Advancing the Frontiers of Computational Intelligence

• Encouraging cutting-edge research and novel methodologies in computational intelligence, spanning neural networks, evolutionary algorithms, fuzzy systems, and hybrid intelligent models.
• Exploring transformative applications of AI and ML in diverse sectors such as healthcare, finance, cybersecurity, robotics, smart cities, agriculture, and industrial automation.
• Bringing together researchers, academicians, industry professionals, and practitioners to exchange ideas, share expertise, and promote meaningful cross-domain collaborations.
• Deepening the understanding of core theoretical foundations, including mathematical models, learning algorithms, optimization strategies, and computational frameworks that drive next-generation AI systems.
• Promoting informed discussions on responsible and ethical AI, with emphasis on fairness, transparency, interpretability, security, and the broader socio-ethical implications of intelligent technologies.
• Providing a dynamic platform for students and early-career researchers to present their work, receive constructive feedback, and cultivate strong professional and research networks.”

ICFAI Foundation for Higher Education (IFHE)

• The ICFAI Foundation for Higher Education is a deemed-to-be-university established under Section 3 of the UGC Act, 1956.
• IFHE's comprehensive student-centric learning approach provides relevant knowledge, imparts practical skills, and inculcates a positive attitude among the students.
• Today, the IFHE is one of the largest multi-disciplinary universities in the country.
• The ICFAI Business School, Faculty of Science and Technology, Faculty of Law , ICFAI School of Architecture, ICFAI School of Social Sciences and Center for Distance and Online Education are the six core academic schools of the university
• IFHE has been permitted by the Ministry of Education, Government of India, to start an Off-Campus Center at Bangalore, Karnataka.
• The University is a member of the Association of Indian Universities (AIU) and the Association of Commonwealth Universities (ACU).
• The University offers students the best and updated curriculum and trains them for rewarding careers.
• It promotes a culture of research that advances knowledge in the field of management, technology, law, architecture, and social sciences.
• IFHE is a Category I Autonomous Institution, and Accredited by NAAC with 'A++' Grade

Faculty of Science and Technology (IcfaiTech)

Faculty of Science and Technology (IcfaiTech), Hyderabad, is a constituent of the ICFAI Foundation for Higher Education. It has been established to promote quality education in the field of Science and Technology. IcfaiTech strives to acquire a reputation as a highly purposeful and innovative institution, setting the pace for workable reforms in professional education that are suitable and most relevant to the Indian cultural milieu.

The core philosophy of education at IcfaiTech is to empower students with the proper knowledge and modern skill sets, so that they are ready to face the challenges of the competitive world. IcfaiTech strives to provide its students with the fine edge required to make a successful professional. The programs at IcfaiTech have been uniquely designed by incorporating courses from diverse areas, including humanities, arts, and management, combined with science, engineering, and industry- based internships. IcfaiTech ensures that students gain exposure and knowledge across different disciplines, develop inter-personal skills and leadership qualities that take them beyond traditional thinking and practice.

The educational philosophy and practices at IcfaiTech allow it to integrate an innovative and emerging body of knowledge into its learning system. The highlights of the academic program are summarized below:

• Cutting-edge course curriculum with contemporary and effective pedagogic methods that emphasize application-oriented learning.
• Encouraging students to not only articulate Science and Technology needs but also provide appropriate solutions.
• Developing appreciation for synthesized multidisciplinary learning by way of workshops, internships, and other group learning assignments

Computer Science & Engineering (CSE) and Artificial Intelligence & Data Science (AI&DS) Departments

The Department of Computer Science & Engineering (CSE) and Artificial Intelligence & Data Science (AI&DS) are research-focused academic unit committed to excellence in advanced computing and intelligent technologies. The two departments collectively offer B.Tech. (CSE, CSE-Cloud Computing, CSE-Cybersecurity, CSE- Blockchain, Cybersecurity, IoT), B.Tech. (AI, AI-DS, AI-ML), and M.Tech. (AI-ML), BCA (AI-ML, AI-DS), B.Sc. (CS/DS), and a strong Ph.D. program that nurtures high- impact research. With a distinguished team of 60+ highly qualified faculty members, comprising professors, researchers, and industry practitioners with diverse expertise in AI/ML, deep learning, NLP, cybersecurity, Blockchain technologies, IoT, cloud computing, distributed systems, high-performance computing, and intelligent data-driven applications. The department drives innovation through strong research contributions and industry collaborations. A vibrant community of 4000+ students enriches a dynamic ecosystem of learning and problem-solving. Modern laboratories, research centers, and incubation facilities support hands-on exploration, applied research, and product development. The department's consistent publications in SCI/Scopus venues and interdisciplinary initiatives position it as a leading hub for emerging technologies and future-ready talent.

Key Department Initiatives

• Organizes national and international conferences, seminars, workshops, and technical conclaves in emerging areas such as AI, Data Science, Cybersecurity, Blockchain, and Cloud Computing.
• Publishes high-quality research articles, book chapters, patents, and technical reports in collaboration with faculty, scholars, and students.
• Collaborates with industry partners, research laboratories, professional bodies, and global organizations to promote joint projects, internships, certifications, and skill development programs.
• Conducts training programs, coding boot camps, hackathons, and hands-on workshops to strengthen practical skills in AI, ML, IoT, full-stack development, and data analytics.
• Encourages student and faculty participation in multidisciplinary projects, innovation challenges, and funded research initiatives that address real-world problems.
• Promotes entrepreneurship, start-up culture, and product innovation through incubation support, ideation camps, and mentoring by industry experts.

Centre of Excellence in Blockchain

The Center of Excellence in Blockchain at the Faculty of Science and Technology (IcfaiTech) aims to drive high-impact research in Blockchain, smart contracts, and distributed ledger technologies, while fostering innovation through patents, publications, and funded projects. It leverages state-of-the-art labs and industry-grade platforms to support experimental research, strengthens collaborations with industry and academic partners for joint development, and nurtures skilled researchers through mentoring, specialized training, and hands-on learning opportunities.

Call for Papers:

The International Conference on Advancements in Computational Intelligence and Machine Learning (ICACIML 2026) invites high-quality research contributions from academicians, researchers, industry practitioners, and scholars across the globe. The conference aims to provide a premier interdisciplinary platform for presenting cutting-edge innovations, discussing emerging trends, and addressing real-world challenges in the fields of Artificial Intelligence, Machine Learning, Data Science, and Computational Intelligence.

We welcome original, unpublished research papers, case studies, survey articles, and industry practice reports in (but not limited to) the following thematic areas:

Track 1: Machine Learning, Deep Learning & Neural Networks

• Supervised, Unsupervised, Semi-supervised learning methods
• Reinforcement Learning, Multi-agent RL, Bandits
• Probabilistic and Bayesian models
• Feature engineering, feature selection, dimensionality reduction
• Optimization methods (convex / non-convex / gradient-free / meta-optimization)
• AutoML, model selection, hyper-parameter tuning
• Explainable & interpretable ML (XAI), model auditability
• Time-series prediction, forecasting, temporal-data ML
• Scalable and efficient ML systems & large-scale deployment
• Transformer architectures, attention models, foundation models
• Convolutional Neural Networks (CNNs) and computer-vision deep learning
• Recurrent Neural Networks (RNNs), LSTM/GRU, sequence modelling
• Graph Neural Networks (GNNs) and deep learning on graphs
• Generative Models: GANs, VAEs, Diffusion Models, Generative AI
• Neural Architecture Search (NAS), Auto-DL
• Edge-AI / TinyML / on-device deep learning
• Multimodal learning (image-text, audio-text, video-text, etc.)
• Optimization techniques in deep learning: regularization, efficient training
• Responsible & trustworthy deep learning: fairness, robustness, ethics

Track 2: Natural Language Processing (NLP)

• Large Language Models (LLMs), fine-tuning, adapter methods, prompt-engineering
• Text classification, summarization, information extraction
• Question Answering, dialog systems, conversational AI, chatbots
• Machine Translation (neural MT), multilingual and low- resource languages
• Sentiment analysis, emotion detection, opinion mining
• Speech processing, speech-to-text, spoken language understanding
• Document understanding, retrieval, search, IR + NLP
• Code-mixed language processing, especially for regional languages (e.g. Indian languages)
• Ethics, bias, fairness and interpretability in NLP
• Applications of NLP in domains such as healthcare, education, law, social media

Track 3: Swarm & Evolutionary Computation

• Genetic Algorithms (GA), Genetic Programming (GP), Evolutionary Strategies
• Particle Swarm Optimization (PSO), Ant Colony Optimization, Bee/Firefly/Other Swarm methods
• Hybrid algorithms: combining evolutionary / swarm methods with ML / DL techniques
• Multi-objective optimization, Pareto-optimal solutions, trade-offs
• Evolutionary Game Theory, multi-agent optimization, co- evolution
• Bio-inspired and nature-inspired computing / optimization
• Swarm robotics, distributed intelligence, self-organizing systems
• Heuristics and metaheuristics for real-world problems (optimization, scheduling, resource allocation, IoT, network optimization)
• Benchmarking, performance evaluation, comparative studies of evolutionary methods

Track 4: ML for Cybersecurity, Healthcare & Emerging Applications

A . ML for Cybersecurity

• Intrusion detection, anomaly detection, network security using ML
• Malware, ransomware, phishing detection and prevention using ML/DL
• Adversarial ML, robustness, secure ML models
• Privacy-preserving ML: federated learning, secure ML, privacy-enhancing tech (e.g. differential privacy, ZKPs)
• Blockchain + ML / Hybrid security-ML frameworks

B. ML for Healthcare & Biomedical Applications

• Medical image analysis (X-Ray, MRI, CT, ultrasound) using ML/DL
• Predictive healthcare analytics, risk scoring, prognosis models
• Remote monitoring via wearables, IoT-based health monitoring, time-series health data
• Clinical decision support systems, diagnostic assistance, prognosis, disease detection
• Drug discovery, genomics / bioinformatics, computational biology using ML
• Explainable & interpretable ML in healthcare decisions (transparency, ethics)

C. ML in Other Emerging Domains & Cross-Cutting Applications

• AI / ML for Smart Cities, IoT-enabled systems, transportation, logistics
• ML for environment, climate modelling, sustainability, resource optimization
• ML in FinTech, fraud detection, financial forecasting
• ML for education: learning analytics, adaptive learning, assessment & evaluation
• AI governance, ethics, policy, fairness, societal impact of ML

Track 5: AI-Driven Business Transformation: Analytics, Digital Innovation, and Sustainable Management Practices

• Predictive Business Analytics & Decision Intelligence
• Digital Transformation, Industry 4.0 & Innovation Management
• FinTech, Risk Analytics & Blockchain Applications
• Marketing Analytics, Consumer Insights & Social Media Mining
• Human Resource Analytics & Future of Work Models
• Healthcare Analytics & Digital Health Systems
• Sustainability, ESG Analytics & Green AI
• AI Governance, Ethics & Policy in Management

Track 6: Intelligent IoT for Smart Manufacturing

• Low-power embedded system design for industrial IoT devices
• Advanced MEMS/NEMS sensors for manufacturing applications
• VLSI and ASIC architectures for high-speed IIoT data processing
• Edge AI hardware accelerators for factory automation
• 5G/6G-enabled real-time communication for manufacturing systems
• Hardware-level cybersecurity for IIoT devices (PUF, secure boot, TPM)
• IoT-enabled robotics control hardware and sensor fusion platforms
• Robust hardware design for extreme temperature and vibration environments

Author Instructions

Paper Template

ICACIML-2026 Review Policy

At the International Conference on Advancements in Computational Intelligence and Machine Learning (ICACIML-2026), we are committed to upholding the highest standards of integrity, quality, and transparency in our review process. Every submission is evaluated with fairness, rigor, and strict adherence to ethical practices.

1. Evaluation Criteria Submissions are assessed based on scholarly merit, originality, alignment with conference themes, and compliance with submission guidelines and industry standards.
2. Expert Review
   Papers are reviewed by subject-matter experts possessing relevant domain expertise.
3. Double-Blind Peer Review
   ICACIML-2026 adopts a double-blind review process where the identities of both authors and reviewers remain confidential.
4. Confidentiality
   Reviewers and editors are prohibited from sharing or discussing submissions outside the review process. This safeguards unpublished ideas and results.
5. Conflict of Interest
   Any identified conflict of interest will result in reassignment of the submission to an alternate reviewer to maintain impartiality.
6. Ethical Responsibility
   Reviewers must report suspected cases of plagiarism, conflicts of interest, or undisclosed funding sources. Such cases will be escalated to the conference’s ethics committee.
7. Review Panel
   Each paper will be evaluated by three independent reviewers. Consolidated reviewer feedback will form the basis of the final decision.
8. Timeliness
   Reviewers are expected to meet deadlines, ensuring a timely and efficient review process without compromising feedback quality.
9. Decision Process
   Acceptance is based on the consensus of three reviewers. In cases of conflicting reviews, an additional expert opinion will be sought.
10. Plagiarism & Similarity Check
    The similarity index must not exceed 15% in total, with no single source contributing more than 5%. Submissions failing these criteria will not advance to the review stage.

Committees:

Chief Patron:

Prof. Tamma Koti Reddy, Vice-Chancellor (Incharge), IFHE, Hyderabad

Patron:

Dr. S. Vijayalakshmi, Registrar, IFHE, Hyderabad.

Dr. K. L. Narayana, Director, IcfaiTech, IFHE, Hyderabad.

Advisory Committee:

Prof. U. B. Desai, Advisor, IFHE, Hyderabad

Dr. J. Mahendar Reddy, Advisor, ICFAI Group

Dr. O. R. S. Rao , Advisor, ICFAI Group

Prof. Arun K Pujari, Advisor & Professor Emeritus

Dr. Ashok Kumar Das, IIIT Hyderabad

Prof. Rashmi Ranjan Rout , NIT Warangal

Prof. Ch Sudhakar, NIT Warangal

Prof. A. Ananda Rao , JNTU, Ananthapur

Prof. K C Santosh, University of South Dakota

Prof. R B V Subrahmanyam, NIT Warangal

Prof. S.Nagender Kumar, University of Hyderabad

Prof. C. Krishna Mohan, IIT Hyderabad

Prof. Chandrasekaran K, NITK Surathkal

Prof. R. Balasubramanian, IIT Roorkee

Prof. Vincenzo Piuri, University of Milan, Italy

Prof. Vijayakumar Varadarajan, The University of New South Wales, Sydney, Australia

Prof. Sanjeev Arora, Princeton University, US

Prof. Divya Midhunchakkaravarthy, Lincoln University College, Malaysia

Prof. Viraj Kumar, IISc Bangalore

Prof. Praveen Kumar Donta, Stockholm University, Sweden

Prof. Muhammad Ijaz Khan, Prince Mohammad Bin Fahd University, KSA

Prof. Durga Prasad Mohapatra, NIT Rourkela

Prof. Bernard De Baets, Ghent University, Belgium

Prof. Humaira Nisar, UTAR, Malaysia

Prof. Aditya Trivedi, ABV-IIITM, Gwalior

Prof. K. V. Arya, ABV-IIITM, Gwalior

Prof. S. Mary Saira Bhanu, NIT Tiruchirappalli

Prof. N. Ramsubramanian, NIT Tiruchirappalli

Prof. D V L N Somayajulu, NIT Manipur

Prof. Kentaro Inui, Tohoku University, Japan

Prof. Joonseok Lee, SNU, South Korea

Prof. Wen-Syan Li, SNU, South Korea

Prof. Hyojin Sung, SNU, South Korea

Prof. Khaled Ben Letaief, HKUST, Hongkong

Prof. Brahim Bensaou, HKUST, Hongkong

Prof. Poddoju Sateesh Kumar, IIT, Roorkee

Steering Committee Chair:

Dr. Sandeep Kumar Panda, Professor, IcfaiTech, IFHE, Hyderabad

General Chairs:

Dr. P. Pavan Kumar, HoD, Dept. of AI&DS, IcfaiTech, IFHE, Hyderabad

Dr. P. Rohini , HoD, Dept. of CSE, IcfaiTech, IFHE, Hyderabad

Publication Chair:

Dr. Pradosh Kumar G, Dept. of AI&DS, IcfaiTech, IFHE, Hyderabad

Technical Committee:

Dr. Asisa Kumar Panigrahy

Dr. K. Adi Narayana Reddy

Dr. Kuncham Sreenivasa Rao

Dr. L. Lakshmi

Dr. A. Sree Lakshmi

Dr. Kotari Sridevi

Dr. Srinivasu Badugu

Dr. Nafis Uddin Khan

Dr. B. Deevena Raju

Dr. B. Seetharamulu

Dr. Srinivasa Rao Kongara

Dr. D. Srinivasa Rao

Dr. Santosh Kumar Sahoo

Dr. Sukantha Das

Dr. Kaushik Midya

Sponsors

Co-Sponsors

Registration:

To encourage wider participation, the conference registration fee will be charged as given below:

Participation Category	Registration Fee (USD)	Registration Fee (INR)
Academicians	150	10,000
Research Scholars / Students	100	8,000
Participation Fee (Non-presenting Authors / Others)	100	5,000
Corporate Delegates / Policy Makers / Govt. Officials / NGO Professionals	150	10,000
Additional Pages(Per Page)	25	1,000

*An additional 18% GST will be applied to the registration fee mentioned above.

Accommodation

A limited number of rooms may be available at nominal rates on the campus of IFHE-Hyderabad. The rooms will be allocated on first-come-first served basis. For any queries, please contact us at info_icaciml2026@ifheindia.org.

Keynote Speakers

Conference Venue:

ICFAITECH - Hyderabad Donthanapally,
Shankarapalli Road
Hyderabad - 501203, Telangana, India.