The Association for Computing Machinery (ACM) is the world’s largest educational and scientific
computing society for the Computer Science/IT community. ACM is recording a healthy growth in India,
and ACM India was launched in 2010 to increase the focus on the country.
Since 2010, ACM India has organized an annual flagship event in January to discuss trends in science and technology,
and to celebrate ACM’s spirit and India’s accomplishments in computing. This event is attended by ACM
Turing Award winners, ACM Office Bearers, researchers and IT professionals. The past events have
witnessed keynote speeches by Tony Hoare (Turing Award 1980), Raj Reddy (Turing Award 1994), Barbara Lisskov (Turing Award 2008), Charles Thacker (Turing Award 2009), Eric Brewer (Infosys
ACM Award 2009), Franz Kaashoek (Infosys ACM Award 2010) and Ravi Kannan (Knuth Prize 2011).
Continuing this tradtion, we have a glittering set of speakes lined up for the forthcoming event.
Agenda for the day
| 08:30 am - 09:15 am|| Registration|
| 09:15 am - 09:50 am|| Inauguration and welcome|
- P J Narayanan, IIIT Hyderabad, President, ACM India
- John White, CEO, ACM
- Vinton G Cerf, Google, President, ACM
| 09:50 am - 10:00 am|| Presentation of ACM India Doctoral Dissertation Award|
- Awardee: Ruta Mehta, IIT, Bombay
Thesis Title: Nash Equilibrium Computation in Various Games
Session conducted by
- Honourable Mention: Srikanth Srinivasan, IMSc, Chennai
Thesis Title: New Directions in Arithmetic and Boolean Circuit Complexity
- Narendra Ahuja, University of Illinois at Urbana-Champaign
- Supratik Chakraborty, IIT Bombay
- Gautam Shroff, TCS
| 10:00 am - 11:00 am|| Keynote lecture|
| 11:00 am - 11:30 am|| Tea|
| 11:30 am - 12:30 pm|| Invited lecture|
| 12:30 pm - 2:00 pm|| Lunch|
| 2:00 pm - 3:00 pm|| Keynote lecture|
| 3:00 pm - 3:30 pm|| Tea |
| 3:30 pm - 4:30 pm|| Invited lecture|
Computer Science in the 21st Century
This talk will explore how computer science is changing and adapting to new infrastructure, new concepts, new realities using network and computing infrastructure for pedagogy.
Polynomials from a Computational Perspective
Polynomials are one of the fundamental objects in mathematics. In this talk, we focus on the problem of classifying polynomials. We argue for classifying polynomials according to the complexity of computing them. This notion is formalized as arithmetic complexity of a polynomial or polynomial family. After discussing some examples, we identify two important classes of polynomials according to their arithmetic complexity: VP and VNP. These are analogs of the classes P and NP in the algebraic settings, and it is not known if VP equals VNP. We connect this question with the problem of deciding if two arithmetic circuits compute the same polynomial, and review the exciting recent progress made on solving this problem.
A System-centric Vision for Computing – Challenges and Work Directions
Systems are becoming ubiquitous: the state of almost everything can be sensed, measured and monitored; people and objects can communicate and interact in entirely new ways; intelligent systems allow enhanced predictability of events and optimal use of resources.
Systems are hard to design due to unpredictable and subtle interactions with their environment, emergent behaviors, and occasional catastrophic cascading failures, rather than to complex data and algorithms. In contrast to transformational software, they are non-terminating non-predictable and have platform-dependent behavior.
By their nature, theoretical foundations of Computing are of little help for studying systems. Even if we perfectly understand the properties of application software, we have no theory to predict its dynamic behavior determined by its interaction with execution and external environments.
We discuss current limitations of the state of the art in system design and advocate for its study as a rigorous and accountable correct-by-construction process leading from application software to trustworthy and optimized implementations.
Despite its increasing importance, system design has attracted little attention from research communities and is relegated to second class status. This is partly due to the predilection of researchers for simple, elegant but impracticable theories. Furthermore, design is by its nature multi-disciplinary, requires consistent integration of heterogeneous system models supporting different levels of abstraction including logics, algorithms and programs as well as physical system models.
Addressing the system design challenge raises a multitude of deep theoretical problems such as the conceptualization of needs in a given area and their effective transformation into correct artifacts by taking into account resources. Awareness on its centrality is a chance to reinvigorate Computing and build novel scientific foundations matching the needs for increasing system integration and new applications.
Automating Program Verification: The search for abstractions using counter-examples
Even though checking if a program satisfies a property is undecidable, much progress has been made in automatic program verification. In this talk, we will describe a verification technique, which automatically constructs abstractions from a program to do verification, called counter-example guided abstraction refinement (or CEGAR). To check if a program P satisfies a property j CEGAR chooses a candidate abstraction A, and if A does not satisfy j, a counterexample witnessing this is used to iteratively refine A. This gives a semi-algorithm for checking if P satisfies j. This technique has found widespread use in program verification, automatic theorem proving, program synthesis, and more recently, even in machine learning! In this talk, we will survey these developments, without assuming much background from the audience.