Meet Our Distingushed Speakers
Dr. Manasi Patwardhan
With over 17 years of expertise in Natural Language Processing and Machine Learning, Dr. Patwardhan has led
numerous industry-driven Proof of Concepts. Her distinguished track record includes more than 10 granted
patents and over 40 publications at premier conferences like ACL, NAACL, EACL, EMNLP, and AAAI. She has
notably served as a demo-chair and program committee member for these esteemed gatherings.
Her contributions at TCS have been consistently recognized with an ‘A grade’ throughout her
seven-year tenure—a distinction achieved by only 2% of the workforce. She is also a recipient of the TCS
Innovista Award, the Young Engineer’s Award from the Institute of Engineers, and the ACM Grace Hopper
Scholarship.
Before entering the industry, she spearheaded R&D activities as Dean (R&D) at VIT, Pune, and
chaired the Board of Studies for Computer Science. As a Professor, she was instrumental in securing grants
from diverse funding agencies and fostering collaborative partnerships with industry while mentoring PhD and
MTech students.
Her current research focuses on GenAI, LLM Agents, training foundational models, and enhancing
reasoning in language models. She is currently leading the development of a platform designing to accelerate
the research lifecycle for scientists.
Abstract: We are building Acceleron, an intelligent partner designed to accelerate the research lifecycles of TCS researchers. Leveraging GenAI, we provide workflows that are steerable by researchers to improve efficiency in tasks such as ideation, exploration, codification, and critique. This talk elaborates on these GenAI techniques and their applications in Acceleron for AI4Research, while also highlighting relevant research problems and their solutions.
Dr. Rohit Gurjar
Serving as faculty at IIT Bombay since 2018, Dr. Gurjar holds dual B.Tech. and M.Tech. degrees, along with a
Ph.D. from IIT Kanpur. His doctoral thesis was recognized by the ACM India Doctoral Dissertation Awards.
Prior to his current role, he broadened his international research perspective through postdoctoral work at
the University of Ulm (Germany), Tel Aviv University (Israel), and Caltech (USA).
Dr. Gurjar's research interests center on theoretical computer science, specifically
Computational Complexity, Derandomization, Polyhedral Combinatorics, and Parallel Complexity. His work
addresses foundational problems such as polynomial identity testing and perfect matching, contributing
significantly to core understandings in algorithm design.
Dr. Sushmita Gupta
Dr. Gupta, who earned her Ph.D. from the University of Southern Denmark, is internationally acclaimed for
her contributions to algorithm design and analysis. Her research primarily explores graph algorithms,
algorithmic game theory, computational social choice, and streaming algorithms.
At IMSc, she teaches advanced courses including Algorithmic Game Theory and Algorithm Design.
She is also deeply involved in academic service, serving on program committees for major conferences and
coordinating summer schools.
Her influential publications cover multiagent systems, strategic behavior in voting, and the
computational complexity of collective decision-making, bridging theoretical foundations with
interdisciplinary computer science applications.
Mr. Jitesh Choudhary
A distinguished senior scientist and technology leader, Mr. Choudhary steers research, development, and
outreach as the Centre Head of C-DAC, Northeast Centre. His leadership at this autonomous R&D organization
under MeitY focuses on strategic initiatives in advanced computing.
His technical expertise spans high-performance computing, artificial intelligence, data science,
and cybersecurity, with an emphasis on developing scalable, indigenous solutions aligned with national
priorities.
Mr. Choudhary actively fosters collaboration between academia, industry, and government to drive
innovation and capacity building, particularly within Indias northeastern region, contributing significantly
to the national mission of technological self-reliance.
Many promising technologies fail not because they do not work, but because they are not designed to scale. "Lab to Launch" presents a systems-driven framework that addresses the critical gap between laboratory success and real-world deployment—the “Valley of Death.” Moving beyond the limitations of Technology Readiness Levels (TRLs), the framework integrates system, manufacturing, operational, and commercial readiness as parallel, interdependent dimensions of innovation maturity. By aligning technical development with integration, production feasibility, deployability, and market viability from early stages, this approach enables predictable, scalable productization. It reframes innovation success from invention alone to sustained, market-ready impact, offering a practical blueprint for transforming research excellence into deployable solutions.
Mr. Godavari Sudhakar Rao
As a Senior Technology Leader and Architect at Samsung R&D Institute India – Bangalore, Mr. Rao spearheads
innovations in advanced Artificial Intelligence, Natural Language Processing, and Large Language Models.
With over 15 years of industry experience, he plays a pivotal role in designing intelligent language systems
that power flagship Samsung products, including the Bixby voice assistant.
Throughout his career, Mr. Rao has led high-impact R&D initiatives, seamlessly combining deep
technical expertise with architectural vision. His work spans natural language understanding, generative AI,
and scalable AI architectures. A recipient of multiple Samsung internal excellence awards, he is a respected
mentor and leader within Samsung’s AI ecosystem, driving the delivery of production-grade solutions.
Abstract: Modern AI systems are becoming more than just chatbots — they are turning into intelligent agents that can search for information, make decisions, and take actions. This talk introduces how Retrieval-Augmented Generation (RAG) helps AI agents find the right knowledge at the right time, leading to more reliable and useful behavior. Through simple examples and real-world use cases, the session will show how combining retrieval with reasoning enables AI systems to better understand problems and act more effectively.
Mr. Nilesh Brahme
Nilesh Brahme is a seasoned Solutions and AI Architect with over 26 years of experience in designing and
delivering scalable, resilient, enterprise-grade technology architectures. His expertise spans Program
Management, Solution Architecture, Artificial Intelligence, and Quantum Computing. He is driven by complex
challenges and is passionate about leading technology transformation initiatives that align with evolving
business strategies.
Throughout his career, Mr. Brahme has successfully led global delivery teams across India and
Europe, fostering multicultural collaboration while emphasizing talent development and team excellence. He
possesses strong capabilities in translating business requirements into scalable, future-ready technology
solutions.
With a deep understanding of the Software Development Lifecycle (SDLC), he has played a key role
in DevOps transformation initiatives, defining CI/CD frameworks, automation standards, and modern
engineering practices. His core competencies include AI & Machine Learning, Data Platforms and ETL, Cloud
Technologies, and Enterprise Architecture Design.
Most recently, he served as Principal Technical Architect at Makers Lab, the Research &
Innovation division of Tech Mahindra, where he spearheaded the development of Indus LLM — one of India’s
pioneering open-source Hindi Large Language Models built from the ground up. He also acted as Lead Architect
for the proposal to build a sovereign LLM under the India AI initiative, which was successfully selected
under India AI 2.0.
Abstract: He will give a PoV about the environmental and sustainability aspect of AI/Gen AI usage. Highlighting the impact with facts and figures and strategies to reduce the CO2 footprint.
Prof. Saket Saurabh
Prof. Saket Saurabh is an Indian theoretical computer scientist and a Professor at the Institute of
Mathematical Sciences (IMSc), Chennai. He completed his BSc (Honours) in Mathematics and MSc in Computer
Science from Chennai Mathematical Institute and went on to earn his PhD in Theoretical Computer Science from
IMSc in 2008. He has since risen to become one of India’s leading researchers in algorithms.
In his research, Prof. Saurabh specializes in parameterized complexity, exact algorithms, graph
algorithms, and computational game theory. His work has shaped how researchers understand and tackle
computationally hard problems, particularly through the development of efficient parameterized and
preprocessing algorithms as well as methods for proving algorithmic lower bounds.
Over his career, he has published numerous influential papers and received several major
recognitions, including the Shanti Swarup Bhatnagar Prize for Science and Technology in Mathematical
Sciences (2021), the ACM India Early Career Researcher Award, and fellowships in prestigious scientific
academies. His contributions bridge deep theoretical insights with algorithmic techniques that influence
both academic research and advanced algorithm design.