AI Reboot: Revisiting Foundations and Frontiers
The IEEE Computer Society Student Branch Chapter, UPES is pleased to present an engaging Two-Day International Webinar Series on AI Reboot: Revisiting Foundations and Frontiers. This exclusive online event brings together domain experts from around the globe to explore advancements and applications in Artificial Intelligence.
📅 Dates: July 27–28, 2025
💻 Mode: Online | 🌐 Open to Global Participants
🎓 Organized by: IEEE Computer Society Student Branch Chapter, UPES
🎙 Esteemed Speakers:
Dr. Sahinur Rahman Laskar
Assistant Professor, UPES India
📅 Sunday, July 27 | 🕓 4:00 PM IST
Topic: NLP Applications, Tools & Techniques
Dr. P. Ravi Teja
Assistant Professor, UPES, India.
📅 Monday, July 28 | 🕚 11:00 AM IST
Topic: Introduction to Reinforcement Learning
Dr. Ritika Jain
Assistant Professor, School of Engg. & Science,
IITM Zanzibar, Tanzania (East Africa)
📅 Monday, July 28 | 🕒 3:00 PM IST
Topic: Lightweight DL Models for Healthcare
Mirza Nempth Ali Baig
AI Researcher, Humber College, Toronto, Canada
📅 Monday, July 28 | 🕗 8:00 PM IST
Topic: Machine Learning and its Applications
🚀 Why Attend?
✅ 4 Expert Speakers
✅ Global Perspectives
✅ Key Topics: NLP, Reinforcement Learning, AI in Healthcare, ML Applications
✅ E-Certificates for all registered and active participants
✅ Meeting link will be shared with registered participants only.
📝 Registration is FREE but Mandatory
🔗 Register here: https://forms.gle/tz77n57EhFS1HC9u7
📲 Scan QR on the poster to register instantly!
🎯 Open to students, professionals, researchers, and AI enthusiasts worldwide. Don’t miss this opportunity to reboot your AI knowledge.
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- Co-sponsored by School of Computer Science, UPES
Speakers
Dr. Sahinur Rahman Laskar of UPES Dehradun India
Tak1: NLP Applications, Tools and Techniques
In this session, Dr. Sahinur Rahman Laskar will delve into the fundamentals and frontiers of Natural Language Processing (NLP), a pivotal domain within Artificial Intelligence that focuses on enabling machines to comprehend and generate human language. The talk will introduce participants to widely used NLP tools and libraries such as NLTK, spaCy, and Hugging Face Transformers, alongside practical applications like sentiment analysis, text summarization, chatbots, and language translation. With an emphasis on real-world use cases and multilingual NLP challenges, especially in low-resource languages, this session aims to equip attendees with a solid foundation in modern NLP techniques and trends. It is ideal for students, researchers, and professionals eager to explore the evolving landscape of language technologies.
Biography:
Dr. Sahinur Rahman Laskar is an Assistant Professor in the School of Computer Science, Data Science Cluster at UPES Dehradun, India. He holds a Ph.D. in Computer Science and Engineering and is an active researcher in the areas of Natural Language Processing (NLP), Foundational Large Language Models (LLMs), Machine Learning/Deep Learning for NLP, and Multilingual Systems. Dr. Laskar has an impressive record of academic contributions, 6 years of teaching and research experience with 31 publications in international conferences and workshops, 14 journal papers (including 8 in SCIE and 6 in Scopus-indexed journals), 2 book chapters, and 2 patents. His work has earned recognition through promising results in numerous international NLP shared tasks, including WANLP (EMNLP-2022), WMT (2019–2022), WAT (2019–2022), FIRE-2020, and LoResMT 2020. He is actively involved in mentoring B.Tech, M.Tech, and Ph.D. students on academic and internship projects in NLP. He has organized major shared tasks, such as the Low-Resource Indic Language Translation (WMT23 at EMNLP 2023) and the Cross-Lingual Mathematical Information Retrieval (CLMIR-2025 at FIRE 2025). Dr. Laskar has also contributed to faculty development through technical talks, including a session on "Deep Learning for Machine Translation" delivered at the DL-NLP 2021 Faculty Development Program, hosted by the Department of CSE and IT, Jaypee Institute of Information Technology, Noida. He is a Senior Member of IEEE, a member of NLP-AI, and recipient of the Best Paper Award at FICTA-2022. He serves as a reviewer for top-tier journals such as ACM Computing Surveys, Language Resources and Evaluation (LREV), Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Natural Language Engineering (NLE), and is an ACL Rolling Reviewer (ARR-2024).
Address:School of Computer Science UPES Dehradun, , Dehradun, Uttaranchal, India, 248007
Ravi Teja of UPES Dehradun India
Talk 2: Introduction to Reinforcement Learning
Dr. Ravi Teja will provide a concise yet insightful overview of Reinforcement Learning (RL), a core area of machine learning where agents learn to make decisions by interacting with their environment. The session will cover key concepts such as rewards, policies, value functions, and the exploration-exploitation trade-off. Real-life applications in robotics, gaming, and autonomous systems will be highlighted to demonstrate the practical relevance of RL. This talk is ideal for beginners looking to understand the foundational principles and emerging opportunities in reinforcement learning.
Biography:
Dr. Ravi Teja is an academic professional with a strong background in engineering and advanced research. He holds a Ph.D. in Wireless Communication and specializes in areas such as Deep Reinforcement Learning, Game Theory, and 5G/6G Networks. His research focuses on developing intelligent, secure, and scalable network frameworks for next-generation communication systems, integrating AI with cutting-edge technologies like SDN, Federated Learning, and Quantum Computing. With multiple publications in reputed journals, he is passionate about solving real-world problems through innovative, interdisciplinary approaches.
Address:School of Computer Science UPES Dehradun, , Dehradun, Uttaranchal, India, 248007
Ritika Jain of IIT MADRAS ZANZIBAR Campus, Tanzania
Talk 3: Lightweight Deep Learning Models for Healthcare
In this session, Dr. Ritika Jain will explore the design and deployment of lightweight deep learning models tailored for healthcare applications, especially in resource-constrained environments. The talk will highlight how optimized architectures like MobileNet and quantized neural networks enable efficient processing on edge devices while maintaining accuracy. Use cases in medical image analysis, disease prediction, and diagnostic support will be discussed. This session is particularly relevant for those interested in developing scalable, AI-driven healthcare solutions suitable for real-world and remote settings.
Biography:
Dr. Ritika Jain is an Assistant Professor at the School of Engineering and Science, IIT Madras Zanzibar, specializing in biomedical signal processing, machine learning, and AI-driven healthcare applications. Her research primarily focuses on the analysis of EEG, EOG, and EMG signals for sleep-stage classification, seizure detection, and the automated diagnosis of neurological disorders. She earned her Ph.D. in Electrical Engineering from the Indian Institute of Science (IISc), Bangalore, where she developed interpretable machine learning models for detecting sleep disorders using multimodal biosignals. She also holds an M.Tech in Signal Processing from IIT Gandhinagar and a B.E. in Electronics and Telecommunication from Bhilai Institute of Technology, where she graduated among the university’s top five. Dr. Jain’s recent contributions include a LightGBM-EOG classifier for diagnosing sleep disorders, published in the IEEE Journal of Biomedical and Health Informatics, and a multimodal sleep staging framework utilizing modality-specific feature selection and data augmentation. Her work on seizure detection using autoencoder-classifier models and cyclic alternating pattern (CAP)-based insomnia classification has been presented at prestigious forums such as IEEE EMBC and DSP. She has authored over 20 research publications, accumulating 160+ citations, and serves as a reviewer for top-tier journals including IEEE JBHI, Frontiers in Neuroscience, and Biomedical Signal Processing and Control. Her work has contributed significantly to the development of efficient, generalizable, and interpretable AI systems for clinical use. At IITM Zanzibar, Dr. Jain teaches and mentors undergraduate and graduate students, while actively leading interdisciplinary research in AI for healthcare and neuroscience. She is a dedicated member of the IEEE Engineering in Medicine and Biology Society (EMBS) and is committed to advancing impactful, patient-centered innovation in healthcare technologies.
Address:Indian Institute of Technology Madras — Zanzibar Campus, P.O. Box 394, Bweleo, Urban West – 71215, Urban West, Unknown, Tanzania, 71215
Mr. Mirza Nemath Ali Baig of Humber International Graduate School Toronto, Canada
Talk 4: Machine Learning and Its Applications
Mr. Mirza Nemath Ali Baig will conclude the series with an engaging session on the fundamentals of Machine Learning (ML) and its wide-ranging applications across various industries. The talk will cover essential ML algorithms, model training workflows, and real-world case studies from domains such as finance, healthcare, and smart systems. Emphasis will be placed on practical implementation, challenges in deployment, and the future potential of ML in solving complex problems. This session is ideal for attendees seeking a practical understanding of ML and its transformative impact.
Biography:
Mirza Nemath Ali Baig is a passionate AI/ML specialist with a strong academic foundation and a forward-looking approach to technological innovation. Currently based in Toronto, Canada, he is pursuing a Graduate Certificate in Artificial Intelligence with Machine Learning at Humber College, where he is honing skills in deep learning, data analytics, cloud computing, and model optimization. Before transitioning to the Canadian tech ecosystem, Mirza served as an Assistant Professor for over six years at esteemed institutions in Hyderabad, India—Lords Institute of Engineering & Technology, Auroras Engineering College, and CMR Engineering College. His teaching and mentoring experience focused on Python, MATLAB, and core computing concepts, while fostering an inclusive and innovative learning environment. He holds a Master of Engineering in Digital Systems from Osmania University and has completed specialized certifications in Data Science and Research from NPTEL. His technical interests are rooted in applying AI to real-world challenges through intelligent systems and data-driven solutions. Mirza has worked on notable projects such as designing a high-speed Flash ADC for WLAN applications and LTE network planning using Atoll. These reflect his expertise in both hardware-level systems and software-centric AI development.
Address:59 Hayden St Unit 400, Toronto, ON M4Y 0E7, Canada, , Toronto, Ontario, Canada, M9W 5L7
Agenda
📅 Event Title:
AI Reboot – Revisiting Foundations and Frontiers (A Two-Day International Webinar Series)
📍 Mode:
Online | Open Globally
📆 Dates:
Day 1: Sunday, July 27, 2025
Day 2: Monday, July 28, 2025.
📌 Day 1: Sunday, July 27, 2025
04:00 PM – 05:00 PM IST
Speaker: Dr. Sahinur Rahman Laskar 🇮🇳
Topic: NLP Applications, Tools & Techniques
Session Overview: Introduction to modern NLP techniques, tools like Hugging Face, and real-world applications in multilingual contexts.
📌 Day 2: Monday, July 28, 2025
11:00 AM – 12:00 PM IST
Speaker: Dr. Ravi Teja 🇮🇳
Topic: Introduction to Reinforcement Learning
Session Overview: Foundational principles of RL, exploration vs. exploitation, and applications in robotics and recommendation systems.
03:00 PM – 04:00 PM IST
Speaker: Dr. Ritika Jain 🌍 (East Africa)
Topic: Lightweight Deep Learning Models for Healthcare
Session Overview: Optimized AI models for resource-constrained healthcare settings with case studies in diagnostics.
08:00 PM – 09:00 PM IST
Speaker: Mirza Nempth Ali Baig 🇨🇦
Topic: Machine Learning and Its Applications
Session Overview: Core ML algorithms, tools, and their integration in sectors like finance, energy, and health.