Computer Science & Engineering (Data Science)

About Department

INTRODUCTION

As technology continues to evolve at an unprecedented pace, the demand for professionals skilled in data science has skyrocketed. One field that has witnessed a significant transformation is Computer Science and Engineering (CSE) departments in engineering colleges. With the emergence of data-driven decision making and the increasing importance of big data analytics, CSE departments have incorporated data science as a crucial component of their curriculum.

THE GROWING IMPORTANCE OF DATA SCIENCE

Data science has emerged as a critical discipline in today’s digital age. It involves extracting actionable insights from vast amounts of structured and unstructured data, enabling organizations to make informed decisions and gain a competitive edge. Industries such as finance, healthcare, marketing, and e-commerce heavily rely on data science to optimize their operations, improve customer experiences, and drive innovation.

ABOUT ACE ENGINEERING COLLEGE CSE (DATA SCIENCE) DEPARTMENT

With the rapid evolution of technology and the increasing amount of available data, the demand for professionals skilled in data science has grown exponentially. Our CSE (Data Science) department aims to meet this demand by providing a comprehensive curriculum that prepares students with the essential skills and knowledge needed for success in this field.

At the core of our department’s vision is the belief that data is at the heart of innovation and informed decision-making. Our faculty members, who are renowned experts in their respective fields, are committed to imparting the latest methodologies and industry best practices to our students. They continuously engage in research, ensuring that our curriculum remains up-to-date and aligned with current industry requirements.

The department is home to a group of highly skilled and experienced faculty members with knowledge in a variety of subjects. Two of the faculty members have doctorates, and one is currently obtaining a Ph.D. In addition, three faculty members are enrolled in the University of Hyderabad’s Artificial Intelligence and Machine Learning Diploma program.

Duration: 4 years (Regular) / 3 years (Lateral Entrance)

No. of Semesters: 8 (Regular) / 6 (Lateral Entrance)

No. of Seats: Total – 180 (Status of NRI Approval – Yes)

Eligibility: Education is based on the 10+2 system. Student must have passed the subjects of Physics, Chemistry, and Mathematics in the qualifying examination

Scope for Higher Studies: M.E. / M.Tech / M.B.A./ M.S.

The CSE department specializing in Data Science has impressive facilities and a fully equipped computer lab that is tailored to the unique requirements of our data science students. We offer an abundant range of resources, such as advanced computing clusters and access to various datasets, allowing students to gain practical experience and enhance their problem-solving abilities.

The department encourages students to actively participate in research projects and engage in internships with leading organizations. These opportunities provide invaluable experiences and allow students to apply the knowledge they acquire in real-world settings. Additionally, we facilitate workshops, seminars, and guest lectures by industry professionals to bridge the gap between academia and industry, allowing students to expand their network and stay abreast of the latest trends and developments.

Collaboration is a key aspect of our department’s ethos, and we actively foster interdisciplinary partnerships within the institution and with external organizations. This collaborative approach serves to enhance the scope of research and enrich the learning environment, enabling students to tackle complex, real-world problems that require cross-domain expertise.

Graduates from our CSE (Data Science) department are well-positioned for exciting career opportunities in various sectors, including technology, finance, healthcare, and more. Armed with a deep understanding of data analytics, statistical modelling, and machine learning algorithms, our graduates are sought after by industry leaders for their analytical and problem-solving skills.

Finally, our engineering college’s CSE (Data Science) department is an ideal place for ambitious data scientists. Our education program encompasses both theoretical learning and hands-on experience, enabling students to develop expertise in the field of data science. Through top-notch faculty, state-of-the-art facilities, and a collaborative mindset, we empower our students with the necessary resources to make innovative advancements in the continuously evolving realm of data science.

OBJECTIVES:

To equip the students with strong fundamental concepts, analytical capability, programming and problem solving skills.
To create an academic environment conducive for higher learning through student training, self learning, sound academic practices and research
endeavors.
To make the students industry ready and to enhance their employability through training and internships. To make students job-ready by applying what you learn and building real-life projects
To improve department industry collaboration through interaction including participation in professional society activities, guest lecturers and industrial visit.
To provide opportunities in order to promote organizational and leadership skills in students through various co-curricular and extra – curricular activities

HOD Profile

Professional Overview

Dr. Suresh Ralla

Professor & Head of the Department – Computer Science and Engineering (Data Science)

Dr. Suresh Ralla
Professor & Head of the Department

Dr. Suresh Ralla is an experienced academician, researcher, and academic administrator with over 17 years of teaching and research experience in the field of Computer Science and Artificial Intelligence. He currently serves as Professor and Head of the Department of Computer Science and Engineering (Data Science) at ACE Engineering College, Hyderabad.

Dr. Suresh Ralla completed his Ph.D. from Osmania University, Hyderabad, focusing on machine learning techniques for heart disease prediction and healthcare data analytics. His research emphasizes intelligent predictive models that support early diagnosis, clinical decision support, and personalized healthcare solutions.

He is dedicated to creating a dynamic learning environment through innovative teaching methods, research-driven education, and student mentorship, while continuously contributing to advancements in artificial intelligence, machine learning, and data science.

Academic Qualifications

Ph.D. in Computer Science / Machine Learning Applications
Osmania University, Hyderabad

M.Tech in Computer Science & Engineering
Osmania University, Hyderabad

B.Tech in Computer Science & Engineering
Kakatiya University, Khammam

Dr. Suresh Ralla’s doctoral research focused on machine learning frameworks for heart disease prediction, integrating intelligent feature selection, ensemble learning algorithms, and predictive analytics to improve healthcare decision-making systems.

Teaching, Leadership & Departmental Development

Dr. Suresh Ralla has extensive teaching experience in core computer science and AI-related subjects including Computer Organization, Information Retrieval Systems, Artificial Intelligence, Data Warehousing and Data Mining, Computer Networks, Operating Systems, Cyber Security, and Software Engineering.

As Head of the Department of Computer Science and Engineering (Data Science), he provides strategic leadership in curriculum development, research initiatives, outcome-based education implementation, and accreditation-related activities. He actively promotes industry-oriented learning, student innovation, and interdisciplinary research collaborations.

He also plays an important role in faculty mentoring, research guidance, and student career development, helping students align academic knowledge with industry requirements.

Research Impact & Areas of Interest

Dr. Suresh Ralla’s research focuses on:

Machine Learning and Artificial Intelligence
Healthcare Data Analytics
Heart Disease Prediction Models
Ensemble Learning Algorithms

His work integrates machine learning, evolutionary computing, and predictive analytics to develop intelligent systems capable of assisting healthcare professionals in early disease detection and decision-making.

Publications & Scholarly Contributions

Dr. Suresh Ralla has published numerous research papers in Scopus indexed journals, international journals, and conference proceedings in the areas of machine learning, data mining, and intelligent computing.

His notable publications include research in journals and proceedings such as:

Journal of Theoretical and Applied Information Technology (Scopus Indexed)
Springer Cognitive and Intelligent Computing Conference Proceedings.
Various national and international conference proceedings

His research contributions focus on genetic feature selection, ensemble learning models, and predictive analytics for heart disease diagnosis.

Book Publication

Artificial Intelligence – Textbook published by Indo-Continental Academic Publishers
ISBN: 978-81-966517-3-2

Patents & Innovation

Flood Monitoring Device with Alert Mechanism
A smart monitoring system designed to detect rising water levels and provide early flood alerts using sensor-based monitoring systems.

System for Ad-Hoc Model Building and Machine Learning Services for Radiology Quality Dashboard
An intelligent framework designed to analyse medical imaging data and generate clinical insights using machine learning techniques.

Awards, Training & Professional Development

Dr. Suresh Ralla has actively participated in several academic training programs and workshops, including:

Data Visualization using Tableau and Power BI
Data Mining and Business Intelligence Workshops
Soft Computing Training Programs
Workshops on Mobile Ad-Hoc Networks and Emerging Technologies

He has also coordinated academic programs and workshops for students and faculty development.

Academic Administration & Institutional Responsibilities

Dr. Suresh Ralla has held several important administrative roles, including:

Head of the Department – CSE(Data Science)
IQAC Coordinator

Through these roles, he actively contributes to institutional development, accreditation processes, research promotion, and student welfare initiatives.

Vision and Mission

Vision of the Department

To be a centre of excellence in Computer Science and Data Science education by producing competent engineers with strong analytical and research skills, entrepreneurial abilities, ethical values, and the capability to address global technological and societal challenges.

Mission of the Department

M1: Provide strong foundations in Computer Science, Data Science, Artificial Intelligence, and Machine Learning through quality teaching–learning processes and modern laboratory facilities.
M2: Develop analytical thinking, problem-solving abilities, and programming skills to address real-world data-driven challenges.
M3: Encourage research, innovation, and entrepreneurship in emerging technologies of data science and computing.
M4: Prepare students for higher education, global careers, and industry requirements through professional training, industry interaction, and lifelong learning.
M5: Promote ethical values, leadership, teamwork, and social responsibility in professional practice.

PEOs, WK, POs and PSOs

Program Educational Objectives (PEOs)

To introduce the fundamentals of science and engineering concepts essential for a data architect / data scientist.
To inculcate the knowledge of mathematical foundations and algorithmic principles for effective problem solving.
To provide knowledge in data science for modern computational data analysis and modeling methodologies.
To provide the knowledge in artificial intelligence techniquesand apply them to develop relevant models and real time products.
To impart knowledge to analyze, design, test and implement the model required for various applications.
To hone personality skills, trigger social commitment and inculcate societal responsibilities.

Knowledge and Attitude Profile (WK)

WK1: A systematic, theory-based understanding of the natural sciences applicable to the discipline and awareness of relevant social sciences.

WK2: Conceptually-based mathematics, numerical analysis, data analysis, statistics and formal aspects of computer and information science to support detailed analysis and modelling applicable to the discipline.

WK3: A systematic, theory-based formulation of engineering fundamentals required in the engineering discipline.

WK4: Engineering specialist knowledge that provides theoretical frameworks and bodies of knowledge for the accepted practice areas in the engineering discipline; much is at the forefront of the discipline.

WK5: Knowledge, including efficient resource use, environmental impacts, whole-life cost, reuse of resources, net zero carbon, and similar concepts, that supports engineering design and operations in a practice area. WK6: Knowledge of engineering practice (technology) in the practice areas in the engineering discipline.

WK7: Knowledge of the role of engineering in society and identified issues in engineering practice in the discipline, such as the professional responsibility of an engineer to public safety and sustainable development.

WK8: Engagement with selected knowledge in the current research literature of the discipline, awareness of the power of critical thinking and creative approaches to evaluate emerging issues.

WK9: Ethics, inclusive behavior and conduct. Knowledge of professional ethics, responsibilities, and norms of engineering practice. Awareness of the need for diversity by reason of ethnicity, gender, age, physical ability etc. with mutual understanding and respect, and of inclusive attitudes.

Program Outcomes (POs)

PO1: Engineering Knowledge: Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization as specified in WK1 to WK4 respectively to develop to the solution of complex engineering problems.

PO2: Problem Analysis: Identify, formulate, review research literature and analyze complex engineering problems reaching substantiated conclusions with consideration for sustainable development. (WK1 to WK4)

PO3: Design/Development of Solutions: Design creative solutions for complex engineering problems and design/develop systems/components/processes to meet identified needs with consideration for the public health and safety, whole-life cost, net zero carbon, culture, society and environment as required. (WK5)

PO4: Conduct Investigations of Complex Problems: Conduct investigations of complex engineering problems using research-based knowledge including design of experiments, modelling, analysis & interpretation of data to provide valid conclusions. (WK8)

PO5: Engineering Tool Usage: Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including prediction and modelling recognizing their limitations to solve complex engineering problems. (WK2 and WK6)

PO6: The Engineer and The World: Analyze and evaluate societal and environmental aspects while solving complex engineering problems for its impact on sustainability with reference to economy, health, safety, legal framework, culture and environment. (WK1, WK5, and WK7)

PO7: Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws. (WK9)

PO8: Individual and Collaborative Team work: Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.

PO9: Communication: Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations considering cultural, language, and learning differences

PO10: Project Management and Finance: Apply knowledge and understanding of engineering management principles and economic decision-making and apply these to one’s own work, as a member and leader in a team, and to manage projects and in multidisciplinary environments.

PO11: Life-Long Learning: Recognize the need for, and have the preparation and ability for i) independent and life-long learning ii) adaptability to new and emerging technologies and iii) critical thinking in the broadest context of technological change. (WK8)

Program Specific Outcomes (PSOs):

PSO1: Understand, analyze and develop essential proficiency in the areas related to data science in terms of underlying statistical and computational principles and apply the knowledge to solve practical problems.

PSO2: Implement data science techniques such as search algorithms, neural networks, machine learning and data analytics for solving a problem and designing novel algorithms for successful career and entrepreneurship.

About the Course

ABOUT THE COURSE

About the Course

This comprehensive course offers numerous advantages for understanding key concepts in data science. It provides a deep dive into the analysis of big data, effectively handling large datasets, and optimizing operations to efficiently manage vast amounts of information. By enrolling in this all-in-one data science course, you will gain valuable knowledge about various tools, IDEs, frameworks, and techniques that are instrumental in mastering different areas within data science. The curriculum begins by introducing the fundamental building blocks of data science, such as foundational principles, core concepts, and basic programming elements. Subsequently, it progresses to cover essential aspects like data visualization and analytics using popular platforms like Excel, SQL, and Tableau. These modules delve into crucial skills, including data extraction strategies, advanced manipulation techniques, detailed analysis methodologies, relevant reporting practices, and constructing intuitive business dashboards.

Top Programming languages for Data Science:

Python
R Programming
Java script
Java
SQL
Scala
Key Areas of Data Science

IDE:

Pycharm
Jupyter

Data Analysis:

FE
Data Wrangling
EDA (explore data analysis)

Data Visualization:

Tableau
Power BI
MATplotlib
Ggplot
Seaborn

WEB Scraping:

Beautiful Soup
Scrapy
URL LIB

Key areas of data science

Data Engineering and Data Warehousing
Data Engineering involves converting data into a format that is suitable for analysis. This often includes overseeing the origin, organization, integrity, storage, and availability of the data in order to enable its query and analysis by other analysts..
related jobs: Data Engineer, Database Developer, Data Analyst
Data Mining and Statistical Analysis
Data Mining involves the utilization of statistical techniques such as exploratory data analysis and predictive modeling to identify patterns and trends in data obtained from various sources. This individual has the ability to analyze a business problem, transform it into a specific question about data, develop predictive models to address this question, and effectively communicate their findings through storytelling.
related jobs: Data Scientist, Business Analyst, Statistician
Cloud and Distributed Computing
Designing and implementing the necessary infrastructure and platforms for cloud computing and distributed systems is what Cloud and System Architecture entail. This role also involves analyzing system requirements, ensuring secure integration with existing applications, and aligning them with business needs.
related jobs: Cloud Architect, Cloud Engineer , Platform Engineer
Database Management and Architecture
The primary responsibility of this role is to create, implement, and manage databases that handle large volumes of complex data transactions for specific services or groups.
related jobs: Database Analyst, Database Administrator, Data Specialist
Business Intelligence and Strategy
BI encompasses various essential tasks, such as enhancing data sources for greater precision and ease, creating customized analytics solutions, overseeing dashboards and reports for stakeholders’ benefit, identifying opportunities to optimize reporting and analysis practices – including aspects like data integrity, test design, validation, and documentation.
related jobs: BI Engineer, BI Developer, BI Analyst, Data Strategist
ML / Cognitive Computing Development
Most individuals associate data science with “creating robots”. This field encompasses a more advanced and intricate version of data mining and statistical analysis. The primary focus lies in acquiring the necessary input to fuel the model, which involves tasks such as constructing data pipelines, identifying convenient sources for data, conducting A/B testing, and establishing benchmarking infrastructure. Once these preliminary steps are completed, attention may shift towards building the actual algorithms or models. However, this phase often relies on well-established industry tools and statistical techniques. It is worth noting that this particular area has become a popular buzzword in numerous organizations; therefore it is advisable to explore specific sub-fields within it to gain a clear understanding of one’s preferences.
related jobs: ML Engineer, AI Specialist, Cognitive Developer, Researcher
Data Visualization and Presentation
Presenting data in a visually pleasing manner has become an integral aspect of various roles, such as business analyst and data scientist. When these areas are designated as official positions within a company, the primary responsibility is to develop tailored BI solutions for teams and customers based on specific business needs and use cases. In some instances, this may involve more emphasis on graphic design skills..
related jobs: Data Viz Engineer, Data Viz Developer, Software Developer
Operations-Related Data Analytics
If you do not identify as highly technical but still have a knack for problem-solving and optimizing processes, these could be suitable career options. These positions involve utilizing the tools and data provided by the rest of the data science team to identify areas for improvement in various aspects of business operations, such as logistics, technology, finance, or human resources.
related jobs: Planning Analyst, Decisions Analyst, Communications Analyst, etc
Market-Related Data Analytics
The level of technical expertise required for these roles varies depending on the analysis level and company. Typically, individuals in these positions concentrate more on external data pertaining to customers, sales, and marketing. However, their overall objective is similar to that of operations personnel: monitoring performance and identifying potential opportunities.
related jobs: Web Analyst, Product Analyst, Market Analyst, Sales Analyst
Sector-Specific Data Analytics (Healthcare, Finance, Insurance, etc.)
Finally, individuals with a background in sectors like Healthcare or Finance and a need for specialized knowledge to assess data may consider exploring entry-level analyst roles within companies operating in these industries. It is important to note that the specific technical skills required for such positions will vary depending on the hiring organization’s expectations and preferred tools.
related jobs: Data Analyst, Business Analyst, Data Scientist — specialized

Opportunities

Data science is gaining immense popularity and becoming a lucrative career choice due to its high salaries and abundant opportunities. This field, widely regarded as one of the most sought-after careers of the 21st century, is witnessing an exponential growth in job openings worldwide.

India, like many other countries, is also witnessing a data explosion and experiencing increased demand for data scientists as more companies embrace this technology-driven discipline.

Data Scientist
Data Analyst
Data Engineer
Business Intelligence Developer.
Data architect
Statistician
Business Analyst
Machine Learning engineer
Database Administrator

Uniqueness of Data Science

UNIQUENESS OF DATA SCIENCE

The demand for data scientists is rapidly increasing each day due to their extensive knowledge and expertise in various fields such as machine learning, statistics, mathematics, computing science, data visualization, and communication. As companies grapple with large amounts of data, they rely on these professionals to extract valuable insights that can enhance their business strategies while adapting to evolving technologies in the market. Consequently, there’s a growing need for skilled individuals who possess reliable data science skills. These experts proficiently manipulate vast datasets using advanced statistical techniques and visualization methods to predict potential outcomes and identify possible risks. Additionally, this escalating demand also offers promising career opportunities for both students and established professionals alike.

In a typical day, the tasks of a data scientist involve extracting information from various sources through the use of APIs or constructing ETL pipelines. Data cleansing is performed using programming languages such as R or Python. They search for more efficient methods to analyze data by exploring disparate and disconnected sources. Data scientists possess knowledge in specific areas and have expertise in managing and interpreting data to solve complex problems. Additionally, they construct models and algorithms that allow them to uncover patterns and trends within extensive datasets. Finally, these insights are communicated visually to stakeholders using visualization tools.

Currently, the role of a ‘data scientist’ is regarded as one of the most attractive jobs in the 21st century. While it is essential to have experience with R, Python, Cloud computing, machine learning, multivariable calculus, probability and statistics, SQL,Tensorflow,and big data analysis skills alongside soft skills like data storytelling,data communication,business acumen and critical thinking for success in this highly competitive field; there are certain additional skills that can set individuals apart. Some examples include:

Data Wrangling: Working with messy and disorganized data sets can be challenging. The database fields may lack clear definitions, contain irrelevant values, or have inconsistent uses within the same field. Additionally, outliers in the data may not have a clear explanation. Therefore, it is essential to transform, standardize, normalize and clean the data before conducting any modeling work in order to extract meaningful insights from it. Data wrangling refers to the process of converting data from one format to another. This task requires patience as no amount of time or knowledge can compensate for a poorly structured dataset. For example, Python offers tools for effective Data Wrangling techniques.

Web Analytics: With the rise of social media platforms such as Facebook, Twitter, Instagram, and more, there is a wealth of untapped data available that can greatly benefit customer services and improve brand offerings. To gain valuable insights into target customers, it is essential to utilize web analytics algorithms to collect online data effectively. Popular web analytic tools like Kissmetrics, Mixpanel, and Google Analytics provide companies with the ability to track website traffic and analyze it for strategic purposes.

Visualization and Storytelling: Although data visualization is an important aspect of a data science role, recruiters may not place significant emphasis on this skill during the hiring process. However, by utilizing data visualization techniques, individuals can effectively illustrate the outcomes derived from machine learning algorithms. As previously mentioned, this enables data scientists to explain and communicate their discoveries to both technical and non-technical audiences. Several helpful tools for data visualization include Matplotlib, d3.js, Tableau, and ggplot. Additionally, incorporating visually appealing charts and graphs of high quality facilitates clear and concise presentation of findings. Moreover it is crucial for a data scientist to possess a imaginative mindset in order to enhance their ability to tell stories with the provided information through engaging stakeholders when necessary.

Career Enhancement Programme – held on 06-05-2023

The Kalam Institute of Youth Excellence is a transformative initiative aimed at realizing the vision and mission of Dr. A. P. J. Abdul Kalam. Recently, in collaboration with ACE Engineering College, KIYE organized a one-day Career Enhancement Programme on May 6th, 2023. A total of 1200 students from ten engineering colleges participated in this programme where they were provided insights into various aspects of career planning and entrepreneurship. The Chief Guest for the event was Dr.G Sateesh Reddy, Scientific Advisor to Raksha Mantri, who spoke about the importance of mind management and developing creative skills through simple techniques using real-life examples. Additionally, as a special guest speaker, Dr.S Somanth – Secretary Department of Space & Chairman ISRO shared valuable insights on how to enhance skills in advanced technologies and explore global opportunities.

Faculty

FACULTY

Name of the Programme	CSE (Data Science)
Approved Intake (2025)	180
No. of Faculty Members	31
	Cadre	Number
	Professor	01
	Assoc. Professor	08
	Asst. Professor	23

Faculty Profile	Qualification	No. of Faculty
	Ph.D	03
	Ph.D(Pursuing)	14
	Post Graduate	13
Technical Staff	Technical Staff	01
	Programmers	04

Name	Dr. Ralla Suresh
Designation	Professor & HOD
Qualification	B.Tech, M.Tech, Ph.D
Professional Exp.	16 Years
Research Interests	Artificial Intelligence and Deep Learning
Registration Number	0862-150505-162448

Name	Dr. P. Ashok Kumar
Designation	Associate Professor
Qualification	B.Tech (CSE), M.Tech (CSE), Ph.D
Professional Exp.	15.9 Years Teaching \| 1 Year Industry
Research Interests	Sentiment Analysis
Registration Number	8672-150415-124752

Name	Dr. G. Lingaiah
Designation	Assistant Professor
Qualification	B.Tech (CSE), M.Tech (CSE), Ph. D(CSE)
Professional Exp.	23 Years
Research Interests	Machine Learning
Registration Number	9754-150506-135923

Name	Mr. Md.Younus Shariff
Designation	Associate Professor
Qualification	B.Tech., M.Tech
Professional Exp.	15 Years Teaching \| 1 Year Industry
Research Interests	MERN Stack and Mobile Development
Registration Number	70150405-155529

Name	Mr. S. Rajendra Kumar
Designation	Associate Professor
Qualification	M.Tech,(Ph.D)
Professional Exp.	21 Years
Research Interests	RF IC Inductor
Registration Number	8363-161223-145310

Name	Mrs. A Sarala Devi
Designation	Associate Professor
Qualification	MCA., M.Tech(CSE) (Ph.D)
Professional Exp.	13 Years
Research Interests	Artificial Intelligence, Neural Networks
Registration Number	37150404-195953

Name	Mr. Gollapalli Parwateeswar
Designation	Assistant Professor
Qualification	B.Tech, M.Tech, UGC NET (JRF)
Professional Exp.	4 Years Teaching \| 1 Year Industry
Research Interests	Computer Networks, Data Science
Registration Number	8056-220416-130520

Name	Mr. Balasani Avinash
Designation	Assistant Professor
Qualification	B.Tech[CSE]., M.Tech [CSE]
Professional Exp.	8 Years
Research Interests	Machine Learning
Registration Number	9794-220418-160447

Name	Mr. Kiran Babu Kommu
Designation	Assistant Professor
Qualification	B.Tech (CSE), M.Tech (CSE), (Ph.D)
Professional Exp.	13 Years
Research Interests	Computer Networks, Data Science
Registration Number	1715-040613-1716

Name	Mrs. Pilligundla Niharika
Designation	Assistant Professor
Qualification	B.Tech (CSE), M.Tech (CSE), (Ph.D)
Professional Exp.	9 Years
Research Interests	Machine Learning
Registration Number	29150404-150258

Name	Mrs. Yerpula Vanitha
Designation	Assistant Professor
Qualification	M.Tech
Professional Exp.	5 Years (System Analyst) 1 Year (Assistant Professor)
Research Interests	Database Management System, Cyber Security
Registration Number	0083-220706-152425

Name	Mrs. B. Saritha
Designation	Assistant Professor
Qualification	B.Tech (CSE), M.Tech (CSE), (Ph.D)
Professional Exp.	8 Years
Research Interests	Machine learning, Data Science
Registration number	3373-170915-114707

Name	Mrs. Vagolu Vanaja
Designation	Assistant Professor
Qualification	B.Tech., M.Tech (CSE)
Professional Exp.	Teaching	Industry
	7 Years	8 Years
Research Interests	Computer networks, Data mining
Registration Number	6004-190108-114004

Name	Mr. Vanama Pavan Kumar
Designation	Assistant Professor
Qualification	B.Tech(IT)., M.Tech(CSE)
Professional Exp.	6 Years
Research Interests	Machine Learning, Big Data Analytics
Registration Number	98150331-122241

Name	Mr. Hari Krishna Mallu
Designation	Assistant Professor
Qualification	B.TECH (IT), M.TECH (CSE), (PhD), TSSET-2023
Professional Exp.	12 Years
Research Interests	Cryptography
Registration Number	8285-201108-114902

Name	Mrs. Turai Swathi
Designation	Assistant Professor
Qualification	B.Tech (CSE), M.Tech (CSE), (Ph.D)
Professional Exp.	5 Years
Research Interests	Artificial Intelligence, Data Mining, and Network Security
Registration Number	4735-190827-134221

Name	Mrs. R Suruthi Sutharsana
Designation	Assistant Professor
Qualification	BE (IT), ME (IT), (PhD)
Professional Exp.	3.6 Years
Research Interests	Wireless sensor Network
Registration Number	4780-230324-132103

Name	Mrs. B. Sreelatha
Designation	Assistant Professor
Qualification	M.TECH
Professional Exp.	3 Years
Research Interests	Cyber Security
Registration Number	0934-170103-132946

Name	Mrs.K.Sukeerthi
Designation	Assistant Professor
Qualification	B.Tech(CSE), M.Tech(CSE), (Ph.D)
Professional Exp.	2.6Years
Research Interests	Cloud Computing
Registration Number	7123-220707-140559

Name	Mr. Kalvacherla Kiran
Designation	Assistant Professor
Qualification	MSc(CS), M.Tech(CSE), (Ph.D)
Professional Exp.	11 Years Teaching \| 2.4 Years Industry
Research Interests	Java, MachineLearning,Optimization Device Detection Using Machine Learning,DBMS
Registration Number	9132-160306-172210

Name	Mr. Y. V. S. Durga Prasad
Designation	Associate Professor
Qualification	B.Tech (ECE), M.Tech (Communication System), PGDM-Marketing., (Ph.D)
Professional Exp.	14.6 Years Teaching \| 2 Years Industry
Research Interests	Computer Networks
Registration Number	53150406-154658 (Others)

Name	Mr. T. Sivalakshmaiah
Designation	Assistant Professor
Qualification	B.Tech, M.Tech
Professional Exp.	14 Years
Research Interests	Machine Learning and Quantum Computing
Registration Number	6157-220621-114218

Name	Mr. J. Sampath Kumar
Designation	Associate Professor
Qualification	M.Tech., (Ph.D)
Professional Exp.	8 Years Teaching \| 3 Years Industry
Research Interests	Computer Networks/wireless communications
Registration Number	9591-150418-172929 (Others)

Name	Mr. Shaik Nagur Vali
Designation	Assistant Professor
Qualification	M.Tech
Professional Exp.	5.6 Years
Research Interests	Devops,AWS Cloud, Data Science
Registration Number	8328-240130-115807 (Others)

Name	Mrs. Ayesha Osmani
Designation	Assistant Professor
Qualification	M.Tech
Professional Exp.	2 Years
Research Interests	Cyber Security
Registration Number	8686-210701-155006

Name	Mr. PEESALA ILANNA
Designation	Assistant Professor
Qualification	B.Tech (IT), M.Tech (CSE), (Ph.D)
Professional Exp.	9 Years
Research Interests	Data Structure, Data Mining, Bioinformatics
Registration Number	1044-160223-143852

Name	Mr. H. Kalyan Rao
Designation	Assistant Professor
Qualification	B. Tech (IT), M. Tech (CSE), PhD CSE (Pursuing)
Professional Exp.	9 years Teaching \| 1 Year Industry
Research Interests	Cloud Computing, Artificial Intelligence, Machine Learning, Operating Systems
Registration Number	4530-230227-162939

Name	Mr. Sujith Kumar Lone
Designation	Assistant Professor
Qualification	B.Tech (CSE), M.Tech (CSE)
Professional Exp.	1 year
Research Interests	Data Structure, IoT
Registration Number	9929-240701-140517

Name	Ms. Syeda Tahniyath Begum
Designation	Assistant Professor
Qualification	B. Tech (CSE)., M. Tech (CSE)
Professional Exp.	–
Research Interests	Java,cloud computing, data science
Registration Number	9057-260213-122326

Name	Mr. Pulla Manoj Kumar
Designation	Assistant Professor
Qualification	B. Tech (CSE)., M. Tech (CSE)
Professional Exp.	–
Research Interests	Artificial Intelligence, Machine Learning, Data Science, Natural Language Processing
Registration Number	–

AI & DS

Name	Mr. Vamsi Krishna Cheedepudi
Designation	Associate Professor
Qualification	M.Tech, (PhD)
Professional Exp.	13 Years
Research Interests	Artificial Intelligence and Machine Learning
Registration Number	4622-240216-131938

Name	Mrs. K. Swathi
Designation	Assistant Professor
Qualification	M.Tech
Professional Exp.	1 Years
Research Interests	Artificial Intelligence and Machine Learning
Registration Number	–

Name	Mr. S.Raja Sekhar Babu
Designation	Assistant Professor
Qualification	MCA., M.Tech (CSE)
Professional Exp.	10 Years
Research Interests	Java, Web Technologies, Operating Systems
Registration Number	3113-150409-121939

Name	Ms. H. V. Lalitha Parameswari
Designation	Assistant Professor
Qualification	M.Tech (Information Technology), IIIT Hyderabad
Professional Exp.	10 Months
Research Interests	Machine Learning, Data Science
Registration Number	7005-250402-125707

Achievements

ACHIEVEMENTS

Academic Year	Achievements	Other Achievements
2023-2024	Journals \| Conferences \| Books \| Patents	Certifications

Faculty Achievements

JOURNALS (A.Y: 2023-2024)

S.No.	Name of the Faculty	Title of the Paper	Journal Name	ISSN Number / DOI Number	Publicatio n Details	Remarks
1.	Dr. P. Chiranjeevi	A Survey: Recommender System For Trustworthy	Juni Khyat	ISSN: 2278-4632 Vol-13, Issue-04, No.01,	(UGC Care Group I Listed Journal)	April : 2023
2.	Dr. P. Chiranjeevi	Harnessing Textual Data For Early Customer Churn Prediction	Parishodh Journal	ISSN NO:2347-6648, Volume XIII, Issue III, ISSN NO:2347-6648	(UGC Care Group I Listed Journal)	March/ 2024
3.	Dr. P. Chiranjeevi	Driven Context-Aware Sentiment Analysis using BERT - Bi-LSTM for Emotion Insights	International Journal of Intelligent Systems and Applications in Engineering (IJISAE) ISSN: 2147-6799	ISSN: 2147-6799 www.ijisae.org	Final Decision: Accepted	March/ 2024
4	B. Saritha	Unravelling Silence: Speech to Indian Sign Language Translation	Parishodh Journal	ISSN NO: 2347-6648 Volume XIII, ISSUE IV	(UGC Care Group I Listed Journal)	April 2024
5	B.Saritha	Unveiling Political Insights From Social Media Using Machine Learning And NLP	Parishodh Journal	ISSN NO: 2347-6648 Volume XIII, ISSUE III	(UGC Care Group I Listed Journal)	March 2024
6	P.Niharika	Post Covid image segmentation of Lungs and disease prediction.	Parishodh Journal 31st March 2024	ISSN NO: 2347-6648 Volume XIII, Issue III, March/2024	(UGC Care Group I Listed Journal)	March 2024
7	A Sarala Devi	Revolutionize Secure Smart Banking: Harnessing Central FPGA for Enhanced Distance Analysis and Security	TELEMATIQUE	ISSN:1856-4194 Volume 23 Issue 1,2024	(UGC Care Group I Listed Journal)	Feb 2024
8.	A Sarala Devi	Unlocking the potentinal of Human Activity Recognition: Harnessing SmartDevice Technology	Parishodh Journal	ISSN:2347-6648 Volume XIII, Issue III	(UGC Care Group I Listed Journal)	March/20 24
9.	A. Sarala Devi	The Phisherman’s Gambit	WJARR	Ref no.WJARR-2024- 1036	ACCEPTE D	April
10	M. Hari Krishna	Mapping Factors Affecting Global Lifespan	Parishodh Journal	ISSN NO: 2347-6648 Volume XIII, ISSUE III	(UGC Care Group I Listed Journal)	March 2024
11	K Kiran Babu	Unraveling Genetic Disorders – A Machine Learning Prophetic Reach	Parishodh	ISSN NO: 2347-6648	UGC Approved Journal	March 2024
12	K Kiran Babu	Analytical CRM using Soft Computing Techniques: A Study of Implications of Feature Selection	Chelonian Conservation and Biology	ISSN: 1071-8443	Scopus Indexed	November 2023
13	P. Ashok Kumar	Vector Based Machine Learning Model For Review Sentiment Analysis	JuniKhyat	ISSN: 2278-4632, Vol- 14, Issue-3, No.02	(UGC Care Group I Listed Journal)	March/ 2024
14	P. Ashok Kumar	Echosigna Fusion: From Gesture To Voice	Parishodh Journal	ISSN NO:2347-6648, Volume XIII, Issue III, ISSN NO:2347-6648	(UGC Care Group I Listed Journal)	March/ 2024
15	P. Ashok Kumar	Event Driven Context- Aware Sentiment Analysis using BERT - Bi-LSTM for Emotion Insights	International Journal of Intelligent Systems and Applications in Engineering (IJISAE)	ISSN: 2147-6799 www.ijisae.org	Final Decision: Accepted (Scopus Indexed)	March/ 2024
16	Devisha Arunadevi Tiwari	Metaverse mingle: Discovering dating intentions in metaverse ,2023\|Journal article Authors:	Journal of Retailing and Consumer Services	DOI: 10.1016/j.jretconser.202 3.103509\| EID: 2-s2.0- 85166326366\|Part of ISSN: 09696989	SCI, Scopus, Web of Science, UGC Care.	November 2023
17	Devisha Arunadevi Tiwari	The Role of Enablers and Barriers in the Upskilling and Reskilling of Users Through Professional Skilling Programs on EdTech Platforms	IEEE Transactions on Engineering Management	DOI: 10.1109/TEM.2023.332 8261	SCI, Scopus, Web of Science, UGC Care.	March 2024
18	Devisha Arunadevi Tiwari	Fast Encryption Scheme for Secure Transmission of e-Healthcare Images	Journal of Image, Graphics and Signal Processing (IJIGSP)	DOI: https://doi.org/10.5815/i jigsp.2023.05.07	Scopus, Web of Science, UGC Care.	2023-05- 14
19	R Suruthi Sutharsana	A Semantic Approach For Short Answer Grading	Parishodh Journal	ISSN NO:2347-6648, Volume XIII, Issue III, ISSN NO:2347-6648	(UGC Care Group I Listed Journal)	March/ 2024

Academic Year	Achievements	Other Achievements
2023-2024	Journals \| Conferences \| Books \| Patents	Certifications

CONFERENCES (A.Y: 2023-2024)

Sl. No.	Name of the Faculty	Title of the Research Paper	Conference Name & Details	Publisher	Month & Year
1.	Dr. P. Chiranjeevi	Investigating Context-Aware Sentiment Classification Using Machine Learning Algorithms	Final Decision: Accepted	Springer Nature Singapore Pte Ltd.	2024
2.	Padmini Chattu	Exploring Convolution Neural Networks for Image Classification in Medical Imaging	IEEE	10.1109/IITCEE59897.2024.10467794	20 March 2024
3.	P. Ashok Kumar	Investigating Context-Aware Sentiment Classification Using Machine Learning Algorithms	Final Decision: Accepted	Springer Nature Singapore Pte Ltd.	April/2023
4.	P. Ashok Kumar	Experimentation Analysis of VQC and QSVM on Sentence Classification in Quantum Paradigm	Final Decision: Accepted	IEEE	March/2024
5	Devisha Arunadevi Tiwari	AI Days 2024	AI Days for Society	Swecha /JNTUH	March/2024
6	Ashwani Attri	AI Days 2024	AI Days for Society	Swecha /JNTUH	March/2024
7	Saritha Banoth	AI Days 2024	AI Days for Society	Swecha /JNTUH	March/2024
8	Revanth Sankul	AI Days 2024	AI Days for Society	Swecha /JNTUH	March/2024

Academic Year	Achievements	Other Achievements
2023-2024	Journals \| Conferences \| Books \| Patents	Certifications

BOOKS (A.Y: 2023-2024)

Sl.

No.

Name of the Faculty

Title of Book

ISBN

Publisher

Year

Dr. P.Chiranjeevi

Cloud Security Fundamentals : Building A Secure Cloud Infrastructure

ISBN: 9788196280741

Well Tech International Publishing House, Govt of India MSME, ISO 9001-2015

2023

A. Sarala Devi

Distributed and Parallel Computing

ISBN:978-81-963245-3-7

Deccan International Academic Publishers

2023

A. Sarala Devi

Software Engineering

ISBN:978-81-963533-6-0

Indo-Continental Academic Publishers

2023

Padmini Chattu

Data Science For Engineers

ISBN:978-93-5757-914-8

Scientific International Publishing House (SIPH)

2023

Academic Year	Achievements	Other Achievements
2023-2024	Journals \| Conferences \| Books \| Patents	Certifications

PATENTS (A.Y: 2023-2024)

Sl.
No.

Name of the Faculty

TITLE OF THE INVENTION

INTERNATIONAL CLASSIFICATION

Month & Year of Publication

APPLICATION NO.

Dr. P.
Chiranjeevi

Assessing AI Contribution to Anti- Corruption Operations

Intellectual Property India, THE PATENTS ACT, 1970 (39 OF 1970)
THE PATENTS RULES, 2003

17/02/2023 Publication Date (U/S 11A)

App No. 202341009147

Dr. P.
Chiranjeevi

Effective Iot Monitoring By Applying Ml Technologies Toreduce Dimensions For Traffic Data And The Detection Ofintrusions

Intellectual Property India, THE PATENTS ACT, 1970 (39 OF 1970)
THE PATENTS RULES, 2003

PUBLICATION 12/01/2024 DATE (U/S 11A)

APPLICATION NUMBER: 202341084819

B.Saritha

A Face Detection and Degeneration System based on Deep Convolutional Neural Newtworks.

Intellectual Property India.

Publication Date (U/S 11A) 30/06/2023

Application No: 202341037886

K Kiran Babu

A Novel Antenna System For IoT Application And Method
Thereof

Intellectual Property India

16/06/2023

202341036939

K Kiran Babu

Deep Learning And AI For Enhanced Image And Video Analysis

Intellectual Property India

08/03/2024

202441009106

V Pavan Kumar

Deep Learning And AI For Enhanced Image And Video Analysis

Intellectual Property India

08/03/2024

202441009106

Academic Year	Achievements	Other Achievements
2023-2024	Journals \| Conferences \| Books \| Patents	Certifications

Certification Course / Training Programs (A.Y: 2023-2024)

S.No.	Name of the Faculty	Course Type/ Training Type	Course Name	Month
1.	Mrs.VANAJA VAGOLU	NPTEL	Introduction to Internet of Things	Jan-Apr 2024
2	Mrs. NIHARIKA PILLIGUNDLA	NPTEL	Edge Computing	Jan-Mar 2024
3	Mrs. NIHARIKA PILLIGUNDLA	NPTEL	Database Management System	Jan-Mar 2024
4	Mr.PAVAN KUMAR VANMA	NPTEL	Introduction to Internet of Things	Jan-Apr 2024
5	Mrs. SARITHA BANOTH	NPTEL	The Joy of Computing using Python	Jan-Apr 2024
6	Mrs. PADMINI CHATTU	NPTEL	Programming in Java	Jan-Apr 2024
7	Mr. KIRAN BABU KOMMU	Digital Skill Readiness Program, Trained by Wipro	.NET Full Stack	05/08/2024
8	Mr. SANKUL REVANTH	Digital Skill Readiness Program, Trained by Wipro	Java Full Stack	05/08/2024
9	Mr. MOHAMMED YOUNUS SHARIFF	Digital Skill Readiness Program, Trained by Wipro	Java Full Stack	05/08/2024

Student Achievements

SNO	DATE	YEAR	ROLL NO	NAME	ACHIEVEMENT	PHOTO
1	03.08.2024	IV-I	21AG1A6728	K LAXMI PRASANNA	Selected in Zithara.ai company as Software Developer with package 5.0 to 6.0 LPA
2	03.08.2024	IV-I	21AG1A6753	PENMETSA LOKESH KARTHIK	Selected in Zithara.ai company as Software Developer with package 5.0 to 6.0 LPA
3	05.10.2024	IV-I	21AG1A6764	MEGHANA VIJAYARAGHAVAN	Selected in KORE.AI Company as Software Developer with package 8.5 LPA

Role of Honors

Department of CSE (Data Science)

S.No	Batch	Hall Ticket Number	Student Name	CGPA / Percentage
1	2021-2025	21AG1A6715	CHANDRAGIRI BHAVANA	8.97
2	2021-2025	22AG5A6702	POTHARAJU PRANEETHA	8.97
3	2020-2024	20AG1A6703	AENUGU AKSHITHA	9.26

Infrastructure

INFRASTRUCTURE

GPU SERVER CONFIGURATION

Hardware configuration	Dell OptiPlex 7080 Tower with 500w upto 92% efficiency PSU Intel Core i7 10700 10^th Generation 32GB DDR4 RAM, M.2 256SSD, 1TB HDD, NVIDIA GeForce RTX 2070 Super 8GB Dell wired keyboard, Windows 10 pro (64bit)
Operating System	Windows10, Ubuntu 16.04.
Open-Source Tools	Python 3.6.5, R-Language, OpenCV, C, C++, JAVA.
Licensed Tools	Oracle 12.1.0.2.0 with analytics.
Other resources	High Speed Internet, Projector, White Board, Intercom

Client system Configuration:

Hardware configuration	Intel i5 processor with 2.5GHz clock frequency, 4GB RAM, 500GB Hard Disk.
Operating System	Windows10, Ubuntu 16.04.
Open Source Tools	Python 3.6.5, R-Language, OpenCV, C, C++, JAVA.
Licensed Tools	Oracle 12.1.0.2.0 with analytics.
Other resources	High Speed Internet, Projector, White Board, Intercom

Course Structure

COURSE STRUCTURE

I B.Tech I-Semester

S. No	Course Code	Course Title
1	MA101BS	Mathematics – I
2	CH102BS	Engineering Chemistry
3	EE103ES	Basic Electrical Engineering
4	ME105ES	Engineering Workshop
5	EN105HS	English
6	CH106BS	Engineering Chemistry Lab
7	EN107HS	English Language and Communication Skills Lab
8	EE108ES	Basic Electrical Engineering Lab
9	MC109	Python Programming
10	MC110	Aptitude & Reasoning

I B.Tech II-Semester

S. No	Course Code	Course Title
1	MA201BS	Mathematics – II
2	PH202BS	Applied Physics
3	CS203ES	Programming for problem Solving
4	ME204ES	Engineering Graphics
5	PH205BS	Applied Physics Lab
6	CS206ES	Programming for problem Solving Lab
7	MC207ES	Environmental Science
8	MC208	Business English

II B.Tech I-Semester

S.No	Course Code	Course Title
1	CS301PC	Discrete Mathematics
2	CS302PC	Data Structures
3	MA305BS	Mathematical and Statistical Foundations
4	CS304PC	Computer Organization and Architecture
5	CS310PC	Advanced Python Programming
6	SM302MS	Business Economics & Financial Analysis
7	CS307PC	Data Structures Lab
8	CS311PC	Advanced Python Programming Lab
9	MC309HS	Gender Sensitization Lab

II B.Tech II-Semester

S.No	Course Code	Course Title
1	CS409PC	Formal Language and Automata Theory
2	CS410PC	Software Engineering
3	CS403PC	Operating Systems
4	CS404PC	Database Management Systems
5	CS405PC	Java Programming
6	CS406PC	Operating Systems Lab
7	CS407PC	Database Management Systems Lab
8	CS408PC	Java Programming Lab
9	MC409HS	Constitution of India

Syllabus

SYLLABUS

R20 Regulation – CSE(DS)

CSD R-20 III-I Syllabus

CSD R-20 III-II Syllabus

CSD R-20 IV-I Syllabus

CSD R-20 IV-II Syllabus

R22 Regulation – CSE(DS)

CSD R-22 I-I Syllabus

CSD R-22 I-II Syllabus

CSD R-22 II-I Syllabus

CSD R-22 II-II Syllabus

CSD R-22 III-I Syllabus

CSD R-22 III-II Syllabus

CSD R-22 IV-I Syllabus

CSD R-22 IV-II Syllabus

R24 Regulation – CSE(DS)

CSD R-24 I-I Syllabus

CSD R-24 I-II Syllabus

CSD R-24 II-I Syllabus

CSD R-24 II-II Syllabus

R25 Regulation – CSE(DS)

CSD R-25 I-I Syllabus

CSD R-25 I-II Syllabus

Events & Activities

Report on
Data Carnival 2.0
On 17&18 Feb 2026

The Department of Data Science organized “Data Carnival 2.0” on 17th & 18th February 2026 at the Seminar Hall and Data Science Laboratory of Ace Engineering College. The event aimed to provide students with a platform to showcase their technical knowledge, creativity, and analytical skills in the field of Data Science and Emerging technologies

Report on
Industrial visit to we hub Hyderabad
On 17.03.2026

An industrial visit was organized for the III Year students of the Computer Science and Design (CSD) department of ACE Engineering College to WE Hub, Hyderabad. The visit aimed to provide students with exposure to real-time entrepreneurial ecosystems, innovation practices, and startup culture. A total of 41 students, accompanied by 02 faculty members, participated in the visit.

Report on
Data Carnival 2.0 on 17&18 Feb 2026

The event commenced with a Welcome address by the Head of the Department, emphasizing the growing importance of Data Science in today’s digital era. In Forenoon session of 17/02/2026, The Coding Contest is conducted in the C–hunt for the Registered Candidates of I year Students in the Data Science Laboratory. Coding contest is conducted at 3 Level. In the Round 1 students attempted beginners level questions, Round 2 Students attempted Intermediate level Questions. Round 3 participants solved story telling problems using C language. It was coordinated by the Faculty Coordinators and monitored by Lab Programmers, Student Volunteers.
The Coding Contest is conducted in the Decode the Snake for the Registered Candidates of II year Students in the Data Science Laboratory. Coding contest is conducted at 3 Level. In the Round 1 students attempted beginners level questions, Round 2 Students attempted Intermediate level Questions. Round 3 participants solved story telling problems using Python Programming Language. It was Coordinated by the Faculty Coordinators and monitored by Lab Programmers, Student Volunteers

Technical Symposium 2.0 – A Huge Success!

The Departments of CSE (Data Science), AIML, and AIDS organized a remarkable Technical Symposium 2.0 in association with CODE (Club of Data Engineers) on 28th March 2024. The symposium featured insightful sessions and engaging activities on the following topics:

1. Tech-Quiz
2. Cognitive Science
3. Debugging

Open to all departments, the event saw an overwhelming participation from students across various fields. Their enthusiasm, passion, and knowledge made the Technical Symposium 2.0 a grand success, further strengthening the spirit of innovation and collaboration among the participants.

“DATA 2025 CARNIVAL” – A Grand Success!

The Department of Computer Science Engineering (Data Science) hosted a two-day event, “DATA 2025 CARNIVAL”, which turned out to be a resounding success! The carnival featured three exciting and engaging events:

1. C-HUNT PROCHAMPS
2. IDEATHON QUIZ
3. E-SPORTS EXTRA CURRICULAR

The event was open to all branches, and students participated with great enthusiasm, showcasing their talents and competitive spirit. Thanks to their active involvement, the carnival was a remarkable success, fostering creativity, teamwork, and fun among all participants.

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Program Report

TECHNICAL FEAST – held on 10/03/2023

Technical feast is organized by CODE. It is a coding competition conducted for both 2nd and 3rd year students. This test is based on Python programming & Quantitative aptitude and Reasoning

INDUSTRIAL VISIT TO T-HUB – held on 19/12/2022

T-Hub is creating impact for startups, corporations and other innovation ecosystem stakeholders-HUB helps the students who have ideas to implement for the society but who are financially weak. T-hub encourage them to implement their ideas

OPEN INTERACTION – held on 17/10/2022

Open interaction is organized by CODE. This open interaction is conducted for making students to come up with new thoughts and expressing their ideas with everyone.