziq Yaqub earned his Ph.D. in Wireless Communication from Keio University, Japan in 1998, MS in Electrical Engineering with distinction from UET Peshawar in 1993 and B.Sc. in Electrical Engineering with distinction from UET Peshawar in 1986. Also he is MBA in Marketing from Fairleigh Dickenson University, USA in 2004.

He is one of the pioneers of LTE/4G, and an inventor of numerous technologies of 4th Generation Wireless Communication, and Smart Grid. He invented 25 New Technologies and Filed Patents in FinTech and Cybersecurity Technologies in last 11 months. He received “Inventor of the Year Award” from the Governor of the State of New Jersey, USA, through Inventors Hall of Fame.

Dr. Yaqub remained an Executive Director of Toshiba America Research, Department head of NIKSUN University, headquartered in Princeton, New Jersey, where he lead educational efforts on Cybersecurity, and Big Data Analytics. He honored with “Corporate Award”, for Strategic Planning of IEEE 802.11n, by Toshiba Headquarters Japan. He also remained Sr. Consultant to the State of New Jersey, a spokesperson in 3GPP on behalf of Department of Homeland Security”, an Associate Professor at University of Tennessee, and currently an Associate Professor at Alabama A&M University, Huntsville. He is also Managing Partner of Del Terri, a Big Data Analytics venture and chairman MWIF where he honored with “Appreciation Award” by MWIF Board of Directors

Dr. Yaqub is skilled in teaching, conducting research, inventing technologies, developing solutions, and building industry academia collaboration. His academic efforts include developing from scratch, the new courses on “Smart Grid”, “4G Networks”, and “Advanced Metering Infrastructure and Cyber Security”. His research interest is in Big Data Analytics, 5G/4G/LTE, Smart Grid technologies (including Electric Vehicles, Renewable Energies, Smart Home Energy Management, etc.), and Cyber Security. He filed 34 patents (24 already issued), published numerous papers in international conferences, and submitted 150+ contributions in technical standards organizations. He remained a working group chairman in Mobile Wireless Internet Forum, Chairman IEEE Membership Development Committee, Chairman IEEE Award Committee, Rapporteur in 3GPP, keynote speaker, panelist, and guest speaker in numerous International conferences. He also conducted number of workshop/ seminars for educational and awareness purpose.


Department of Electrical and Computer Engineering
Rowan University

Signal processing; Computer vision; Big data analytics; Machine learning;

Optimization Education and Professional Experience:                                                                       Nidhal Carla CV

He did his PhD in Electrical & Computer Engineering, from University of Illinois at Chicago, IL. His M.S in Pure Mathematics  and Electrical & Computer Engineering from Illinois Institute of Technology, Chicago, IL Illinois Institute of Technology, Chicago, and BS degree from  National School of Electrical Engineering, Computer Science and Telecommunications (ENSEA), France

He is serving as a Professor at  Department of Electrical and Computer Engineering, Rowan University from  Sep. 2013 – present. He worked as Associate Professor (Jul. 2013 – Aug. 2013) and Assistant Professor (Aug. 2007 – Jun. 2013) at Systems Engineering Department, University of Arkansas at Little Rock. He was research assistant  in Multimedia Communications Lab Department of Electrical and Computer Engineering, University of Illinois at Chicago from Aug. 2003- Aug. 2007.

Dr. Ling Wang

Associate Professor

Department of Automation

Shanghai Key Laboratory of Power Station Automation Technology (Mailbox 49), School of Mechatronics Engineering and Automation, Shanghai University, Shanghai, 200072, China


Dr. Ling Wang earned his Ph.D in Control Theory and Control Engineering from East China University of Science and Technology, Shanghai China in 2007 and Bachelors in Automation from the same university in 2002. Since 2007 he is serving as an associate professor in department of Automation of Shanghai University His research interests include; meta-heuristic optimization algorithms, and their applications. The main focus of his work includes; Particle Swarm Optimization, Ant Colony Optimization, Differential Evolution and Quantum Evolutionary Algorithm and their applications to engineering, such as fault diagnosis and intelligent control, currently his research focus is deployment optimization of industrial wireless sensor network, controller design for ultra-supercritical power units. He has more than 50 research publications in impact factor journals and international conferences.


Metaheuristic Approaches in Exploring Smart and Optimized Solutions for Enhancing Energy Efficiency:

Optimization is very important for energy systems, and now metaheuristics are widely adopted to improve the efficiency and effectiveness. The applications of metaheuristic-based approaches are firstly reviewed and few important metaheuristics, like Particle Swarm Optimization, Ant Colony Optimization, Harmony Search, as well as an emergent highly effective algorithm named Human Learning Optimization (HLO), are introduced. The controller design of energy systems based on metaheuristics are specially focused and analyzed, and a novel framework based intelligent data-driven control is then presented which can directly design the optimal controller based on the input and output data without the information of the model. Finally, some real applications are introduced.

Muhammad Khawar Islam                                                                                                 Muhammad Khawar Islam CV 

1. Ph.D Electrical Engineering 1998 University of New South Wales, Sydney,  Australia.
2. M.Eng. Sc. (Dig. Comm.) 1993 University of New South Wales, Sydney,  Australia.
3. B. Sc. Eng. (GOLD MEDAL) 1987 University College of Engineering, Mirpur  (AJ&K.)

Post Doctoral Research:
20th August 2004 to 31 st May 2006, City University of Hong Kong, HONG KONG.
Experience (September 1987 to date)
1. Present position:
4th March 2015 to Date, Professor, (Electrical Engineering), Taibah University,  Kingdom of Saudi Arabia.
2. 1st November 2012 to February 2015, Dean/Director, Faculty of Engineering &  Technology (Professor in Electrical Engineering), University of Gujrat, Pakistan,
3. 22nd July 2010 to 31 st October 2012, Chairman/Professor, Department of  Telecommunication Engineering, University of Engineering & Technology, Taxila,  Pakistan.
4. 10th November 2006 to 21st July 2010, Professor, Software Engineering, University of  Engineering & Technology, Taxila, Pakistan.
5. 1st June 2006 to 8th November 2006, Professor, Electrical Engineering, University of  Azad Jammu & Kashmir, Mirpur Campus, (AJ&K)
6. 20th August 2004 to 31st May 2006, Research Fellow at Optoelectronics Research  Centre, Department of Electronic Engineering, City University of Hong Kong, HONG  KONG.
7. 1st September 2001 to 18th August 2004 , Professor/Chairman Department of  Computer Sciences & Information Technology, University of Azad Jammu & Kashmir,  Mirpur Campus, (AJ&K)
8. September 1987 to August 2001, worked as Lecturer, Assistant Professor and Associate  Professor, University College of Engineering, Mirpur (AJ&K)

He has produced three PhDs under his supervision.

Azhar Fakharuddin

Alexander Von Humboldt Research Fellow  Dept. of Physics, Univ. of Konstanz, Germany

Research Interests

Interfaces and stability of perovskite solar cells,

Optical properties of mixed halide perovskites, Light emitting diodes,                                 Azhar Fakharuddin CV

made of halide perovskites, Nanostructures: designs and properties.

Education and research experience

1. Alexander Von Humboldt Since 1 August 2016 Dept. of Physics, Univ. of Konstanz, Germany Research Fellow (Interfaces in perovskite solar cells)
2. Postdoctoral Research Fellow 1 June 2015-May 2016 Universiti Malaysia Pahang, Malaysia (Organic solar cells)  Doctor of Philosophy Dec 2011-Jan 2015 Universiti Malaysia Pahang, Malaysia (Advanced Materials)
3. Master of Engineering Jul 2009-Sep 2011 Universiti Malaysia Pahang, Malaysia (Electronic)
4. Bachelor of Engineering Mar 2004-Aug 2008 Mehran University of Engineering & Technology, (Electronic) Sindh, Pakistan.

Related Patents

1. Qamar wali, A. Fakharuddin, R. Jose, Z. M. M. Yusoff., “SnO2 Multichannel nanotubes” , patent applied, 2014.
2. R. Jose, A. Fakharuddin, Z. Khalidin, “Nanowires based dye-solar modules”, patent applied. 2014.
3. R. Jose, A. Fakharuddin, Z. Khalidin, M. M. Yusoff, “ A dye sensitized solar cell device”, PI2013000529 (6 March

Reviewer for peer reviewed journals

Reviewing jobs includes high impact peer reviewed journals such as Nanoscale, Scientific Reports, JPCL, Solar
Energy, APL Materials, PCCP, Crystals, and Material Science and Engineering Reports.

“How Can Deep Learning Create a Smarter Grid?”

Dr. Nidhal Bouaynaya, Dept. of Electrical and Computer Engineering, Rowan University


Deep learning  technology is  empowering many aspects of modern society, including web  searches,  social  networking,  recommendation  systems;  and  it  is  increasingly  beingimplemented  in  consumer  products,  such  as  camera  and  smart  phones.  Deep  learning  allowscomputational  models  that  are  composed  of  multiple  processing  layers,  to  learn  nonlinear representations  of  data  with  multiple  levels  of  abstraction,  and  thus  outperform  traditional machine  learning  systems  in  classification  and  prediction  accuracies.  Applications  of  deep learning to  the electric power grid are still embryonic. Historical data  could be capitalized to learn powerful machine learning models to cope with the high uncertainty of the electrical patterns. In this talk,  we will  explore,  in the smart grid context,  the benefits of using Deep Reinforcement Learning, a hybrid type of methods that combines Reinforcement Learning with Deep Learning, to perform  on-line optimization of schedules for building energy management systems   beyond what traditional models would offer.


Dr. Nidhal Carla  Bouaynaya received the B.S. degree in Electrical  and  Computer  Engineering  from  the  National  School  of Electrical  Engineering,  Computer  Science  and  Telecommunications (ENSEA), France, in 2002, the M.S. degree in Electrical and Computer Engineering from the  Illinois Institute of Technology, Chicago, IL, in 2002, the M.S. diploma (DEA) in Signal and Image Processing from ENSEA, France, in 2003, the M.S. degree in Mathematics and the Ph.D. degree in Electrical and Computer Engineering from the University of Illinois at Chicago, Chicago, IL, in 2007. From August 2007 till August 2013,  she  was  an  Assistant  then  Associate  Professor  with  the Department of Systems Engineering at the University of Arkansas at Little Rock, Little Rock, USA. In September  2013,  she  joined  the  Department  of  Electrical  and  Computer  Engineering  at  Rowan University, New Jersey, USA, where she is currently an Associate Professor. Her research interests are in signal, image and video processing, dynamical systems and machine learning. Dr. Bouay naya won the Best Student Paper Award at SPIE Conference on Visual Communication and Image Processing (SPIE  VCIP’06)  in  2006,  the  Best  Paper  Award  at  the  IEEE  International  Workshop  on  Genomic Signal Processing and Statistics in 2013 (GENSIPS’13) and the Runner-up Best Paper Award at the IEEE International Conference on Bioinformatics and Biomedicine in 2015 (BIBM’15). She is also the winner of the UALR Faculty Excellence Award in Research in 2013 and the 2017 winner of Rowan Excellence  Award  in  Research.  Her  research  is  funded  by  the  United  States  National  Science Foundation  (NSF),  United  States  National  Institutes  of  Health  (NIH),  New  Jersey  Department  of Transportation (NJ  DoT),  United  States  Department  of  Agriculture  (USDA)  and  the  United  States Federal Aviation Administration (FAA). She is also interested in entrepreneurial endeavors. In 2017, she  Co-founded and is Chief Technology Officer (CTO) of MRIMATH, LLC, a start-up company in medical imaging.