Cheenta Ivy League Mentoring Seminar

Dr. Bhavna Aggarwal is a doctor and mentor who helps students navigate the journey from high school to top global universities. Her daughters, Anushka Aggarwal and Gunjan Aggarwal—both EGMO medalists—study at MIT and Trinity College, University of Cambridge. At Cheenta Academy, she guides students and parents in understanding international academic pathways with clarity and confidence.

Pipeline scientist at the LSST Rubin

Abstract: SNIa provides one of the most robust probe to estimate the nature of dark energy and measure the speed of accelerating Universe at the current epoch. In this talk I will cover the basics of how SNIa is used as a tool to do so and then how the LSST Rubin will revolutionize the measurement of Dark Energy using the SNIa observed during it’s lifetime.

VAP at Rutgers University

Abstract: First we try to lay the foundations of one and several complex variables, theory of Bergman metrics and K\"ahler-Einstein metrics. Then show that the Bergman metric of the ball quotients $\mathbb{B}^2/Γ$, where $Γ$ is a finite and fixed point free group, is Kähler-Einstein if and only if $Γ$ is trivial. As a consequence, we characterize the unit ball $\mathbb{B}^2$, among 2 dimensional Stein spaces with isolated normal singularities, proving an algebraic version of Cheng's conjecture for 2 dimensional Stein spaces (one can think of it as a version of Riemann mapping theorem for 2 dimensional Stein spaces)

Published author in Nature Communications

Abstract: This research seminar explores ongoing attempts to decode the inscriptions of the Indus Valley Civilization. It discusses the historical context of the script, the major challenges in decipherment, and competing scholarly theories about its nature. The session highlights modern research methods, including linguistic comparison and computational analysis. Archaeological evidence and seal imagery are examined to support interpretations. The talk emphasizes interdisciplinary research as key to understanding this ancient writing system.

Research Scholar at Université Paris-Saclay

Abstract:This research talk explores the fundamental connections between automata theory and algebra, highlighting how algebraic structures provide powerful tools to analyze computational systems. The session introduces automata as mathematical models that describe machine behavior through state transitions and accepting conditions. By examining examples of finite automata over binary sequences, the talk illustrates how languages are recognized and classified. The discussion further emphasizes the role of algebraic methods in understanding the structural properties of formal languages. Overall, the seminar presents an elegant interplay between computation and algebraic theory.

Research Scientist at MIT

Abstract: In the era of big data, astronomy and astrophysics are undergoing transformative breakthroughs driven by large-scale observational experiments. A landmark achievement was the 2016 detection of gravitational waves by the Laser Interferometer Gravitational-wave Observatory (LIGO), confirming a century-old prediction of Einstein’s theory of relativity. This was followed in 2017 by the first simultaneous observation of gravitational waves and electromagnetic radiation from a neutron star merger, inaugurating the field of multi-messenger astronomy. This talk provides a historical overview of gravitational wave discovery, examines the current scientific landscape, and discusses the technological and analytical challenges involved in advancing this rapidly evolving field.

Virginia Tech University

Abstract: Sparse signal recovery remains an important challenge in large-scale data analysis and both Bayesian and frequentist literature has undergone an explosive development in the past in both theory and methodology. The purpose of this talk is to briefly review and discuss these developments. In the first half of this talk, I will survey the extant literature, and connections with Bayesian models will be highlighted at various points. In the second half, I will discuss a few unexplored aspects of their behavior and cover several recent developments. I will offer some insights into these problems and point out future directions.

NASA Marshall Space Flight Center

Abstract:This research seminar by Dr. Debnandini Mukherjee (NASA/University of Alabama) focuses on the search for giant and dwarf compact objects in the universe, including massive stellar systems and dense remnants such as white dwarfs and neutron stars. The talk presents key observational techniques and theoretical frameworks used to detect, classify, and analyze these objects within extensive astronomical datasets. Particular attention is given to the challenges associated with identifying compact objects amidst large-scale survey data and the methodologies developed to address these limitations. The seminar further highlights the role of such objects in advancing our understanding of stellar evolution, gravitational physics, and cosmic structure formation. Overall, the session outlines current research developments and future directions in compact object astronomy.

অধ্যাপিকা ইউনিভার্সিটি অফ লিভারপুল

সারাংশ - মেশিন লার্নিং আধুনিক কৃত্রিম বুদ্ধিমত্তার একটি কেন্দ্রীয় স্তম্ভ হয়ে উঠেছে, যা কম্পিউটারকে স্পষ্টভাবে প্রোগ্রাম না করেও ডেটার নমুনা থেকে শিখে সিদ্ধান্ত গ্রহণের সক্ষমতা অথবা ভবিষ্যদ্বাণী করার ক্ষমতা প্রদান করে। এই আলোচনায় মেশিন লার্নিং-এর একটি সহজবোধ্য পরিচয় উপস্থাপন করা হবে, যেখানে এর মূল ধারণা, প্রচলিত শেখার পদ্ধতি এবং বাস্তব জীবনের প্রয়োগ নিয়ে আলোচনা করা হবে। এছাড়াও, কীভাবে মেশিন লার্নিং মডেল প্রশিক্ষণ, মূল্যায়ন ও বাস্তব ব্যবহারে প্রয়োগ করা হয়, সেই সঙ্গে ডেটার গুণগত মান, সাধারণীকরণ ক্ষমতা এবং নৈতিক বিষয়সহ প্রধান চ্যালেঞ্জগুলো তুলে ধরা হবে। এই আলোচনার উদ্দেশ্য হলো শ্রোতাদের মেশিন লার্নিং সম্পর্কে একটি ভিত্তিমূলক ধারণা প্রদান করা এবং বিজ্ঞান, শিল্প ও সমাজে এর ক্রমবর্ধমান প্রভাব সম্পর্কে সচেতন করা।

Postdoc at Auburn University

Abstract: The Cannon Conjecture roughly says that that if a certain kind of group has a 2 dimensional sphere as its boundary, then it should be a fundamental group of a 3-manifold. I will present an enemy scenario to this conjecture: I will discuss a higher-dimensional analogue of this conjecture that does not hold. This is based on a joint work with Kevin Schreve.

Professor, CS, Rutgers-Camden, Lecturer, CIS, University of Pennsylvania.

Abstract: This talk focuses on algorithmic thinking, which means approaching problems in a logical, step-by-step manner. It explains how complex problems can be broken down into smaller and more manageable parts. The topic is highly relevant to mathematics, computer science, and computational problem-solving.
It encourages students to develop clarity of thought, structured reasoning, and effective solution-building skills. Overall, the session highlights the importance of systematic and creative thinking in tackling challenging problems.