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3rd International Conference On Information Science & Communication Technology 2025
15 April - 16 April 2025
Venue:
ICCBS Auditorium,University Of Karachi , Auditorium DHA Suffa University
About Us
The University of Karachi holds a unique position in the country’s educational system. As a respected research and reaching institution, it is committed to intellectual leadership, and to excellence in both developing knowledge and conveying that knowledge to its students. The University of Karachi meets the commitments to preserve knowledge through its instructional and research programs for higher level education.
The Department of Computer Science, University of Karachi, was established by a resolution of Academic Council in its meeting, held on November 27. 1984, and it began functioning in the academic year 1985-86 by offering a Degree Program in Master of Computer Science (MCS) and become one of first institutions in Karachi imparting education in Computer Science and Technology. The Department also offers evening program leading to Post Graduate Diploma (PGD) in Computer & Information Sciences. In the year 1995; Department started MCS evening program, on self-finance basis, to cater the growing demand of professionally skilled manpower in the field of Computer Science.
To further strengthen the discipline of Computer Science by producing high quality pro with sound fundamental knowledge. the department has started in the year 1996 and 2001 BS (Computer Science) in the morning and evening, a four year degree program leading to MS (Computer Science), a two year program after completing the BS. MS programs leads to PhD (Computer Science) program. The University of Karachi has excellent supporting faculty in the subjects of Mathematics, Statistics, Physics and other allied subjects for teaching these courses at BS (Computer Science) level. The first batch of BS (Computer Science) of the morning program passed in 1999.
The Department of Computer Science offers a wide range of courses at various levels. The purpose of these courses is to provide opportunities for advanced studies and research in the field of Computer Science and information Technology and related fields, and also to produce highly skilled computer personnel to cater the need of Computer professionals in the country and abroad. The Department maintains high standard of education through continuous assessment and with periodic tests, quizzes, seminars and field projects. The Department maintains close link with professional organizations at national and international levels, to enhance professional and academic standard of the faculty and as well as of the students.
CONFERENCE AIMS AND OBJECTIVES
The International Research Conference is a federated organization dedicated to bringing together a significant number of diverse scholarly events for presentation within the conference program. Events will run over a span of time during the conference depending on the number and length of the presentations.
The ICISCT 2025 event aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of INFORMATION SCIENCE and COMMUNICATION TECHNOLOGY. It also provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of INFORMATION SCIENCE and COMMUNICATION TECHNOLOGY.
KEYNOTE SPEAKERS

Hironori Washizaki
Impact of IEEE Computer Society in Advancing Emerging Technologies including LLM/AI and Software Engineering
Abstract
To be the leading provider of technical information, community services, and personalized services to the world’s computing professionals, the IEEE Computer Society has been strategically providing activities and products related to emerging technologies and professional and educational activities, including the Technology Predictions and the Guide to the Software Engineering Body of Knowledge (SWEBOK Guide). This talk first provides an overview of IEEE CS’s strategic areas, including engaging our members, engaging the industry, and leading new areas such as AI and Society, with the cross-cutting strategic themes, including the empowerment and diversification of our volunteer base, nimbleness in execution, and diversity and inclusion. Then, the talk explains the latest version of the Technology Predictions 2025, which foresees 22 breakthrough technologies (incl. LLM/AI Agents, Mis/Disinformation, AI-based Medical Diagnosis, Next-gen cyberwarfare, and more) to shape the future of our world for decades to come, and the SWEBOK Guide V4.0, which reflects the current state of generally accepted knowledge derived from the interaction between software engineering theory and practice. Furthermore, the talk introduces related endeavors and initiatives, including industry-focused events such as the Generative AI Summit and the SWEBOK Summit, and the engagement and career development opportunities such as the CS Juniors program and professional certification programs.
Profile
Hironori Washizaki is the 2025 IEEE Computer Society (CS) president. He is a professor and the associate dean of the Research Promotion Division at Waseda University. He is a visiting professor at the National Institute of Informatics and an advisor at the University of Human Environments. He also works in the industry as an outside director and advisor at eXmotion and SI&C. He has led professional and educational activities at the IEEE CS, including the evolution of the Guide to the Software Engineering Body of Knowledge (SWEBOK) and the CS Juniors program. He has led many academia-industry joint research and large-funded projects in systems and software requirements, design, reuse, quality assurance, and AI software engineering. He leads a professional IoT/AI/DX education project called “Smart SE.” Since 2015, he has been the convenor of ISO/IEC/JTC1/SC7/WG20 to standardize bodies of knowledge and certifications in systems and software engineering. He has been the IPSJ SIG Software Engineering (SIGSE) chair since 2021

Prof Mariofanna Milanova
At the Intersection of Generative AI, Human Augmentation, and Innovations
Abstract
The talk presents the integration and synergy between generative AI, human augmentation, and technologies. It effectively conveys advanced, innovative concepts, appealing to an audience interested in the future of AI and technology. Every participant will receive a complimentary code from NVIDIA to test the models
Profile
Professor of Computer Science at the University of Arkansas, Senior Member of IEEE, NVIDIA Certified Instructor for Deep Learning
Dr. Mariofanna Milanova is a professor in the Department of Computer Science at UA Little Rock and has been a faculty member since 2001. She received a M.Sc. in Expert Systems and Artificial Intelligence and Ph.D. in Engineering and Computer Science from the Technical University, Sofia, Bulgaria. Dr. Milanova conducted post-doctoral research in visual perception at the University of Paderborn, Germany. Dr. Milanova has extensive academic experience at various academic and research organizations worldwide.
Dr. Milanova is an IEEE Senior Member, Fulbright U.S. Scholar, and NVIDIA Deep Learning Institute University Ambassador. Dr. Milanova’s work is supported by NSF, NIH, DARPA, DoD, Homeland Security, NATO, Nokia Bell Lab, NJ, USA and NOKIA, Finland. She has published more than 130 publications, over 53 journal papers, 45 book chapters, and numerous conference papers. She also has two patents

Dr Atif Siddiqui
Data Analytics through Machine Learning and its impact on Manufacturing Industry
Abstract
Lead Engineer Test System, Airbus Defence and Space, UK and visiting faculty department of Computing and Mathematical Sciences, University of Greenwich, UK
A highly motivated, skilled and result oriented technical leader with more than 26 years of diverse work and geographical experience in electronics and telecom industry. Proficient in designing and implementing test systems along with managing multi-functional teams, delivering successful projects within strict timelines. Offer strong work ethics, with focus on detail orientation including industry communication standards, stakeholder management and agile project management. Established track record of streamlining and implementing agile practical solutions with focus on continuous improvement and performance matrices. Currently focused on application of Machine Learning to solve industrial problems in Aerospace industry.

Dr. Kashif Nisar
Artificial Intelligence and Security in Federated Learning Enabled 6G Era
Abstract
Software-Federated Learning (FL) is an emerging Artificial Intelligence (AI) paradigm that enables multiple parties to collaboratively train a model without sharing their data. With the upcoming Sixth Generation (6G) era, FL is expected to adapt a more prevalent role as a potential solution to overcome the challenges of data privacy, AI, security and scalability in distributed and heterogeneous systems. Presently, research works in the security domain of FL enabled 6G communication are widely pursued. However, the outcome of research efforts is critically dependent upon the concepts and platforms used during analysis and evaluation. Therefore, this study initiates by focusing on the requirements of analysis in the security of distributed and heterogeneously involved multiple entities in FL enabled 6G. Thereby, this study comprehensively reviews and identifies the potential Conceptual Techniques and Software Platforms for analysis and evaluation in security-related areas of FL enabled 6G communication. Further, this study highlights major challenges faced during the analysis in the security of FL enabled 6G. Finally, this review deliberates upon the potential open research issues AI, security, and that can be pursued using the identified techniques and platforms.
Profile
Dr. Kashif Nisar has done Post-Doctoral from Auckland University of Technology, Auckland, New Zealand. Before, he completed his PhD as a candidate with fully funding at the Universiti Teknologi PETRONAS, Malaysia. Through his major in Computer Network and Information Technology; he has obtained solid training in Research and Development (R&D), writing funding proposal, journal publication, and as a consultant. Currently, Dr. Nisar is serving as a Lecturer at the University of Notre Dame, Sydney Campus, New South Wales, Australia. In 2014, he has served as a Guest Professor at Fernuniversität Hagen, Germany, fully funded by DAAD. He holds a number of visiting professor positions in well-known universities such the McMaster University, Hamilton, ON, Canada, University of Auckland, New Zealand, Hanyang University, South Korea, and Waseda University, Tokyo, Japan. Dr. Nisar has been published 250+ research papers in many high impact journals and well reputed international conferences proceeding in the area of Computer Network. His research interests include Future Internet (FI), Artificial Intelligence (AI), Information Centric Network (ICN), Content-Centric Networking (CCN), Fourth Industrial Revolution (IR 4.0), Quantum Network, Information Security & Privacy, Network/Cyber Security, Digital Forensics, Applied Cryptography, Vehicular Clouds, Cloud & Edge Computing, and Blockchain. Currently, he is working on Future Networks, IoT security and API security and he is also working closely with Industry. Dr. Nisar is the member of many professional organizations from academia and industry including Senior Member of IEEE (Founding IEEE Vice-Chair, Subsection), member of ACM, ACM-SIGMOBILE, ISOC, Engineers Australia, IAENG, Park Lab etc. and a fellow of APAN and ITU. Dr. Nisar is serving as an editorial board member for various journals including Computer Communications Elsevier, IEEE Internet Initiative, Wiley, and serves as reviewer for most of the IEEE transactions, IEEE Access, IEEE IoT, Springer and Elsevier Journals. He also serves as technical program committee member of various conferences such as IEEE GLOBECOM, IEEE R10 TENCOM, IEEE TrustCom, IEEE ICC, IEEE VTC, IEEE VNC, IEEE ICCVE, ICCCN, and so on. Also, he is serving as a guest editor for more than a dozen special issues in journals and magazines such as IEEE, Elsevier, Springer and Wiley.
Abstract
Artificial Intelligence and Security in Federated Learning Enabled 6G Era
Software-Federated Learning (FL) is an emerging Artificial Intelligence (AI) paradigm that enables multiple parties to collaboratively train a model without sharing their data. With the upcoming Sixth Generation (6G) era, FL is expected to adapt a more prevalent role as a potential solution to overcome the challenges of data privacy, AI, security and scalability in distributed and heterogeneous systems. Presently, research works in the security domain of FL enabled 6G communication are widely pursued. However, the outcome of research efforts is critically dependent upon the concepts and platforms used during analysis and evaluation. Therefore, this study initiates by focusing on the requirements of analysis in the security of distributed and heterogeneously involved multiple entities in FL enabled 6G. Thereby, this study comprehensively reviews and identifies the potential Conceptual Techniques and Software Platforms for analysis and evaluation in security-related areas of FL enabled 6G communication. Further, this study highlights major challenges faced during the analysis in the security of FL enabled 6G. Finally, this review deliberates upon the potential open research issues AI, security, and that can be pursued using the identified techniques and platforms.

Prof Dr Enrique Nava
Developing applications with 3D depth digital image processing
Abstract:
3D digital image processing techniques are now routinely used in many applications: medical imaging, environmental assessment, remote sensing, etc. In this paper, we will present some new trends, involving the use of new technology depth cameras with a very broad range of new applications, including gesture recognition and hand tracking, 3d modeling, metaverse, underwater video processing and hyperspectral remote sensing. Using 3D depth cameras, we obtain sparse point cloud data which imposes some new needs on research to be solved for building new applications. The aim of this talk is to present some basic and new ideas to inspire new research in this area, as well to present actual research projects in this field.
Profile:
Prof Dr Enrique Nava finished his PhD thesis under supervision of Prof. J.M. Rebollar on the design of circular waveguide polarizer devices on microwaves/millimiter waves to be used on communication satellite antennas. As a result, a new developed computer software, based on a full solution of electromagnetic equations, was able to predict polarizer behaviour with enough accuracy to be used on industrial optimization and design purposes. This software was the only one available at that time and was transferred to relevant research institutions and companies on that field (eg. INTA) for industrial use. After obtaining a position as Associate Professor (Profesor Titular de Universidad) at University of Málaga in 1994, I’ve focused my research work on interdisciplinary applications of digital signal and image processing, with many collaborations on medical, chemical, biological, industrial fields. Since 1995, I’m the head of the Andalusian research group ‘Radiological Image Digital Processing’ (TIC128), with eight post-doctoral researchers on Engineering and Medicine background. I finished many foreign research stays: Kurt Rossmann Lab (2000), at University of Chicago (USA), working on mammography computer-aided diagnosis algorithm development; at for Institut für Technische Akustik (2011 and 2014) at RWTH (Aachen, Germany), working on advanced array processing techniques for location of acoustic sources; at University of New South Wales (UNSW@ADFA, 2012, Camberra, Australia) working in digital signal processing applied to biotremology in termites and ants; and on oceanographic research ships (Spanish Institute of Oceanography, IEO (MEDIAS campaign, 2015 and 2017), working on acoustics and digital image processing for fisheries research. I’ve active collaborations in research with different national and international research groups: University of Malaga UMA Analytical Chemistry Group (pesticides in food quantification), Italian INFN-LNF group (X-ray microtomography new prototype), Romanian LAPI at Polytechnic University of Bucharest group (digital image processing), Prof. Moreno-Torres at UMA (acoustic phonetics applied to medical applications), several Pakistan universities (image and signal processing) and LAV University of Cadiz group (underwater acoustics). I’m a member of NEUBIAS (Network of European BioImage Analysts to advance life science imaging), a COST network focused on microscopy bioimage analysis. Since 2019 to now, I was lecturing a course on digital signal processing to students of University of Pingdingshan, China. From 2019, I’m acting as coordinator of several Erasmus+ programmes between University of Málaga and some Asian countries (Pakistan, India, Nepal, Afghanistan) for mobilities and capacity building. From 2024 I’m acting also as Deputy Vicechancellor for Strategical Projects at the Unviersity of Malaga.

Dr. Bhagwan Das
Dr. Bhagwan Das
Abstract
In an era marked by climate change and increasing humanitarian crises, the need for integrated solutions has never been more urgent. This keynote addresses the intersection of climate literacy and technological innovation, highlighting how informed communities can leverage cutting-edge tools to enhance their resilience and response strategies. Drawing on case studies from around the globe, we will explore successful initiatives that have utilized data analytics, remote sensing, and community engagement to tackle the multifaceted challenges posed by climate change. By fostering a deep understanding of climate dynamics, we can empower individuals and organizations to act decisively and effectively in times of crisis. Participants will leave with actionable insights on developing climate literacy programs that incorporate technology, building collaborative frameworks that unite stakeholders from diverse sectors, and creating scalable solutions that respond to the specific needs of vulnerable communities. Together, we can transform knowledge into action, driving impactful humanitarian efforts that adapt to and mitigate the effects of our changing world. Join us in this critical conversation to redefine the future of humanitarian aid in a climate-impacted landscape.
Profile
Currently, Dr. Bhagwan Das is working as Senior Research Fellow at Melbourne Institute of Technology, Australia. Dr. Bhagwan Das succeed to achieve a patent and achieved 8 copyrights for his research and innovation. Dr. Bhagwan Das is the recipient of BEST MAN INVENTOR 2016 award given by International Federation of Inventors Associations (IFIA), Geneva, Switzerland. He won COMMERCIAL AWARD given by Universiti Tun Hussein Onn Malaysia (UTHM) in 2016. He also received SPECIAL AWARD from Malaysian Research & Innovation Society (MyRIS) in iMIT SIC 2017 at UUM, Kadeh, Malaysia. He has published more than 100 articles in reputed ISI impact factor journals and in conferences. He is member of professional bodies, Fellow Member- Engineer Australia, Member-Pakistan Engineering Council, Member-Pakistan Engineering Congress, Senior Member-IEEE (USA), Member-IFIA (Switzerland). Dr. Bhagwan Das is Senior IEEE Member. He remain Chair, IEEE Computer Society 2020-2023, Secretary, IEEE IES 2021-2023. His area of research includes Climate Literacy, Internet of Things, AI and Data Sciences.

Prof Arthur James Swart
Title :Using Informetrics to gain salient insights into Doctoral thesis over a 5-year period
Abstract
The successful completion of a PhD study is a noteworthy achievement that few people in the world experience. It represents the pinnacle of academic studies at a university which opens the doors to several opportunities. Despite the benefits associated with a PhD degree, it remains a daunting task. The purpose of this study is therefore to present an analysis of 72 PhD theses that were completed over a 5-year period (2014 – 2018) at the Central University of Technology (CUT), Free State, to help prospective doctoral candidates to better understand what is required, or acceptable, at this level of research. It can further create awareness among researchers in Higher Education about the type of research that was completed at CUT over this period. An ex-post facto study is employed where informetric analysis is used to obtain quantitative data. Key results indicate that 61% of the PhD students worked under the guidance of two or more promotors. 44% of the theses contained between 200 and 300 pages, with none below 100. PDF file sizes varied from less than 2 MB to more than 12 MB. A recommendation is made to create awareness among prospective doctoral candidates of the results of this study, further encouraging them to also include a sentence in their abstracts that clearly defines the scientific contribution of their study.
Profile
James completed a National Diploma in Electrical Engineering at a local technical college in Bloemfontein in 1993, while working as an apprentice for a national telecommunications company in South Africa (SA). He then joined the Vaal University of Technology as a laboratory technician in 1995 and was promoted to a Senior Lecturer in 2007 after obtaining a Masters in Education. James obtained a Doctorate in Electrical Engineering in 2011 and then moved to the University of South Africa in 2013, the largest distance-learning institute in Africa. In 2014, he joined the Central University of Technology, where he currently serves as an Associate Professor in the field of Electrical Engineering and as the Principal Research Leader for a Research Group in Engineering Education where he focuses on the Scholarship of Teaching and Learning.
James has over 30 years of academic experience, 5 years of Industry experience and more than 200 publications. He is currently registered as a Professional Engineering Technologist with the Engineering Council of South Africa (ECSA) and is a rated scientist with the National Research Foundation (NRF) of SA. James obtained a Commendation for Teaching from the Council of Higher Education (CHE) of SA in 2015 and served as the Treasurer for the South African Society of Engineering Education (SASEE) between 2017 and 2019.
He has presented many motivational presentations at different universities in India and spent a week lecturing in Bangalore during 2024. His greatest assets are academic writing, mentorship and public speaking.

Prof hui Wang
Machine learning for virus detection in a viral infection outbreak.
Abstract
COVID-19 is still here, and the world is still living in the cloud of the global epidemic. Measures of epidemics management are still in place in many places in the world, which include (1) prevention (lockdown, social distancing, face masks, vaccine) (2) detection (testing and diagnostics) (3) response (isolation, therapeutics). Virus detection is an important means to manage an epidemic. Gold standard methods are reliable but are typically costly and time consuming; alternative methods are cheaper and faster but are typically less reliable. UK EPSRC has funded a study on virus detection using spectroscopy and machine learning. If successful, it will provide the basis for developing new virus testing systems that are cheaper and faster (than gold standard methods) but also reliable. This talk will present an overview of epidemics management measures, the findings from this UK EPSRC funded project on virus detection, and an outlook on the role of artificial intelligence in future epidemics management.
Profile
Biography of speaker: Hui Wang is Professor of Computer Science in Queen’s University Belfast. Prior to that, he was Professor of Computer Science in the School of Computing, Ulster University, where he led the Artificial Intelligence Research Centre (2009-2021) and was Research Director (2018-2020). He obtained his PhD in Artificial Intelligence from Ulster University, MSc and BSc in Computer Science from Jilin University, China.
He is Principal Investigator of a number of regional, national and international projects in the areas of image/video analytics (EPSRC funded MVSE 2021-2024, Horizon 2020 funded DESIREE and ASGARD, FP7 funded SAVASA, Royal Society funded VIAD), spectral data analytics (EPSRC funded VIPIRS on virus detection 2020-2022), text analytics (INI funded DEEPFLOW, Royal Society funded BEACON), and intelligent content management (FP5 funded ICONS); and is co-investigator of several other funded projects. He is an associate editor of IEEE Transactions on Cybernetics, founding Chair of IEEE SMCS Northern Ireland Chapter (2009-2018), and a member of IEEE SMCS Board of Governors (2010-2013).
His research interests are machine learning, knowledge representation and reasoning, and their applications in image, video, spectra and text data analyses. Notable contributions include lattice machine (an algebraic framework for machine learning by generalisation and knowledge representation), contextual probability (a perceptionist formulation of probability), and neighbourhood counting (a generic similarity measure that can be specialized to any form of data including multivariate data, sequences, tree and graph structures). His current focus is detection learning and knowledge-based learning.

Mohamed Rawidean Mohd Kassim
The Application of Internet of Things (IoT) and Wireless Sensor Network (WSN) in Smart Agriculture
Abstract
IoT and WSN technologies are widely used to build decision support systems to overcome many problems in the real world. One of the most interesting fields having an increasing need for decision support systems is Smart Agriculture (SA). This project presents WSN as the best way to solve the agricultural problems related to farming resources optimization, decision-making support, and land monitoring. This approach provides real-time information about the lands and crops that will help farmers make the right decisions. Using the basic principles of Internet and WSN technology, SA systems based on the IoT technology is explained in detail, especially on the hardware architecture, network architecture and software process control. The software monitors data from the sensors in a feedback loop, which activates the control devices based on threshold value. Implementation of WSN in SA will optimize the usage of resources such as water fertilizer and maximize the yield of the crops.
Profile
Mohamed Rawidean Mohd Kassim has worked for 35 years in MIMOS (Malaysian Institute of Microelectronic Systems), the Ministry of Science, Technology and Innovation Malaysia. MIMOS is the government applied and industrial R&D arm in IT and microelectronics. He joined MIMOS as a Research Fellow and now is the R&D Manager in the Technology Deployment department. His research interest areas are Wireless Sensor Network (WSN), Internet of Things (IoT), Real-Time Systems and Multimedia. He has participated in more than 30 national and international R&D projects as a team member, or leader on technical and management positions. Mohamed Rawidean is an IEEE Senior Member. Currently, he is the Regional Coordinator, Region 10, IEEE Computer Society. He was the IEEE Computer Society Malaysia Chapter Chair from 2002 to 2013. As a lecturer, he has given computer science courses for undergraduate and graduate students. He has written conference papers, one book chapter (‘Sensors for Everyday Life’, Springer Pub., 2017) and technical reports. He is also a member of the Industry Advisory Panel (IAP) for Monash University Malaysia and Universiti Kuala Lumpur (UniKL). Mohamed Rawidean has organized IEEE national and international conferences, seminars and workshops. He is the Founding Chairman for IEEE Conference on Open Systems (ICOS), Program Chair and Technical Program Chair for several IEEE conferences. He has provided many keynotes, invited industrial talks and workshops in WSN, Intelligent Real-Time Systems and IoT. He has eight patents registered under his name, mostly in wireless sensors, networks and sensor applications. He received his B.Sc. (Hons) degree in the Computer Sciences (1987) from National University of Malaysia, and his M.Sc. in Interacting Systems Design (1993) from Loughborough University of Technology, United Kingdom. He obtained his Six Sigma Black Belt in 2009 from Motorola University.

Zhi Jin
Software Requirements Engineering for Complex Embedded Systems
Abstract:
With the development of IoT technology, embedded software systems are becoming more and more complex. Compared with general software systems, complex embedded systems typically have the characteristics of strong correlation of task intent, strong dependence on physical devices and execution logic interweaving, etc. The bottlenecks of efficient development of complex embedded software systems include systematically representing system design intent, decoupling complex requirements, and extracting fine-grained operational software requirements. Guided by the requirements engineering method based on environmental modeling, this talk systematically constructs the requirements engineering methodology for embedded software systems, including the projection-based method for requirements specification, and the transformation strategies from task intent to software requirements. This talk will also present the practice of this approach in specific cases.
Profile:
Zhi Jin is professor of computer science at Peking University. She is the deputy director of Key Lab of High Confidence Software Technologies (PKU), Ministry of Education, China. Her main research interest is AI for SE, with a long-term focus on domain knowledge-led requirements engineering. She has published over 300 scientific articles in refereed international journals, such as IEEE T-KDE, T-SE, ACM T-OSEM, and T-CPS, and high rank conferences, such as ICSE, FSE, ASE and RE. She has co-authored five books and has held more than 20 approved invention patents. She is five times recipient of ACM SIGSOFT Distinguished Paper Awards.
Prof. Jin serves as an Associate Editor of IEEE Transactions on Software Engineering, IEEE Transactions on Reliability, and ACM Transactions on Autonomous and Adaptive Systems, and serves on the Editorial Board of Requirements Engineering Journal and Empirical Software Engineering. She has won the first prize of Science and Technology Progress Award of the Ministry of Education, the first prize of CCF Technological Invention Award, the second prize of Beijing Technological Invention Award. She is also honored CCF Outstanding Achievement (Xia Peisu) Award, IEEE TCSVC Outstanding Leadership Award, and Zhongchuang Software Talent Award. She is Fellow of IEEE, CCF and AAIA.
INVITED SPEAKERS

Prof. Dr. Yasar Ayaz
Prof. Dr. Yasar Ayaz
Abstract
He is the Founding Chairman and Central Project Director of Pakistan’s National Center of Artificial Intelligence (NCAI) headquartered at National University of Sciences and Technology (NUST) in Islamabad. He also founded Pakistan’s first Department of Robotics & Artificial Intelligence at NUST in 2010 which he headed from June 2010 to August 2020 and where he is also currently a full Professor. He also holds the prestigious title of Specially-Appointed Professor title at Tohoku University, Japan and has been assisting the university in various roles especially for selection of new international students from Pakistan since 2015. He is also the Vice President of Monbukagakusho Alumni Association of Pakistan (MAAP).
Profile
Prof Yasar is the author of over 150 international publications and has won international best paper awards in London, UK and Sydney, Australia in 2018 and 2013 respectively. He also has 3 product design patents registered in his name with several more under review. He has delivered more than 60 invited and keynote talks at prominent venues including USA, Japan, UK, South Korea, China, Italy, Belarus, Norway etc and has won and developed projects of well over Two Billion Pakistan Rupees including international grants and national consortium based projects. In addition to winning President’s Gold Medal, University Best Teacher Award, SMME Best Researcher Award and University Top Performer award at Pakistan’s top university: NUST, Prof Yasar has also been awarded the prestigious Pakistan Engineering Council (PEC) Engineers’ Excellence Award and Gold Medal in 2020. He has been awarded Lifetime Achievement Award by IEEE Islamabad Section and is also a recipient of President’s Award for Pride of Performance which is one of the highest Civil Awards of Pakistan conferred by the Honorable President of Pakistan himself in 2021 and conferred with BRAIN Award 2022-23 for NUST Top Performer 2022 by Rector NUST in 2024

Mehar Ullah
Dr. Mehar Ullah
Abstract
Dr. Mehar Ullah is a Postdoctoral Researcher at LUT University in Lappeenranta, Finland, specializing in the integration of the Internet of Things (IoT), edge computing, and big data within cyber-physical systems. His research focuses on enhancing information flow in smart grids and developing frameworks for IoT platform selection applicable to various industrial applications, including carbon fiber recycling and industrial energy management systems.
His recent research includes studies on cybersecurity in the hydrogen economy and the development of unified frameworks for IoT platform selection in Power-to-X cogeneration plants.
He earned his Doctor of Engineering degree from LUT University, where his dissertation focused on the digitalization of various industrial sectors through IoT applications.
Dr. Ullah’s expertise encompasses information and communication technology, cloud computing, and information management. He is actively engaged in advancing the role of IoT in cyber-physical systems, aiming to improve efficiency and sustainability across different industries.

Dr. Vaidas Giedrimas
AI-enhanced Crowdsourcing as an Element of Information Systems Development
Abstract
he Information Systems Development process consists of a few elements, which may look contradictory at first sight. On the one hand, we reached huge progress in automated software development. It is possible to make a priori correct large-scale distributed software using formal methods. On the other hand, the enthusiasts of crowdsourcing and the participants of open source projects emphasize the importance of the human factor. The authors of this paper believe that in computer science the composition of crowdsourcing and automated software development is possible as in other sciences where two or more former competitive theories eventually complement each other. Moreover, it leads to synergy. The conceptual framework of the methodology for crowdsourcing-based software development incorporating artificial intelligence elements is discussed in this presentation.
Profile
Dr. Vaidas Giedrimas is an Associate Professor and Head of the ICT Research Group at Panevėžys University of Applied Sciences (PANKO), Lithuania, and a faculty member at Vilnius University Šiauliai Academy (Lithuania). He specializes in distributed software systems, including grid, cloud, edge, and mobile computing, component-based software engineering, and service-oriented architectures. A highly sought-after speaker, Dr. Giedrimas has delivered keynote addresses at numerous international conferences, including ICCTSAI 2021 (UK), ICISCT 2017 (Uzbekistan), AICT 2013 (Azerbaijan), and ISD 2014 (Croatia). His expertise in software engineering, digital forensics, and computational methodologies, combined with his ability to present complex topics in an engaging and interdisciplinary manner, has earned him recognition as a thought leader in the field. Dr. Giedrimas is actively involved in international research collaborations, serving as a Management Committee member for European COST Actions such as DigForAsp (Digital Forensics), BETTY (Behavioural Types for Reliable Large-Scale Software Systems), and Reversible Computation). He also represents Lithuania on the NorduGrid Collaboration Board, contributing to advancements in high-performance computing.”
